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Transcript
Health at a Glance 2011
OECD INDICATORS
Contents
OECD 50th Anniversary: Measuring progress in health in OECD countries over the past fifty years
Chapter 1. Health status
Health at a Glance 2011
Chapter 2. Non-medical determinants of health
Chapter 3. Health workforce
OECD INDICATORS
Chapter 4. Health care activities
Chapter 5. Quality of care
Chapter 6. Access to care
Chapter 7. Health expenditure and financing
Chapter 8. Long-term care
Health at a Glance 2011
OECD (2011), Health at a Glance 2011: OECD Indicators, OECD Publishing.
http://dx.doi.org/10.1787/health_glance-2011-en
This work is published on the OECD iLibrary, which gathers all OECD books, periodicals and statistical databases.
Visit www.oecd-ilibrary.org, and do not hesitate to contact us for more information.
ISBN 978-92-64-11153-0
81 2011 10 1 P
-:HSTCQE=VVVZXU:
OECD INDICATORS
Please cite this publication as:
Health at a Glance
2011
OECD INDICATORS
This work is published on the responsibility of the Secretary-General of the OECD. The
opinions expressed and arguments employed herein do not necessarily reflect the official
views of the Organisation or of the governments of its member countries.
This document and any map included herein are without prejudice to the status of or
sovereignty over any territory, to the delimitation of international frontiers and boundaries
and to the name of any territory, city or area.
Please cite this publication as:
OECD (2011), Health at a Glance 2011: OECD Indicators, OECD Publishing.
http://dx.doi.org/10.1787/health_glance-2011-en
ISBN 978-92-64-11153-0 (print)
ISBN 978-92-64-12610-7 (HTML)
Annual: Health at a Glance
ISSN 1995-3992 (print)
ISSN 1999-1312 (HTML)
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use
of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli
settlements in the West Bank under the terms of international law.
Photo credits: Cover © Shutterstock/Yuri Arcurs. Chapter 1: © Comstock/Jupiterimages. Chapter 2: © Comstock/
Jupiterimages. Chapter 3: © Randy Faris/Corbis. Chapter 4: © Vincent Hazat/Photo Alto. Chapter 5: © CREATAS/
Jupiterimages. Chapter 6: © onoky – Fotolia.com. Chapter 7: © Tetraimages/Inmagine. Chapter 8: © Thinkstock/
iStockphoto.com.
Corrigenda to OECD publications may be found on line at: www.oecd.org/publishing/corrigenda.
© OECD 2011
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at [email protected]
FOREWORD
Foreword
T
his 2011 edition of Health at a Glance: OECD Indicators presents the most recent comparable
data on key indicators of health and health systems across OECD countries. For the first time, it
features a chapter on long-term care.
This edition presents data for all 34 OECD member countries, including the four new member
countries: Chile, Estonia, Israel and Slovenia. Where possible, it also reports comparable data for Brazil,
China, India, Indonesia, the Russian Federation, and South Africa, as major non-OECD economies.
The production of Health at a Glance would not have been possible without the contribution
of OECD Health Data National Correspondents, Health Accounts Experts, and Health Care Quality
Indicators Experts. The OECD gratefully acknowledges their effort in supplying most of the data and
qualitative information contained in this publication. The OECD also acknowledges the contribution
of other international organisations, especially the World Health Organization, the World Bank and
Eurostat, for sharing some of the data presented here, and the European Commission for supporting
data development.
This publication was prepared by a team from the OECD Health Division under the co-ordination of
Gaétan Lafortune and Michael de Looper. Chapter 1 and Chapter 2 were prepared by Michael de Looper;
Chapter 3 by Michael Schoenstein, Gaëlle Balestat and Rebecca Bennetts; Chapter 4 by Gaétan Lafortune
and Gaëlle Balestat; Chapter 5 by Gerrard Abi-Aad, Vladimir Stevanovic, Rie Fujisawa and
Niek Klazinga; Chapter 6 by Michael de Looper and Marion Devaux (with a contribution from
Lothar Janssen of the German Federal Ministry of Health); Chapter 7 by David Morgan, Rebecca Bennetts
and Roberto Astolfi; and Chapter 8 by Jérôme Mercier, Margarita Xydia-Charmanta and
Francesca Colombo. Statistical support was provided by Nelly Biondi. This publication benefited from
comments and suggestions by Valérie Paris and Mark Pearson.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3
OECD 50th Anniversary
Measuring Progress
in Health in OECD Countries
over the Past Fifty Years
W
ork on health at the OECD began in the early 1980s, as part of an examination of the
strong growth in health expenditure in the prior decade. In the 1980s and the 1990s, this
work focused largely on building a robust database that could be used for comparative
analyses of health systems, beginning with comparable data on health spending. This
developmental work led to the release of the first version of the OECD manual A System of
Health Accounts in 2000. In the ten years since the launch of the OECD Health Project in 2001,
OECD work has broadened to address some of the main challenges that policy makers face
to improve the performance of their countries’ health systems (see box on next page).
As work on both health data and health policy has expanded, so has co-operation with
other international organisations, in particular the World Health Organization (WHO) and
the European Commission. A first framework of co-operation was signed between the
OECD Secretary-General and the WHO Director-General in 1999, and this agreement was
further extended in 2005 to cover not only statistical work but also analytical work related
to the financing and delivery of health care services. At the end of 2005, the OECD, WHO
and Eurostat (the European statistical agency) launched a first joint data collection based
on the work already undertaken for A System of Health Accounts, to improve the availability
and comparability of data on health expenditure and financing. Building on this success, a
new joint collection between the three organisations was launched in 2010 to gather
comparable data on non-monetary health care statistics. This strong collaboration avoids
duplication of work and ensures synergies between the three organisations.
The OECD Health Data database, the main source for this publication, has been built up
over the past 30 years in close co-operation with officials from all OECD countries and
other international organisations. It provides a unique source of information to compare
the evolution of health and health systems across OECD countries, with some time series
spanning the whole 50-year period since the Organisation’s foundation.
Looking back at the evolution of health and health systems since the OECD was
created in 1961, three major trends stand out:
1. The remarkable gains in life expectancy.
2. The changing nature of risk factors to health.
3. The steady growth in health spending, which has exceeded GDP growth by a substantial
amount.
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5
Key events related to OECD work on health
1961: Creation of the OECD as a successor to the Organisation for European Economic
Co-operation.
1980: OECD Conference on Social Policies calls for more analysis on health expenditure
growth, leading to the beginning of OECD work on health under the Working Party
on Social Policy.
1985: First OECD report on health, Measuring Health Care, 1960-1983: Expenditure, Costs and
Performance (including the first paper edition of the OECD Health Database).
1991: First electronic edition of OECD Health Data.
1999: First OECD/WHO Framework for Co-operation.
2000: Release of OECD manual A System of Health Accounts to improve the comparability of
data on health expenditure and financing.
2001: Launch of the OECD Health Project to address key policy challenges in improving the
performance of OECD health systems.
2001: Creation of OECD Group on Health to oversee the OECD Health Project (the name and
mandate of this group was changed in 2006 to the OECD Health Committee).
2001: First edition of Health at a Glance to present key indicators from the database in a
user-friendly format.
2003: Launch of OECD Health Care Quality Indicators (HCQI) project to develop a set of
indicators measuring and comparing quality of care across countries.
2004: First OECD Health Ministerial Meeting in Paris to discuss the main findings from the
OECD Health Project. Release of publication Towards High-Performing Health Systems,
along with a series of policy studies.
2005: Renewal of the OECD/WHO Framework for Co-operation, extending the co-operation
beyond statistical work to include analysis of health systems issues related to
financing, human resources and efficiency.
2005: First annual OECD, WHO and Eurostat Joint Health Accounts Questionnaire to increase
the availability and comparability of data on health expenditure based on A System
of Health Accounts.
2010: New OECD, WHO (European region) and Eurostat Joint Questionnaire on non-monetary
health care statistics to improve availability and comparability of data on health
workforce and other resources.
2010: Release of editions of Health at a Glance covering European and Asia/Pacific regions.
2010: Release of first OECD report on prevention, Obesity and the Economics of Prevention – Fit
Not Fat, identifying trends in obesity and cost-effective interventions to address the
obesity epidemic.
2010: Second OECD Health Ministerial Meeting in Paris to discuss health system priorities in
the aftermath of the economic crisis. Release of first HCQI publication Improving
Value in Health Care: Measuring Quality, and a series of policy studies in the publication
Value for Money in Health Spending.
2011: Second edition of the manual A System of Health Accounts released jointly by OECD,
WHO and Eurostat to promote greater comparability in health accounting systems in
developed and developing countries.
6
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
Remarkable gains in life expectancy
The health of populations in OECD countries has improved greatly over the past
50 years, with women and men living longer than ever before. Since 1960, life expectancy
has increased on average across OECD countries by more than 11 years, reaching nearly
80 years in 2009. The increase has been particularly noticeable in those OECD countries
that started with relatively low levels in 1960, such as Korea where life expectancy has
increased by a remarkable 28 years between 1960 and 2009. There have also been huge
gains in life expectancy in Turkey and Mexico as well as in Chile, one of the countries that
has recently joined the OECD. Japan has also achieved large gains and is now leading OECD
countries, with a life expectancy of 83 years. But many other countries are close behind.
In 2000, only 2 OECD countries had a total life expectancy of 80 years or more. By 2009,
22 countries had reached this milestone.
Life expectancy at birth, 2009 (or nearest year available),
and years gained since 1960
Life expectancy at birth, 2009
Years gained, 1960-2009
Japan
Switzerland
Italy
Spain
Australia
Israel
Iceland
Sweden
France
Norway
New Zealand
Canada
Luxembourg
Netherlands
Austria
United Kingdom
Germany
Greece
Korea
Belgium
Finland
Ireland
Portugal
OECD
Denmark
Slovenia
Chile
United States
Czech Republic
Poland
Mexico
Estonia
Slovak Republic
Hungary
Turkey
83.0
82.3
81.8
81.8
81.6
81.6
81.5
81.4
81.0
81.0
80.8
80.7
80.7
80.6
80.4
80.4
80.3
80.3
80.3
80.0
80.0
80.0
79.5
79.5
79.0
79.0
78.4
78.2
77.3
75.8
75.3
75.0
75.0
74.0
73.8
90
Years
80
70
60
50
40
15.2
10.9
12.0
12.0
10.7
9.9
8.6
8.3
10.7
7.2
9.7
9.4
11.3
7.1
11.7
9.6
11.2
10.4
27.9
10.2
11.0
10.0
15.6
11.2
6.6
10.5
21.4
8.3
6.7
8.0
17.8
6.5
4.4
6.0
25.5
0
5
10
15
20
25
30
Years
Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523177
These gains in life expectancy reflect large declines in mortality at all ages. Infant
mortality rates have declined sharply in all countries. Deaths from cardiovascular diseases
(comprising mostly heart attack and stroke) have also fallen dramatically. Although
cardiovascular diseases remain the leading cause of death in OECD countries, mortality
rates have been cut by more than half since 1960. Falls in important risk factors for heart
and cerebrovascular diseases, including smoking, combined with improvements in
medical treatment, have played a major role in reducing cardiovascular mortality rates.
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7
The gender gap in life expectancy was 5.5 years on average across OECD countries
in 2009, with average life expectancies reaching 82.2 years for women compared with
76.7 years for men. While the gender gap tended to widen in the 1960s and the 1970s, since
the 1980s it has narrowed in most OECD countries because of higher gains in longevity for
men. This can be attributed at least partly to the narrowing of differences in risk-increasing
behaviours such as smoking, accompanied by sharp reductions in mortality rates from
cardiovascular diseases among men.
There have also been large gains in life expectancy at age 65. Women in OECD
countries can now expect to live an additional 20 years after 65 (up from 15 years in 1960),
while men can expect to live another 17 years (up from 13 years in 1960). Whether longer
life expectancy is accompanied by good health and functional status among ageing
populations has important implications for health and long-term care systems.
The changing nature of risk factors to health in OECD countries
Although some of the gains in longevity can be explained by a reduction in important
risk factors to health, much of the burden of diseases in OECD countries nowadays is linked
to lifestyle factors, with tobacco smoking, alcohol consumption, obesity, unhealthy diet
and lack of physical activity being largely responsible. People who live a physically active
life, do not smoke, drink alcohol in moderate quantities, and eat plenty of fruit and
vegetables have a risk of death in a given period that is less than one-fourth of those who
have invariably unhealthy habits (Sassi, 2010).
Many OECD countries have achieved remarkable progress in reducing tobacco
consumption over the past decades, although it still remains a leading cause of early death
and hence an important public health issue. Much of this decline can be attributed to
policies promoting public awareness campaigns, advertising bans and increased taxation.
In many OECD countries, smoking rates among adults have been cut by more than half
since the 1960s, from over 40% to less than 20% now. In both Canada and the United States,
smoking rates fell from 42% in 1965 to 16% in 2009.
Progress has been mixed concerning alcohol consumption. In many OECD countries,
consumption has fallen markedly since 1980, with curbs on advertising, sales restrictions
and taxation proving to be effective measures. On the other hand, consumption has risen
in some countries, notably in some Nordic countries, the United Kingdom and Ireland. The
worrying trend in these and other countries is the consumption pattern among younger
people, with the practice of heavy episodic drinking (“binge drinking”) increasing in recent
years. Heavy alcohol consumption has considerable impacts on health, as well as health
care and social costs. Causes of death directly or indirectly attributable to alcohol
consumption can include car accidents, violence and suicides, while diseases made more
likely by alcohol include cardiovascular diseases, cancers of the mouth and oesophagus,
and cirrhosis of the liver.
The alarming rise in obesity rates has risen at the top of the public health policy
agenda in recent decades, not only in OECD countries, but increasingly in developing
countries. Obesity is a key risk factor for numerous chronic conditions. Research shows
that severely obese people die 8-10 years earlier than those of normal weight, a value
similar to that for smokers. Obesity rates have doubled or even tripled in many countries
since 1980, and in more than half of OECD countries, 50% or more of the population is now
overweight, if not obese. The obesity rate among the adult population is the highest in the
United States, having risen from 15% in 1980 to 34% in 2008. Japan and Korea have the
lowest rates, although obesity is also rising in these two countries.
8
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
Increasing obesity rates among the adult population in OECD countries,
1990, 2000 and 2009 (or nearest years)
1990
%
35
2000
2009
30
31
34
19
23
24
25
25
25
13
14
11
10
6
12
9
9
9
11
6
6
11
9
10
9
6
6
4
2
3
3
4
5
8
8
10
9
10
15
12
20
13
12
14
13
14
12
15
8
11
15
11
15
13
15
7
13
16
14
17
9
13
17
11
14
17
18
20
8
12
20
16
22
21
23
22
25
5
27
30
Ko
re
a1
J
Sw ap
it z an 1
er
la
No nd
rw
ay
It a
Fr l y
an
Sw ce
Ne e
th de
er n
la
n
Au ds
s
De tr i a
nm
Be ar k
lg
iu
m
Is
Ge r ae
rm l
a
F i ny
nl
an
Ir e d
l
Po and
r tu
ga
Sp l
a
C a in
n
C z O ada
ec EC
h
Re D15
pu
Hu bli c
ng
a
L u Ic r y
Un xe e l a
i t e mb n d
d ou
Ki rg
1
ng
d
Au om
1
st
ra
l
Ne C ia 1
w hi
Ze le 1
al
a
Un M nd 1
i t e ex i
d co 1
St
at
es 1
0
Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
1. Data are based on measurements rather than self-reported height and weight.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523196
The obesity epidemic is the result of multiple and interacting dynamics, which have
progressively led to lasting changes in people’s lifestyles in relation to nutrition and
physical activity. Many OECD governments are now intensifying their efforts to promote a
culture of healthy eating and active living, with a large majority adopting initiatives aimed
at school-age children. A recent OECD report found that interventions aimed at tackling
obesity in at least three areas – health education and promotion, regulation and fiscal
measures, and counselling in primary care – are all effective in improving health and
longevity and have favourable cost-effectiveness ratios compared with scenarios in which
chronic diseases are treated only as they emerge. When multiple interventions are
combined in a strategy that targets different groups and determinants of obesity
simultaneously, overall health gains can be significantly enhanced without any loss in
cost-effectiveness (Sassi, 2010).
The steady growth in health spending
A third important trend observed over the past 50 years among health systems in
OECD countries has been the steady rise in health spending, which has tended to grow
faster than GDP. In 1960, health spending accounted for under 4% of GDP on average across
OECD countries. By 2009, this had risen to 9.6%, and in a dozen countries health spending
accounted for over 10% of GDP. The health spending share of GDP grew particularly rapidly
in the United States, rising from about 5% in 1960 to over 17% in 2009, which is
5 percentage points more than in the next two highest countries, the Netherlands and
France, which allocated 12% and 11.8% respectively.
Health spending per capita has also grown rapidly over the past few decades, at a rate of
6.1% per year in real terms on average across OECD countries during the 1970s, falling to
3.3% per year in the 1980s, then up to 3.7% in the 1990s, and 4.0% between 2000 and 2009.
The rate of growth of health spending has consistently exceeded GDP growth in each and
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
9
Health expenditure as a share of GDP, 1960-2009, selected OECD countries
Canada
%
18
Japan
United Kingdom
United States
OECD
16
14
12
8
6
4
2
0
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523215
every decade. But it has varied across countries. In the United States, health expenditure has
increased faster than in all other high-income OECD countries since 1970, increasing
five-fold in real terms, even taking account population growth.
In many countries, the health spending share of GDP has tended to rise strongly
during economic recessions, and then to stabilise or decline only slightly during periods of
economic expansion. Looking back at the recession of the early 1990s, some countries such
as Canada and Finland substantially reduced public expenditure on health in order to
reduce their budgetary deficits, leading to a noticeable reduction in the health spending
share of GDP for a few years. But these reductions in public spending on health often
proved to be short-lived and after a short period of cost-containment, growing supply and
demand of health services led to a revival of health expenditure growth which exceeded
GDP growth.
The public sector is the main source of health financing in all OECD countries, except
in Chile, Mexico and the United States. The public share of health spending was 72% of
total health expenditure on average across OECD countries in 2009, a share that has been
relatively stable over the past 20 years. However, there has been a convergence of the public
share of health spending among OECD countries in recent decades. Many of those
countries that had a relatively high public share in the early 1990s, such as Poland and
Hungary, have decreased their share, while other countries which historically had a
relatively low level (e.g. Portugal, Turkey) have increased their public share, reflecting
health system reforms and the expansion of public health insurance coverage.
As shown in this edition of Health at a Glance, while there is some relationship between
higher health spending per capita and higher life expectancy, the relationship tends to be
less pronounced as countries spend more on health. This indicates that many other factors
beyond health spending affect life expectancy. The weak correlation at high levels of health
expenditure suggests that there is room to improve the efficiency of health systems to
ensure that the additional money spent on health brings about measurable benefits in
terms of health outcomes.
10
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
Looking ahead
Over the past three decades, the OECD has played an important role in developing and
making available data and indicators to assess and compare the performance of health
systems. While substantial progress has been achieved, much work is still needed to
improve the comparability of data on health systems and to promote analysis to support
health policy making.
In renewing its mandate in June 2011, the OECD Health Committee reaffirmed that the
overarching objective of OECD work on health is to foster improvements in the
performance of health systems in OECD countries and in non-OECD countries as
appropriate. Following this mandate, the OECD will continue to share data, experiences
and advice regarding current and emerging health issues and challenges. As the health
sector represents an ever-growing share of OECD economies, measuring trends in health
expenditure, how spending is allocated between prevention and care, and whether this
brings about the expected benefits in terms of improved health outcomes, will become
increasingly important.
In October 2011, the OECD, in collaboration with WHO and Eurostat, released the
second edition of the manual A System of Health Accounts. This publication will help to
further improve the comparability of data on health expenditure through agreed
international standards. The OECD encourages co-operation among OECD countries and
non-members in developing health accounts on a consistent basis. It will continue to work
closely with WHO and Eurostat in administering an annual questionnaire to collect
comparable data based on this accounting system.
The OECD also continues to develop and collect indicators measuring the quality of
care and outcomes of health services, as part of the Health Care Quality Indicators project.
The developmental work carried out under this project is crucial for filling key gaps in
measuring the performance of health systems. At the same time, the OECD intends to
expand its analytical work to explore the reasons for the observed variations in quality of
care in OECD and partner countries, beginning with the areas of cancer and primary care.
In a context of population ageing, it will also become increasingly important to
monitor the financing, delivery and quality of long-term care services across OECD
countries. Building on recent work on long-term care (Colombo et al., 2011), the OECD is not
only pursuing the collection of more comparable data about long-term care systems, but
also analysing policies related to access, quality and financial sustainability of long-term
care systems, and sharing best practices.
Keeping with the spirit of openness that has characterised the OECD since its inception,
the Organisation is expanding its co-operation with non-member countries on issues where
collaboration may be mutually beneficial. The release of European and Asia/Pacific editions
of Health at a Glance in 2010 provided an example of such growing co-operation. The OECD
aims to promote the sharing of the health data systems and the policy expertise and
experience that reside in its member countries in order to foster improvements in health
system performance in non-member countries as well.
OECD AT 50 – HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
11
TABLE OF CONTENTS
Table of Contents
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
16
List of Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21
1. Health Status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23
1.1.
1.2.
1.3.
1.4.
1.5.
1.6.
1.7.
1.8.
1.9.
1.10.
1.11.
1.12.
Life expectancy at birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Premature mortality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mortality from heart disease and stroke. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mortality from cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mortality from transport accidents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Suicide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Infant mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Infant health: Low birth weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Perceived health status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Diabetes prevalence and incidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Cancer incidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
AIDS incidence and HIV prevalence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
24
26
28
30
32
34
36
38
40
42
44
46
2. Non-medical Determinants of Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
49
2.1.
2.2.
2.3.
2.4.
Tobacco consumption among adults. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Alcohol consumption among adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Overweight and obesity among adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Overweight and obesity among children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
50
52
54
56
3. Health Workforce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
59
3.1.
3.2.
3.3.
3.4.
3.5.
3.6.
3.7.
3.8.
3.9.
Employment in the health and social sectors . . . . . . . . . . . . . . . . . . . . . . . . . .
Medical doctors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Medical graduates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Remuneration of doctors (general practitioners and specialists) . . . . . . . . . .
Gynaecologists and obstetricians, and midwives . . . . . . . . . . . . . . . . . . . . . . .
Psychiatrists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Nurses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Nursing graduates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Remuneration of nurses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
60
62
64
66
68
70
72
74
76
4. Health Care Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
79
4.1.
4.2.
4.3.
4.4.
4.5.
4.6.
Consultations with doctors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Medical technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Hospital beds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Hospital discharges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Average length of stay in hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Cardiac procedures (coronary angioplasty) . . . . . . . . . . . . . . . . . . . . . . . . . . . .
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
80
82
84
86
88
90
13
TABLE OF CONTENTS
4.7.
4.8.
4.9.
4.10.
4.11.
Hip and knee replacement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
92
Treatment of renal failure (dialysis and kidney transplants). . . . . . . . . . . . . .
94
Caesarean sections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
96
Cataract surgeries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
98
Pharmaceutical consumption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5. Quality of Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Care for chronic conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.1. Avoidable admissions: Respiratory diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.2. Avoidable admissions: Uncontrolled diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Care for acute exacerbation of chronic conditions . . . . . . . . . . . . . . . . . . . . . . . . . . 108
5.3. In-hospital mortality following acute myocardial infarction. . . . . . . . . . . . . . 108
5.4. In-hospital mortality following stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
Patient safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5.5. Obstetric trauma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5.6. Procedural or postoperative complications . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Care for mental disorders. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
5.7. Unplanned hospital re-admissions for mental disorders. . . . . . . . . . . . . . . . . 116
Cancer care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.8. Screening, survival and mortality for cervical cancer. . . . . . . . . . . . . . . . . . . .
5.9. Screening, survival and mortality for breast cancer . . . . . . . . . . . . . . . . . . . . .
5.10. Survival and mortality for colorectal cancer . . . . . . . . . . . . . . . . . . . . . . . . . . .
118
118
120
122
Care for communicable diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
5.11. Childhood vaccination programmes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
5.12. Influenza vaccination for older people . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
6. Access to Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
6.1.
6.2.
6.3.
6.4.
6.5.
6.6.
6.7.
6.8.
Unmet health care needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Coverage for health care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Burden of out-of-pocket health expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . .
Geographic distribution of doctors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Inequalities in doctor consultations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Inequalities in dentist consultations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Inequalities in cancer screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Waiting times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
130
132
134
136
138
140
142
144
7. Health Expenditure and Financing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
14
7.1.
Health expenditure per capita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
7.2.
7.3.
7.4.
7.5.
7.6.
Health expenditure in relation to GDP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Health expenditure by function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Pharmaceutical expenditure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Financing of health care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Trade in health services (medical tourism) . . . . . . . . . . . . . . . . . . . . . . . . . . . .
150
152
154
156
158
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TABLE OF CONTENTS
8. Long-term Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
8.1.
8.2.
8.3.
8.4.
Life expectancy and healthy life expectancy at age 65 . . . . . . . . . . . . . . . . . . .
Self-reported health and disability at age 65 . . . . . . . . . . . . . . . . . . . . . . . . . . .
Prevalence and economic burden of dementia . . . . . . . . . . . . . . . . . . . . . . . . .
Recipients of long-term care. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
162
164
166
168
8.5.
8.6.
8.7.
8.8.
Informal carers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Long-term care workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Long-term care beds in institutions and hospitals . . . . . . . . . . . . . . . . . . . . . .
Long-term care expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
170
172
174
176
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Annex A. Additional Information on Demographic and Economic Context,
Health System Characteristics, and Health Expenditure and Financing . . 190
Annex B.
Data Sources for Non-OECD Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
15
INTRODUCTION
Introduction
H
ealth at a Glance 2011 presents comparisons of key indicators of health and health
systems across the 34 OECD countries, as well as for some major non-OECD economies. It
includes, for the first time, a special chapter on long-term care. The indicators presented in
this publication have been selected on the basis of their policy relevance and data
availability and comparability. The data come mainly from official national statistics,
unless otherwise indicated.
Policy and economic context
The recent economic recession has resulted in a marked increase in government
deficits in many countries since 2008. Many countries will need to substantially reduce
their budget deficits. The extent of government spending reductions and/or tax increases
needed will depend on the strength of the economic recovery and the size of the deficit and
cumulative debt.
Given that health spending accounts for a high and growing share of public budgets, it
will be hard to protect it from any overall effort to control public spending following the
recession. The extent to which public spending on health may be affected will depend on
the relative priority allocated to health. It will also depend on the extent to which public
spending on health brings demonstrated benefits in terms of better health outcomes. In a
context of scarce public resources, there will be growing pressures on Health Ministries and
health care providers to demonstrate efficiency (cost-effectiveness) in how resources are
allocated and spent. Chapter 5 presents some of the progress achieved thus far in
measuring quality of care and health outcomes across countries, although further effort is
needed to improve data availability and comparability.
Structure of the publication
The framework underlying this publication looks at the performance of health care
systems in the context of a broader view of public health (Figure 0.1). It is based on one that
was endorsed for the OECD Health Care Quality Indicators project (Kelley and Hurst, 2006;
Arah et al., 2006).
The framework highlights that the goal of health care systems is to improve the health
status of the population. Many factors influence the health status of the population,
including a number that fall outside health care systems, such as the social, economic and
physical environment in which people live, and individual lifestyle and behavioural
factors. The performance of health care systems also contributes to the health status of the
population. This performance includes several dimensions, most notably the degree of
access to care and the quality of care provided.
16
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
INTRODUCTION
Figure 0.1. Conceptual framework for health system performance assessment
Health status
(Chapter 1)
Non-medical determinants of health
(Chapter 2)
Health care system performance
How does the health system perform?
What is the level of quality of care and access to services?
What does this performance cost?
Quality of care
(Chapter 5)
Access to care
(Chapter 6)
Cost/expenditure
(Chapter 7)
Health care resources and activities
Health workforce
(Chapter 3)
Health care activities
(Chapter 4)
Health system design and context
(Annex A)
Source: Adapted from Kelley and Hurst (2006).
Performance measurement also needs to take into account the financial resources
required to achieve these access and quality goals. The performance of health systems
depends on the people providing the services, and the training, technology and equipment
that are at their disposal.
Finally, a number of factors that are related to health care system performance are
presented, such as countries’ demographic, economic and social context, and the design of
their health systems.
Health at a Glance 2011 provides comparisons across OECD countries on each
component of this framework. It is organised as follows.
Chapter 1 on Health Status highlights large variations across countries in life
expectancy, mortality, disease incidence and other measures of population health status.
The length of life and whether it is lived free of illness and disability has intrinsic value,
with good health consistently ranked as one of the most valued aspects in people’s lives.
Good health status also has instrumental value through enhancing opportunities to
participate in education, training, and the labour market.
Chapter 2 on Non-medical Determinants of Health focuses on modifiable lifestyles and
behaviours. Many factors affect population health status, including tobacco smoking,
alcohol drinking, and overweight and obesity problems. Most of these factors can be
modified by supporting health and other policies.
Chapter 3 looks at the Health Workforce, the key actors in any health system. It provides
data on the supply and remuneration of doctors and nurses in OECD countries. Trends are
also presented on the number of new graduates from medical and nursing education
programmes – a key determinant of current and future supply.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
17
INTRODUCTION
Chapter 4 reviews a key set of Health Care Activities. The chapter begins by looking at
consultations with doctors, one of the most common services received by patients. It then
goes on to review cross-country variations in the supply and use of diagnostic technologies
such as magnetic resonance imaging (MRI) and computed tomography (CT) scanners. The
hospital sector continues to absorb the largest share of health spending in OECD countries,
hence a focus on the availability of hospital beds, their rate of use, the number of hospital
discharges and average length of stay. The chapter also looks at variations in the use of
high-volume and high-cost procedures, such as coronary angioplasty, caesarean sections
and cataract surgeries. It concludes with an examination of the volume of pharmaceutical
consumption, particularly the use of drugs that treat diabetes and depression, drugs that
lower cholesterol, and antibiotics.
Chapter 5 examines Quality of Care or the degree to which care is delivered in
accordance with established standards and improves health outcomes. It summarises the
data collection conducted through the OECD Health Care Quality Indicators Project, providing
comparisons on selected indicators of care for chronic conditions, mental disorders,
cancers and communicable diseases. The measures include indicators of process of care
that are recommended for certain population or patient groups to maximise desired
outcomes, and key outcomes measures such as survival rates following heart attack, stroke
and cancer. For the first time, the chapter also includes a set of indicators on patient safety.
Chapter 6 on Access to Care aims to gauge whether OECD countries are meeting their
stated health policy goal of ensuring adequate access to essential health care services on
the basis of individual need. It begins with a review of self-reported unmet needs for
medical and dental care, as a broad measure of perceived access problems. This subjective
measure is complemented by more objective indicators of financial access such as the
degree of public or private health insurance coverage and the burden of out-of-pocket
payments. Geographic access to care follows, here measured by the “density” of doctors in
different regions within each country. Another approach is to measure inequalities among
different socio-economic groups in their use of health services, taking into account
differences in need. Three indicators look at the use of doctors and dentists and at
screening for cancer by income groups. The final indicator relates to timely access to care
and considers variations in waiting times to see a doctor (whether a GP or a specialist), and
to obtain an elective surgery.
Chapter 7 on Health Expenditure and Financing compares how much OECD countries
spend on health, both on a per capita basis and in relation to GDP. As well as indicators of
total spending, the chapter provides an analysis of the different types of health services and
goods consumed across OECD countries, including a separate focus on pharmaceuticals.
Along with the allocation of health care spending, the chapter also looks at how these health
services and goods are paid for in different countries (i.e. the mix between public funding,
private health insurance where it exists, and out-of-pocket payments by patients). Lastly,
with the growth in medical tourism and international trade in health services, current levels
and trends are examined, in the light of efforts to improve data availability.
Chapter 8 is a special chapter on Long-term Care, building on a recent OECD project
which focussed particularly on the long-term care workforce and the financing of services
(Colombo et al., 2011). Indicators on life expectancy and life expectancy in good health
at 65, self-reported health and disability status and dementia prevalence provide a context
for the proportion of the older population who may be in need of care. These are
complemented by an indicator on older persons receiving long-term care services at home
or in institutions. Care provision, both informal and formal, is discussed through two
18
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
INTRODUCTION
indicators on family carers and paid long-term care workers. The final indicator of this
chapter looks at long-term care expenditure as a share of GDP and the growth rate over the
past decade.
Annex A provides additional information on the demographic and economic context
within which health and long-term care systems operate, as well as some key characteristics
of health system financing and delivery.
Presentation of indicators
Text and figures
Each of the topics covered in the different chapters of this publication is presented
over two pages. The first provides a brief commentary highlighting the key findings
conveyed by the data, defines the indicator and discloses any significant national variation
from the definition which might affect data comparability. On the facing page is a set of
figures. These typically show current levels of the indicator and, where possible, trends
over time. In some cases, an additional figure relating the indicator to another is included.
Where an OECD average is included in a figure, it is the unweighted average of the OECD
countries presented, unless otherwise specified.
Data limitations
Limitations in data comparability are indicated both in the text (in the box related to
“Definition and comparability”) as well as in footnotes to figures. Readers should exercise
particular caution when considering time trends for Germany. Data for Germany up to 1990
generally refer to the former West Germany and data for subsequent years refer to unified
Germany.
Readers interested in using the data presented in this publication for further analysis
and research are encouraged to consult the full documentation of definitions, sources and
methods presented in the OECD Health Database on OECD.Stat (http://stats.oecd.org/index.aspx,
then choose “Health”). More information on the OECD Health Database is available at
www.oecd.org/health/healthdata.
Population figures
The population figures presented in the annex and used to calculate rates per capita
throughout this publication come from the OECD Historical Population Data and
Projections (as of June 2011), and refer to mid-year estimates. Population estimates are
subject to revision, so they may differ from the latest population figures released by the
national statistical offices of OECD member countries.
Note that some countries such as France, the United Kingdom and the United States
have overseas colonies, protectorates or territories. These populations are generally
excluded. The calculation of GDP per capita and other economic measures may, however,
be based on a different population in these countries, depending on the data coverage.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
19
INTRODUCTION
OECD country ISO codes
Australia
AUS
Japan
JPN
Austria
AUT
Korea
KOR
Belgium
BEL
Luxembourg
LUX
Canada
CAN
Mexico
MEX
Chile
CHL
Netherlands
NLD
Czech Republic
CZE
New Zealand
NZL
Denmark
DNK
Norway
NOR
Estonia
EST
Poland
POL
Finland
FIN
Portugal
PRT
France
FRA
Slovak Republic
SVK
Germany
DEU
Slovenia
SVN
Greece
GRC
Spain
ESP
Hungary
HUN
Sweden
SWE
Iceland
ISL
Switzerland
CHE
Ireland
IRL
Turkey
TUR
Israel
ISR
United Kingdom
GBR
Italy
ITA
United States
USA
Other major economy ISO codes
20
Brazil
BRA
Indonesia
IDN
China
CHN
Russian Federation
RUS
India
IND
South Africa
ZAF
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
LIST OF ACRONYMS
List of Acronyms
AIDS
ALOS
AMI
ATC
BMI
CAD
COPD
CT
DDD
ESRF
EU-SILC
GDP
GP
HCQI
HIV
ICHA
IHD
Acquired immunodeficiency syndrome
Average length of stay
Acute myocardial infarction
Anatomic-therapeutic classification
Body mass index
Coronary artery disease
Chronic obstructive pulmonary disease
Computed tomography
Defined daily dose
End-stage renal failure
European Union Statistics on Income and Living Conditions survey
Gross domestic product
General practitioner
Health Care Quality Indicators (OECD Project)
Human immunodeficiency virus
International Classification for Health Accounts
Ischemic heart disease
MRI
PPP
PSI
PYLL
SHA
Magnetic resonance imaging
Purchasing power parities
Patient safety indicators
Potential years of life lost
System of Health Accounts
SIDS
Sudden infant death syndrome
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
21
1. HEALTH STATUS
1.1. Life expectancy at birth
1.2. Premature mortality
1.3. Mortality from heart disease and stroke
1.4. Mortality from cancer
1.5. Mortality from transport accidents
1.6. Suicide
1.7. Infant mortality
1.8. Infant health: Low birth weight
1.9. Perceived health status
1.10. Diabetes prevalence and incidence
1.11. Cancer incidence
1.12. AIDS incidence and HIV prevalence
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
23
1. HEALTH STATUS
1.1. Life expectancy at birth
Life expectancy at birth continues to increase remarkably in
OECD countries, reflecting sharp reductions in mortality
rates at all ages. These gains in longevity can be attributed to
a number of factors including rising living standards,
improved lifestyle and better education, and greater access
to quality health services. Other factors such as better nutrition, sanitation and housing also play a role, particularly in
countries with emerging economies (OECD, 2004a).
with similar income per capita. For example, Japan and
Israel have higher, and the United States, Denmark and
Hungary have lower life expectancies than would be predicted by their GDP per capita alone. High rates of mortality
for some diseases at older ages, the legacy of smoking and
other factors such as obesity and economic inequality have
been suggested as possible reasons for the United States’
poorer outcomes (Crimmins et al., 2010).
On average across OECD countries, life expectancy at birth for
the whole population reached 79.5 years in 2009, a gain of
more than 11 years since 1960 (Figure 1.1.1). Japan leads a
large group (including almost two-thirds of the 34 OECD
countries) in which life expectancy at birth is currently
80 years or more. A second group, including Portugal,
the United States and a number of central and eastern
European countries have a life expectancy of between 75 and
80 years. Life expectancy among OECD countries was lowest
in Turkey and Hungary. However, while life expectancy in
Hungary has increased only modestly since 1960, it has
increased rapidly in Turkey, so that it is quickly approaching
the OECD average (OECD and World Bank, 2008).
Figure 1.1.3 shows the relationship between life expectancy
at birth and health expenditure per capita across OECD
countries. Higher health spending per capita is generally
associated with higher life expectancy at birth, although
this relationship tends to be less pronounced in countries
with the highest health spending per capita. Japan and
Spain stand out as having relatively high life expectancies,
and the United States, Denmark and Hungary relatively low
life expectancies, given their levels of health spending.
Nearly all OECD and emerging countries have experienced
large gains in life expectancy over the past 50 years. Life
expectancy at birth in Korea, Turkey and Chile has
increased by 20 years or more over the period 1960-2009.
Mexico, Portugal and Japan, as well as emerging countries
such as Indonesia, China, India and Brazil also show strong
gains. South Africa and the Russian Federation are still
characterised by high mortality rates and in terms of length
of life, they are well below the OECD average.
The gender gap in life expectancy stood at 5.5 years on
average across OECD countries in 2009, with life expectancy reaching 76.7 years among men and 82.2 years
among women. While the gender gap in life expectancy
increased substantially in many countries during the 1960s
and the 1970s, it narrowed during the past 30 years, reflecting higher gains in life expectancy among men than among
women. This can be attributed at least partly to the
narrowing of differences in risk-increasing behaviours,
such as smoking, between men and women, accompanied
by sharp reductions in mortality rates from cardiovascular
diseases among men.
Higher national income (as measured by GDP per capita) is
generally associated with higher life expectancy at birth,
although the relationship is less pronounced at the highest
levels of national income (Figure 1.1.2). There are also
notable differences in life expectancy between countries
24
Variations in GDP per capita may influence both life expectancy and health expenditure per capita. Other factors
beyond national income and total health spending are
required to explain variations in life expectancy across
countries.
Definition and comparability
Life expectancy at birth measures how long on
average a newborn can expect to live, if current death
rates do not change. However, the actual age-specific
death rate of any particular birth cohort cannot be
known in advance. If rates are falling, as has been the
case over the past decades in OECD countries, actual
life spans will be higher than life expectancy
calculated using current death rates.
The methodology used to calculate life expectancy
can vary slightly between countries. This can change
a country’s estimates by a fraction of a year.
Life expectancy at birth for the total population is
calculated by the OECD Secretariat for all OECD
countries, using the unweighted average of life expectancy of men and women.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.1. Life expectancy at birth
1.1.1 Life expectancy at birth, 2009 (or nearest year), and years gained since 1960
Life expectancy at birth, 2009
Years gained, 1960-2009
Japan
Switzerland
Italy
Spain
Australia
Israel
Iceland
Sweden
France
Norway
New Zealand
Canada
Luxembourg
Netherlands
Austria
United Kingdom
Germany
Greece
Korea
Belgium
Finland
Ireland
Portugal
OECD
Denmark
Slovenia
Chile
United States
Czech Republic
Poland
Mexico
Estonia
Slovak Republic
Hungary
Turkey
China
Brazil
Indonesia
Russian Federation
India
South Africa
83.0
82.3
81.8
81.8
81.6
81.6
81.5
81.4
81.0
81.0
80.8
80.7
80.7
80.6
80.4
80.4
80.3
80.3
80.3
80.0
80.0
80.0
79.5
79.5
79.0
79.0
78.4
78.2
77.3
75.8
75.3
75.0
75.0
74.0
73.8
73.3
72.6
71.2
68.7
64.1
51.7
90
Years
80
70
60
50
15.2
10.9
12.0
12.0
10.7
9.9
8.6
8.3
10.7
7.2
9.7
9.4
11.3
7.1
11.7
9.6
11.2
10.4
27.9
10.2
11.0
10.0
15.6
11.2
6.6
10.5
21.4
8.3
6.7
8.0
17.8
6.5
4.4
6.0
25.5
26.7
18.1
30.0
0.0
21.7
2.6
40
0
5
10
15
20
25
30
Years
Source: OECD Health Data 2011; World Bank and national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523253
1.1.2 Life expectancy at birth and GDP per capita,
2009 (or nearest year)
Life expectancy in years
84
FRA
ISR
NZL
80
CHL
KOR
PRT
SVN
CZE
POL
76
BRA
72
TUR
GRC
FIN
Life expectancy in years
84
CHE
CAN
NLD
IRL
USA
DNK AUT
GBR
NOR
ISR
LUX
76
MEX
CHN
SVK
HUN
72
IDN
POL
EST
TUR HUN
BRA
AUS ISL
JPN
SWE
ESP
CHE
CAN LUX
ITA
FRA
NOR
NZL
FIN
AUT NLD
PRT
GBR
DEU
GRC
SVN IRL BEL DNK
CZE
SVK
RUS
68
R² = 0.54
IND
64
0
10 000
USA
IDN
RUS
68
KOR
80
CHL
BEL
EST
MEX
CHN
JPN DEU
ISL
SWE
ESP ITA
AUS
1.1.3 Life expectancy at birth and health spending
per capita, 2009 (or nearest year)
R² = 0.69
IND
64
20 000
30 000
40 000
50 000
60 000 70 000
GDP per capita (USD PPP)
Source: OECD Health Data 2011; World Bank and national sources for
non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523272
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
0
2 000
4 000
6 000
8 000
Health spending per capita (USD PPP)
Source: OECD Health Data 2011; World Bank and national sources for
non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523291
25
1. HEALTH STATUS
1.2. Premature mortality
Premature mortality, measured in terms of potential years
of life lost (PYLL) before the age of 70 years, focuses on
deaths among younger age groups of the population. PYLL
values are heavily influenced by infant mortality and
deaths from diseases and injuries affecting children and
younger adults: a death at five years of age represents
65 PYLL; one at 60 years of age only ten. Premature mortality can be influenced by advances in medical technology,
especially in relation to infant mortality and deaths due to
heart disease, and in prevention and control measures,
reducing untimely or avoidable deaths from injuries and
communicable diseases. A number of other variables, such
as GDP per capita, occupational status, numbers of doctors
and alcohol and tobacco consumption have also been
associated with reduced premature mortality (Or, 2000;
Joumard et al., 2008).
Rates of premature mortality are higher among males in all
countries, with the OECD average in 2009 (4 689 years lost
per 100 000 males) almost twice that of females (2 419). The
main causes of potential years of life lost before age 70
among men are external causes including accidents and
violence (29%), followed by cancer (20%) and circulatory
diseases (17%). For women, the principal causes are cancer
(31%), external causes (17%), and circulatory diseases (12%).
Among males, Iceland and Sweden had the lowest levels of
premature mortality in 2009, and for females levels were
lowest in Iceland and Luxembourg (Figure 1.2.1). In the
OECD, Estonia and Mexico reported the highest premature
mortality rates for males, and Mexico and Hungary for
females, with levels more than double those of the country
with the lowest PYLL. The rates for the United States were
also high – almost 50% above the OECD average in the case
of females, and 30% for males. Among US males, more than
one-third (and in females, one-fifth) of these premature
mortality rates can be attributed to deaths resulting from
external causes, including accidents, suicide and homicide.
Premature death from homicide for men in the United
States is more than five times the OECD average. Rates of
premature mortality are also extremely high in the Russian
Federation, at over four times the OECD average for males,
and three times for females.
Across OECD countries, premature mortality has been cut
by more than half since 1970 (Figure 1.2.2). The decline in
premature mortality was more rapid for females than for
26
males between 1970 and the early 1990s, but since then the
average rate of PYLL has been declining at the same rate for
both men and women. The downward trend in infant
mortality was a major factor contributing to the decline
in earlier years (see Indicator 1.7 “Infant mortality”). More
recently, the decline in deaths from heart disease among
adults has contributed significantly to the overall reduction
in premature mortality in many countries (see Indicator 1.3
“Mortality from heart disease and stroke”).
Portugal, Luxembourg and Italy have seen premature
mortality rates decline rapidly among both males and
females, so that they are currently less than one-third
of 1970 levels. Although the rate is still high, Mexico has also
seen a dramatic decline. In each case, the sharp reduction in
infant mortality rates has been an important contributing
factor. In contrast, premature mortality has declined more
slowly in Hungary, particularly among males. This is largely
attributed to persistently high levels of mortality from circulatory disease (currently twice the OECD average) and from
liver disease (over three times the OECD average). The slow
decline in PYLL in part reflects unhealthy lifestyles, in
particular high alcohol and tobacco consumption among
males in Hungary, together with Hungary’s high suicide
rates. Declines in premature mortality have also been slow
in Poland and the United States.
Definition and comparability
Potential years of life lost (PYLL) is a summary
measure of premature mortality, providing an explicit
method of weighting deaths which occur at younger
ages. The calculation of PYLL involves adding agespecific deaths occurring at each age and weighting
them by the number of remaining unlived years up
to a selected age limit, defined here as age 70. For
example, a death occurring at five years of age is
counted as 65 years of PYLL. The indicator is
expressed per 100 000 females and males.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.2. Premature mortality
1.2.1 Potential years of life lost (PYLL), females and males, 2009 (or nearest year)
Females
Males
Iceland
Luxembourg
Japan
Spain
Italy
Sweden
Greece
Israel
Slovenia
Switzerland
Norway
Australia
Germany
Austria
Korea
France
Finland
Netherlands
Portugal
Ireland
Czech Republic
OECD
United Kingdom
Denmark
Belgium
Canada
New Zealand
Estonia
Chile
Slovak Republic
Poland
United States
Hungary
Mexico
Russian Federation
1 492
1 704
1 763
1 872
1 882
1 916
1 935
1 949
1 998
2 024
2 063
2 077
2 123
2 148
2 171
2 202
2 208
2 235
2 246
2 302
2 412
2 419
2 479
2 493
2 500
2 554
2 775
2 990
3 004
3 049
3 127
3 555
3 629
4 946
7 056
10 000
8 000
6 000
PYLL per 100 000 females
4 000
2 000
2 995
3 613
3 287
3 857
3 518
3 081
4 367
3 601
4 508
3 295
3 518
3 561
3 824
4 068
4 171
4 459
4 696
3 114
4 708
4 239
5 046
4 689
3 988
4 311
4 585
4 168
4 365
8 872
5 622
7 025
7 801
6 133
7 863
8 481
20 161
0
0
2 000
4 000
6 000
8 000
10 000
PYLL per 100 000 males
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523310
1.2.2 Reduction in potential years of life lost (PYLL), 1970-2009 (or nearest year)
1970
2009
20 257
PYLL per 100 000 population
25 000
6 670
5 763
10 406
5 657
10 280
5 419
49 98
9 243
4 847
4 306
3 726
8 344
3 546
3 559
8 727
8 350
3 544
3 457
3 410
3 463
8 289
7 744
6 692
3 365
3 316
3 282
7 631
7 782
3 272
7 454
3 177
3 162
3 233
9 420
7 704
3 104
8 932
2 974
2 866
2 823
2 804
2 767
2 699
6 108
7 480
8 616
8 810
6 294
2 669
2 661
2 678
7 239
6 911
2 528
6 707
5 777
2 507
5 000
2 262
10 000
9 923
15 000
13 277
14 505
20 000
Ic
el
a
S w nd
ed
en
Sw Jap
it an
L u z er l
xe a n
m d
Ne bo
t h ur g
er
la
nd
s
It a
ly
Is
ra
No el
rw
Au ay
st
ra
li a
Sp
G e a in
rm
an
Au y
st
r
Gr i a
ee
Un
c
i te K e
or
d
Ki ea
ng
do
Ir e m
la
Sl nd
ov
en
i
Fr a
an
c
Ca e
n
De ada
nm
Po ar k
r tu
g
F i al
nl
an
d
OE
C
D
B
Ne elg
i
C z w Z um
ec ea
h lan
Re d
pu
bl
ic
Un
Ch
i
t
Sl e d il e
ov
ak S t a
Re te s
pu
bl
Po ic
la
Hu nd
ng
a
Es r y
Ru
to
ss
ni
a
ia
n M ex
Fe
i
de co
ra
tio
n
0
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523329
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
27
1. HEALTH STATUS
1.3. Mortality from heart disease and stroke
Cardiovascular diseases are the main cause of mortality in
almost all OECD countries, and accounted for 35% of all
deaths in 2009. They cover a range of diseases related to the
circulatory system, including ischemic heart disease
(known as IHD, or heart attack) and cerebrovascular disease
(or stroke). Together, IHD and stroke comprise two-thirds of
all cardiovascular deaths, and between them they caused
almost one-quarter of all deaths in OECD countries in 2009.
Ischemic heart disease is caused by the accumulation of
fatty deposits lining the inner wall of a coronary artery,
restricting blood flow to the heart. IHD alone was responsible for 15% of all deaths in OECD countries in 2009. Mortality from IHD varies considerably, however (Figure 1.3.1).
Central and eastern European countries report the highest
IHD mortality rates; the Slovak Republic for both males and
females, followed by Estonia, Hungary and the Czech
Republic. IHD mortality rates are also relatively high in
Finland, Poland and Ireland, far ahead of Korea and Japan,
the countries with the lowest rates. There are regional
patterns to the variability of IHD mortality rates. Closely
following the two OECD Asian countries, the countries with
the lowest IHD mortality rates are five countries located in
southern Europe and the Mediterranean: France, Portugal,
Spain, Israel and Italy. This lends support to the commonly
held hypothesis that diet – an important underlying risk
factor – explains much of the difference in IHD mortality
across countries.
Death rates for IHD are much higher for men than for
women (Figure 1.3.1). On average across OECD countries,
IHD mortality rates in 2009 were nearly two times greater for
men. The disparity was greatest in France and Luxembourg
with male rates two-to-three times higher, and least in
Mexico and the Czech and Slovak Republics, at 60% higher.
Since 1980, IHD mortality rates have declined in nearly all
OECD countries. The decline has been most remarkable in
the Netherlands, the Nordic countries (Denmark, Norway,
Sweden and Iceland), Australia, the United Kingdom and
Israel, with rates being cut by two-thirds or more. Declining
tobacco consumption contributed significantly to reducing
the incidence of IHD, and consequently to reducing mortality rates. Improvements in medical care have also contributed to reduced mortality rates (see Indicators 4.6 “Cardiac
procedures” and 5.3 “In-hospital mortality following acute
myocardial infarction”). A small number of countries however, including Hungary, Poland and the Slovak Republic,
28
have seen little or no decline since 1980. The rate in Greece
has declined only slightly, although it was already comparatively low in 1980. Only in Korea and Mexico have
mortality rates increased.
Stroke was the underlying cause for about 8% of all deaths
in OECD countries in 2009. It is a loss of brain function due
to disruption of the blood supply to the brain. In addition to
being an important cause of mortality, the disability burden
from stroke is also substantial (Moon et al., 2003). As with
IHD, there are large variations in stroke mortality rates
across countries (Figure 1.3.2). The rates are highest in the
Slovak Republic, Hungary, Poland and the Czech Republic.
They are the lowest in Israel, Switzerland, France and the
United States.
Looking at trends over time, stroke mortality has decreased in
all OECD countries (except Poland and the Slovak Republic)
since 1980. Rates have declined by around three-quarters in
Austria, Portugal and Japan. As with IHD, the reduction in
stroke mortality can be attributed at least partly to a reduction in risk factors. Tobacco smoking and hypertension are
the main modifiable risk factors for stroke. Improvements in
medical treatment for stroke have also increased survival
rates (see Indicator 5.4 “In-hospital mortality following
stroke”).
Definition and comparability
Mortality rates are based on numbers of deaths
registered in a country in a year divided by the size of
the corresponding population. The rates have been
directly age-standardised to the 1980 OECD population to remove variations arising from differences in
age structures across countries and over time. The
source is the WHO Mortality Database.
Deaths from ischemic heart disease are classified to
ICD-10 codes I20-I25, and stroke to I60-I69. Mathers
et al. (2005) have provided a general assessment of the
coverage, completeness and reliability of data on
causes of death.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.3. Mortality from heart disease and stroke
1.3.1 Ischemic heart disease, mortality rates,
2009 (or nearest year)
Females
Korea
Japan
France
Portugal
Netherlands
Spain
Israel
Chile
Italy
Luxembourg
Norway
Switzerland
Slovenia
Greece
Denmark
Belgium
Australia
Mexico
Germany
Iceland
United Kingdom
OECD
Sweden
Canada
Austria
United States
New Zealand
Ireland
Poland
Finland
Czech Republic
Hungary
Estonia
Slovak Republic
Russian Federation
21
37
17
38
Males
Females
50
19
54
29
62
27
66
28
43
78
39
81
41
81
35
86
42
87
42
88
40
89
38
90
49
93
42
94
99
52
103
65
56
110
50
110
50
110
60
117
58
118
61
123
67
124
68
129
70
131
65
137
66
139
170
74
207
126
275
156
282
141
324
208
524
269
0
1.3.2 Stroke, mortality rates,
2009 (or nearest year)
50
Israel
Switzerland
France
United States
Canada
Netherlands
Australia
Austria
Germany
Iceland
Spain
Ireland
Norway
United Kingdom
New Zealand
Sweden
Belgium
Mexico
Luxembourg
Finland
Italy
Japan
OECD
Denmark
Chile
Greece
Korea
Slovenia
Estonia
Portugal
Czech Republic
Poland
Hungary
Slovak Republic
Russian Federation
100
150
200
250
300 350
Age-standardised rates per 100 000 population
23
28
25
29
22
31
29
32
29
34
32
35
34
36
28
36
32
39
30
41
32
41
36
41
31
42
39
42
43
42
36
45
38
45
41
47
37
48
38
50
40
50
30
53
42
54
45
56
Males
66
47
70
69
73
46
76
54
80
52
81
62
84
68
88
62
111
71
112
77
313
230
0
50
100
150
200
250
300
Age-standardised rates per 100 000 population
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523348
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523367
1.3.3 Trends in ischemic heart disease mortality rates,
selected OECD countries, 1980-2009
1.3.4 Trends in stroke mortality rates,
selected OECD countries, 1980-2009
Hungary
Korea
Poland
Portugal
Netherlands
OECD
United Kingdom
OECD
Age-standardised rates per 100 000 population
300
Age-standardised rates per 100 000 population
300
250
250
200
200
150
150
100
100
50
50
0
1980
1985
1990
1995
2000
2005
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523386
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
0
1980
1985
1990
1995
2000
2005
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523405
29
1. HEALTH STATUS
1.4. Mortality from cancer
Cancer is the second leading cause of mortality in OECD
countries after diseases of the circulatory system, accounting for 28% of all deaths on average in 2009. In 2009, cancer
mortality rates were the lowest in Mexico, Finland, Japan
and Switzerland. They were the highest in central and
eastern European countries (Hungary, Poland, Slovenia, the
Czech and Slovak Republics) and Denmark (Figure 1.4.1).
Cancer mortality rates are higher for men than for women
in all countries (Figure 1.4.1). In 2009, the gender gap was
particularly wide in Korea, Spain and Estonia, along with
the Russian Federation, Japan and France, with mortality
rates among men more than twice those for women. This
gap can be explained partly by the greater prevalence of
risk factors among men, as well as the lesser availability or
use of screening programmes for cancers affecting men,
leading to lower survival rates after diagnosis.
Three common cancers – lung, breast and prostate – are
discussed in detail below. Mortality from cervical and
colorectal cancer is considered further in Chapter 5.
Lung cancer is responsible for the largest number of cancer
deaths among men in OECD countries, except in Sweden,
Mexico and Chile. Lung cancer is also one of the main causes
of cancer mortality among women. Tobacco smoking is the
most important risk factor for lung cancer. In 2009, death
rates from lung cancer among men were the highest in
central and eastern European countries (Hungary, Poland
and the Czech and Slovak Republics), Belgium, the
Russian Federation, Estonia, Greece and the Netherlands
(Figure 1.4.2). These are all countries where smoking rates
among men are relatively high. Death rates from lung cancer
among men are low in Chile, Mexico and Sweden, which,
in the latter two countries, reflect smoking rates (see
Indicator 2.1 “Tobacco consumption among adults”).
Breast cancer is the most common form of cancer among
women in all OECD countries (Ferlay et al., 2010). It
accounted for around 30% of cancer incidence among
women, and 15% of cancer deaths in 2009. While there has
been an increase in measured incidence rates of breast
cancer over the past decade, death rates have declined or
remained stable, indicating increases in survival rates due
to earlier diagnosis and better treatment (see Indicator 5.9
“Screening, survival and mortality for breast cancer”). The
lowest mortality rates from breast cancer are in Korea and
Japan, while the highest rates are in Denmark, Belgium,
Ireland and Hungary (Figure 1.4.3).
30
Prostate cancer has become the most commonly occurring
cancer among men in many OECD countries, particularly
for those aged over 65 years of age, although death rates
from prostate cancer generally remain lower than for lung
cancer. The rise in the reported incidence of prostate
cancer in many countries during the 1990s and 2000s was
largely due to the greater use of prostate-specific antigen
(PSA) diagnostic tests. Death rates from prostate cancer
in 2009 varied from lows of less than 10 per 100 000 males
in Korea and Japan, to highs of more than 30 per
100 000 males in Estonia, Slovenia and Nordic countries
(Denmark, Sweden and Norway) (Figure 1.4.4). The causes
of prostate cancer are not well-understood. Some evidence
suggests that environmental and dietary factors might
influence the risk of prostate cancer (Institute of Cancer
Research, 2009).
Death rates from all types of cancer for males and females
have declined at least slightly in most OECD countries
since 1995, although the decline has been more modest
than for cardiovascular diseases. The exceptions to this
declining pattern are Greece, Poland, Portugal and Estonia,
where cancer mortality has remained static.
Definition and comparability
Mortality rates are based on numbers of deaths
registered in a country in a year divided by the size of
the corresponding population. The rates have been
directly age-standardised to the 1980 OECD population to remove variations arising from differences in
age structures across countries and over time. The
source is the WHO Mortality Database.
Deaths from all cancers are classified to ICD-10
codes C00-C97, lung cancer to C32-C34, breast cancer
to C50 and prostate cancer to C61. Mathers et al. (2005)
have provided a general assessment of the coverage,
completeness and reliability of data on causes of
death.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.4. Mortality from cancer
1.4.1 All cancers mortality rates, males and females,
2009 (or nearest year)
Females
Mexico
Israel
Sweden
Finland
Iceland
Switzerland
Chile
Australia
United States
Norway
Luxembourg
Japan
Germany
Austria
Greece
United Kingdom
New Zealand
Portugal
Canada
OECD
Spain
Italy
Ireland
Korea
France
Belgium
Netherlands
Denmark
Russian Federation
Czech Republic
Slovak Republic
Slovenia
Poland
Estonia
Hungary
85
125
125
129
111
124
115
130
126
117
93
121
118
102
141
143
104
143
124
96
117
143
91
111
122
144
173
123
140
135
138
142
128
165
0
50
Males
Females
101
105
1.4.2 Lung cancer mortality rates, males and females,
2009 (or nearest year)
162
165
165
177
180
180
184
185
185
189
189
193
194
199
199
199
204
205
208
211
212
218
221
221
226
226
237
251
254
263
266
272
275
316
Mexico
Chile
Sweden
Israel
Iceland
New Zealand
Portugal
Australia
Finland
Norway
Luxembourg
Switzerland
Japan
Austria
United Kingdom
Germany
Ireland
OECD
France
United States
Korea
Italy
Slovenia
Canada
Spain
Denmark
Slovak Republic
Czech Republic
Netherlands
Greece
Estonia
Russian Federation
Belgium
Poland
Hungary
100
150
200
250
300 350
Age-standardised rates per 100 000 population
6
12
26
29
22
13
36
37
39
39
40
41
42
42
42
44
45
48
50
50
52
36
26
8
20
13
24
13
17
12
17
30
18
27
20
14
57
57
58
58
59
60
60
62
62
64
65
65
68
70
36
14
13
17
36
9
42
13
18
30
11
11
8
17
20
34
0
Males
15
75
87
98
25
50
75
100
Age-standardised rates per 100 000 population
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523424
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523443
1.4.3 Breast cancer mortality rates, females,
2009 (or nearest year)
1.4.4 Prostate cancer mortality rates, males,
2009 (or nearest year)
Korea
Japan
Mexico
Chile
Spain
Norway
Finland
Portugal
Australia
Czech Republic
Poland
Sweden
Greece
Iceland
Slovak Republic
United States
Estonia
OECD
Switzerland
Austria
Italy
Russian Federation
Luxembourg
Germany
France
Canada
United Kingdom
Slovenia
New Zealand
Netherlands
Israel
Hungary
Ireland
Belgium
Denmark
6.1
10.8
11.4
13.4
16.4
17.4
17.7
18.1
18.5
18.6
19.1
19.1
19.3
19.7
19.7
19.8
19.9
20.1
20.3
21.0
21.4
21.4
21.6
22.1
22.3
22.4
23.2
23.6
24.1
24.7
25.0
25.6
26.1
26.7
28.6
0
10
20
30
40
Age-standardised rates per 100 000 population
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523462
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
Korea
Japan
Israel
Italy
Russian Federation
Greece
Spain
United States
Mexico
Luxembourg
Germany
France
Austria
Canada
Hungary
Poland
Belgium
Finland
Slovak Republic
OECD
Portugal
Czech Republic
United Kingdom
Switzerland
Australia
New Zealand
Netherlands
Ireland
Iceland
Chile
Norway
Slovenia
Sweden
Denmark
Estonia
8.1
8.4
12.3
15.6
15.9
16.3
16.6
17.5
17.9
18.6
19.6
20.0
20.1
21.2
21.3
21.8
22.3
22.3
22.3
22.4
22.6
22.7
23.3
24.0
24.3
25.0
25.3
25.9
28.1
29.1
31.9
32.7
32.7
34.1
36.6
0
10
20
30
40
Age-standardised rates per 100 000 population
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523481
31
1. HEALTH STATUS
1.5. Mortality from transport accidents
Worldwide, an estimated 1.2 million people are killed in
transport accidents each year, most of which are road
traffic accidents, and as many as 50 million people are
injured or disabled (WHO, 2009a). In OECD countries alone
transport accidents were responsible for more than
120 000 deaths in 2009, occurring most often in the United
S t a t e s ( 4 5 0 0 0 ) , M ex i c o ( 1 7 0 0 0 ) , Ko re a a n d Jap a n
(7 000 each). In addition, there were 38 000 deaths in the
Russian Federation.
Mortality from road accidents is the leading cause of death
among children and young people – especially young men –
in many countries. Most fatal traffic injuries occur in
passenger vehicles, although the fatality risk for motor
cycles and mopeds is highest among all modes of transport
(OECD/ITF, 2011).
Besides the adverse social, physical and psychological
effects, the direct and indirect financial costs of transport
accidents are substantial; one estimate put these at 2% of
gross national product annually in highly-motorised
countries (Peden et al., 2004).
Death rates were the highest in the Russian Federation
in 2009, and among OECD countries, in Mexico and the United
States, all in excess of 14 deaths per 100 000 population
(Figure 1.5.1). They were the lowest in Iceland, the
Netherlands and the United Kingdom, at four deaths per
100 000 population or less, much lower than the OECD
average of 8.2. A five-fold difference exists between Iceland
and Mexico, the OECD countries with the lowest and highest
rates. In all countries, death rates from transport accidents
are much higher for males than for females, with disparities
ranging from twice as high in New Zealand to almost five
times higher in Greece and Chile. On average, three times
as many males than females die in transport accidents
(Figure 1.5.1).
Much transport injury and mortality is preventable. Road
security has increased greatly over the past decades in many
countries through improvements of road systems, education
and prevention campaigns, the adoption of new laws and
regulations and the enforcement of these laws through more
traffic controls. As a result, death rates due to transport
32
accidents have been halved in OECD countries since 1995
(Figure 1.5.2). Estonia, Iceland, Korea, Portugal and Japan
have seen the largest declines, with a reduction of 60% or
more since 1995, although the number of vehicle kilometres
travelled has increased in the same period (OECD/ITF, 2010).
Death rates have also declined in the United States, but at a
slower pace, and therefore remain above the OECD average.
In Chile and the Russian Federation, there have been significant increases in death rates from road accidents since 1995
(Figure 1.5.3).
The effects of the recent economic crisis may have had a
favourable outcome on transport accident mortality. Many
countries had a slight decrease or stagnation in traffic
volumes, but a much more significant reduction in fatalities.
However, in the long-term, effective road safety policies are
the main contributor to reduced mortality (OECD/ITF, 2011).
Definition and comparability
Mortality rates are based on numbers of deaths registered in a country in a year divided by the size of the
corresponding population. The rates have been
directly age-standardised to the 1980 OECD population
to remove variations arising from differences in age
structures across countries and over time. The source
is the WHO Mortality Database.
Deaths from transport accidents are classified to
ICD-10 codes V01-V89. Mortality rates from road
traffic accidents in Luxembourg are biased upward
because of the large volume of traffic in transit,
resulting in a significant proportion of non-residents
killed. Mathers et al. (2005) have provided a general
assessment of the coverage, completeness and
reliability of data on causes of death.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.5. Mortality from transport accidents
1.5.1 Transport accident mortality rates, 2009 (or nearest year)
Total population
Males and females
Females
Iceland
Netherlands
United Kingdom
Japan
Sweden
Norway
Germany
Ireland
Switzerland
Finland
Denmark
Israel
Spain
Austria
France
Australia
Luxembourg
Estonia
OECD
Czech Republic
Slovak Republic
Canada
Portugal
Slovenia
Italy
Hungary
Belgium
New Zealand
Chile
Korea
Greece
Poland
United States
Mexico
Russian Federation
3.2
4.0
4.0
4.1
4.1
4.8
5.0
5.1
5.1
5.2
5.9
5.9
6.7
6.8
6.8
7.1
7.7
7.9
8.2
8.4
8.6
8.8
8.9
8.9
9.3
9.5
10.6
11.1
13.2
13.7
13.8
14.0
14.6
17.0
24.7
25
20
15
10
Age-standardised rates per 100 000 population
5
0
Males
0.5 5.7
2.1
6.1
1.7
6.2
6.2
2.2
6.3
2.0
7.6
2.0
7.7
2.3
7.8
2.5
8.4
1.9
8.3
2.4
8.7
3.2
9.5
2.6
10.7
2.7
11.0
2.8
10.8
2.9
10.9
3.4
12.2
3.2
12.7
3.9
12.9
3.7
12.7
4.1
13.9
3.5
12.8
4.9
14.6
3.6
14.4
3.6
15.3
3.4
15.4
4.2
16.3
5.0
15.4
7.0
22.3
4.8
21.6
6.8
22.6
4.8
22.3
6.3
21.1
8.3
27.8
7.0
12.3
0
10
39.7
20
30
40
Age-standardised rates per 100 000 population
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523500
1.5.2 Trends in transport accident mortality rates,
selected OECD countries, 1995-2009
France
Mexico
United States
OECD
Estonia
Iceland
Korea
Portugal
Japan
Germany
Ireland
Slovenia
Luxembourg
Austria
Spain
France
Netherlands
Switzerland
Slovak Republic
Denmark
Israel
Hungary
OECD
Finland
Greece
United Kingdom
Australia
Belgium
Norway
New Zealand
Poland
Italy
Sweden
Canada
United States
Mexico
Czech Republic
Chile
Russian Federation
Age-standardised rates per 100 000 population
25
20
15
10
5
0
1995
1997
1999
2001
2003
2005
2007
2009
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523519
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1.5.3 Change in transport accident mortality rates,
1995-2009 (or nearest year)
-71.0
-68.3
-67.2
-63.1
-61.7
-57.6
-57.1
-55.5
-52.5
-52.4
-52.1
-50.7
-50.0
-50.0
-48.5
-47.8
-47.3
-46.6
-41.6
-38.8
-35.5
-35.5
-34.9
-33.3
-33.3
-33.1
-30.3
-29.5
-28.1
-17.0
-11.0
-9.1
-8.7
6.5
13.3
-80
-60
-40
-20
0
20
%
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523538
33
1. HEALTH STATUS
1.6. Suicide
The intentional killing of oneself can be evidence not only
of personal breakdown, but also of a deterioration of the
social context in which an individual lives. Suicide may be
the end-point of a number of different contributing factors.
It is more likely to occur during crisis periods associated
with upheavals in personal relationships, through alcohol
and drug abuse, unemployment, clinical depression or
other forms of mental illness. Because of this, suicide is
often used as a proxy indicator of the mental health status
of a population. However, the number of suicides in certain
countries may be under-reported because of the stigma
that is associated with the act, or because of data issues
associated with reporting criteria (see “Definition and
comparability”).
Intentional self-harm is a significant cause of death in many
OECD countries, and there were almost 150 000 suicide
deaths in 2009. Rates were lowest in southern European
countries (Greece, Italy and Spain) and in Mexico and Israel,
at six or fewer deaths per 100 000 population (Figure 1.6.1).
They were highest in Korea, the Russian Federation,
H u n g a ry, a n d Ja p a n , a t m o re t h a n 1 9 d e a t h s p e r
100 000 population. There is a ten-fold difference between
Korea and Greece, the countries with the highest and lowest
suicide rates.
Death rates from suicide are three-to-four times greater for
men than for women across OECD countries (Figure 1.6.1),
a gap that has remained fairly stable over time. The exception is Korea, where women are much more likely to take
their own lives, although male rates are still twice those
of females. The gender gap is narrower for attempted
suicides, reflecting the fact that women tend to use less
fatal methods than men. Suicide is also related to age, with
young people aged under 25 and elderly people especially
at risk. While suicide rates among the latter have generally
declined over the past two decades, less progress has been
observed among younger people.
Since 1995, suicide rates have decreased in many OECD
countries, with pronounced declines of close to 40% or
more in Estonia, Luxembourg and Austria (Figure 1.6.2).
However, death rates from suicides have increased in
Korea, Chile, Japan, Mexico and Portugal, although in
Mexico rates remain at low levels, and in Japan rates have
been static since the late 1990s. In Korea, male suicide rates
more than doubled from 17 per 100 000 in 1995 to 39
in 2009, and rates among women are the highest in the
OECD, at 20 per 100 000 (Figure 1.6.3). Between 2006
and 2010, the number of persons treated for depression
and bipolar disease in Korea rose sharply (increases of
17 and 29 per cent respectively), with those in low socio-
34
economic groups more likely to be affected (HIRA, 2011).
Economic downturn, weakening social integration and the
erosion of the traditional family support base for the
elderly have all been implicated in Korea’s recent increase
in suicide rates (Kwon et al., 2009).
Suicide is often linked with depression and the abuse of
alcohol and other substances. Early detection of these
psycho-social problems in high-risk groups by families and
health professionals is an important part of suicide prevention campaigns, together with the provision of effective
support and treatment. Many countries are promoting
mental health and developing national strategies for prevention, focussing on at-risk groups (Hawton and van
Heeringen, 2009). In Germany, as well as Finland and
Iceland, suicide prevention programmes have been based
on efforts to promote strong multisectoral collaboration
and networking (NOMESCO, 2007).
Definition and comparability
The World Health Organization defines suicide as an
act deliberately initiated and performed by a person
in the full knowledge or expectation of its fatal
outcome. Comparability of data between countries is
affected by a number of reporting criteria, including
how a person’s intention of killing themselves is
ascertained, who is responsible for completing the
death certificate, whether a forensic investigation is
carried out, and the provisions for confidentiality of
the cause of death. Caution is required therefore in
interpreting variations across countries.
Mortality rates are based on numbers of deaths registered in a country in a year divided by the size of the
corresponding population. The rates have been
directly age-standardised to the 1980 OECD population to remove variations arising from differences in
age structures across countries and over time. The
source is the WHO Mortality Database. Deaths from
suicide are classified to ICD-10 codes X60-X84.
Mathers et al. (2005) have provided a general assessment of the coverage, completeness and reliability of
data on causes of death.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.6. Suicide
1.6.1 Suicide mortality rates, 2009 (or nearest year)
Total population
Males and females
Females
Greece
Mexico
Italy
Israel
Spain
United Kingdom
Portugal
Australia
Luxembourg
Netherlands
Germany
Slovak Republic
Denmark
Canada
Iceland
United States
Norway
Chile
Sweden
New Zealand
Ireland
OECD
Czech Republic
Austria
Poland
France
Switzerland
Belgium
Estonia
Slovenia
Finland
Japan
Hungary
Russian Federation
Korea
2.8
4.4
4.9
5.0
6.0
6.2
7.3
7.5
7.8
7.8
8.9
9.3
9.9
10.2
10.3
10.5
10.9
11.0
11.0
11.2
11.3
11.3
11.4
12.0
12.9
13.8
14.3
16.2
16.8
17.2
17.3
19.7
19.8
26.5
28.4
30
25
20
15
10
Age-standardised rates per 100 000 population
5
0
Males
4.8
0.8
1.5
2.1
1.6
2.6
2.6
2.9
3.3
2.7
4.6
4.1
1.7
5.3
4.9
3.9
4.3
6.2
4.1
6.0
5.0
4.6
5.1
3.4
5.2
3.5
6.8
8.7
8.4
4.8
6.7
8.9
10.5
8.0
7.9
7.5
8.0
8.8
9.7
9.8
12.5
11.9
13.3
11.2
14.1
17.9
15.0
15.7
16.6
17.1
15.7
18.5
16.1
17.8
18.0
18.1
20.1
19.7
23.2
21.6
20.6
24.6
31.2
28.2
26.0
29.2
33.8
49.4
39.3
19.7
0
10
20
30
40
50
Age-standardised rates per 100 000 population
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523557
1.6.2 Change in suicide rates,
1995-2009 (or nearest year)
Estonia
Luxembourg
Austria
Australia
Denmark
Germany
Russian Federation
Slovenia
Slovak Republic
Finland
Israel
Hungary
Italy
Czech Republic
New Zealand
France
Canada
Switzerland
Sweden
Spain
Belgium
Netherlands
OECD
United Kingdom
United States
Norway
Greece
Poland
Ireland
Iceland
Portugal
Mexico
Japan
Chile
Korea
1.6.3 Trends in suicide rates, selected OECD countries,
1995-2009
-55.2
-42.6
-37.5
-34.8
-34.0
-32.1
-32.1
-31.7
-30.1
-30.0
-29.6
-29.5
-25.8
-25.0
-24.3
-21.1
-19.0
-18.3
-16.7
-13.0
-12.4
-10.3
-10.3
-8.8
-7.9
-7.6
-6.7
-5.1
Austria
Japan
Korea
OECD
Age-standardised rates per 100 000 population
30
25
20
15
10
0.9
1.0
4.3
5
15.8
37.8
54.9
153.6
-60
-20
0
20
60
100
Percentage change
Source: OECD Health Data 2011; IS-GBE (2011).
1 2 http://dx.doi.org/10.1787/888932523576
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
0
1995
1997
1999
2001
2003
2005
2007
2009
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523595
35
1. HEALTH STATUS
1.7. Infant mortality
Infant mortality, the rate at which babies and children of
less than one year of age die, reflects the effect of economic
and social conditions on the health of mothers and
newborns, as well as the effectiveness of health systems.
In most OECD countries, infant mortality is low and there is
little difference in rates (Figure 1.7.1). A small group of
OECD and emerging countries, however, have infant mortality rates above ten deaths per 1 000 live births. In 2009,
rates ranged from less than three deaths per 1 000 live
births in Nordic countries (Iceland, Sweden, Finland),
Japan, Slovenia, Luxembourg and the Czech Republic, up to
a high of 13 and 15 in Turkey and Mexico respectively.
Infant mortality rates were also relatively high (six or
more deaths per 1 000 live births) in the United States and
in Chile.
In emerging countries (India, South Africa, Indonesia and
Brazil), infant mortality rates are above 20 deaths per
1 000 live births. In India, one-in-twenty children die before
their first birthday. The recent UN Commission on Information and Accountability for Women’s and Children’s Health
has called for renewed efforts by emerging countries to
accurately measure and monitor maternal and child deaths
and the health expenditure committed to improving the
health of mothers and babies (UN Commission, 2011).
Around two-thirds of the deaths that occur during the first
year of life are neonatal deaths (i.e. during the first four
weeks). Birth defects, prematurity and other conditions
arising during pregnancy are the principal factors contributing to neonatal mortality in developed countries. With an
increasing number of women deferring childbearing and a
rise in multiple births linked with fertility treatments, the
number of pre-term births has tended to increase (see
Indicator 1.8 “Infant health: Low birth weight”). In a number
of higher-income countries, this has contributed to a
leveling-off of the downward trend in infant mortality rates
over the past few years. For deaths beyond a month (post
neonatal mortality), there tends to be a greater range of
causes – the most common being SIDS (sudden infant death
syndrome), birth defects, infections and accidents.
All OECD countries have achieved remarkable progress in
reducing infant mortality rates from the levels of 1970,
when the average was approaching 30 deaths per 1 000 live
births, to the current average of 4.4 (Figure 1.7.2). This
equates to a cumulative reduction of 85% since 1970.
Portugal has seen its infant mortality rate reduced by
nearly 7% per year on average since 1970, moving from the
country with the highest rate in Europe to an infant mortality rate which is among the lowest in the OECD in 2009
(Figure 1.7.1). Large reductions in infant mortality rates
have also been observed in Korea, Israel and Turkey.
36
The reduction in infant mortality rates has been slower in
the Netherlands and the United States. At one time the
infant mortality rates in the United States was well below
the OECD average, but it is now above average (Figure 1.7.2).
Significant differences are evident among ethnic groups in
the United States, with Black or African-American women
more likely to give birth to high-risk, low birthweight
infants, and with an infant mortality rate more that double
that for white women (12.9 versus 5.6 in 2006) (NCHS, 2011).
Numerous studies have used infant mortality rates as a
health outcome to examine the effect of a variety of
medical and non-med ical d eterminants of health
(e.g. OECD, 2010a). Although most analyses show an overall
negative relationship between infant mortality and health
spending, the fact that some countries with a high level of
health expenditure do not exhibit low levels of infant
mortality suggests that more health spending is not necessarily required to obtain better results (Retzlaff-Roberts
et al., 2004). A body of research also suggests that many
factors beyond the quality and efficiency of the health
system – such as income inequality, the social environment, and individual lifestyles and attitudes – influence
infant mortality rates (Kiely et al., 1995).
Definition and comparability
The infant mortality rate is the number of deaths of
children under one year of age in a given year,
expressed per 1 000 live births. Neonatal mortality
refers to the death of children under 28 days.
Some of the international variation in infant and
neonatal mortality rates may be due to variations
among countries in registering practices of premature
infants. Most countries have no gestational age or
weight limits for mortality registration among live
birth infants. Minimal limits exist for Norway (to be
counted as a death following a live birth, the gestational age must exceed 12 weeks) and in the Czech
Republic, the Netherlands and Poland a minimum
gestational age of 22 weeks and/or a weight threshold
of 500g is applied.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.7. Infant mortality
1.7.1 Infant mortality rates, 2009 and decline 1970-2009 (or nearest year)
2009
Decline 1970-2009
Iceland
Japan
Slovenia
Luxembourg
Sweden
Finland
Czech Republic
Denmark
Greece
Norway
Ireland
Spain
Belgium
Germany
Korea
Estonia
Portugal
Italy
Austria
Israel
Netherlands
France
Australia
Switzerland
OECD
United Kingdom
New Zealand
Canada
Hungary
Poland
Slovak Republic
United States
Chile
Russian Federation
Turkey
China
Mexico
Brazil
Indonesia
South Africa
India
1.8
2.4
2.4
2.5
2.5
2.6
2.9
3.1
3.1
3.1
3.2
3.3
3.4
3.5
3.5
3.6
3.6
3.7
3.8
3.8
3.8
3.9
4.3
4.3
4.4
4.6
4.7
5.1
5.1
5.6
5.7
6.5
7.9
8.2
13.1
13.8
14.7
22.5
29.8
43.1
50.3
60
40
Deaths per 1 000 live births
20
0
5.0
4.3
5.8
5.7
3.7
4.1
4.9
3.8
5.6
3.3
4.5
5.3
4.6
4.7
6.3
4.0
6.8
5.2
4.8
6.0
3.0
3.9
3.6
3.2
4.5
3.5
3.2
3.3
4.9
4.7
3.8
2.8
5.7
2.6
6.0
4.5
4.3
3.6
3.1
n.a.
2.3
0
2
4
6
8
Average annual rate of decline (%)
Source: OECD Health Data 2011; World Bank and national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523614
1.7.2 Infant mortality rates, selected OECD countries, 1970-2009
Korea
Portugal
United States
OECD
Deaths per 1 000 live births
60
50
40
30
20
10
0
1970
1975
1980
1985
1990
1995
2000
2005
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523633
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
37
1. HEALTH STATUS
1.8. Infant health: Low birth weight
Low birth weight – defined as newborns weighing less than
2 500 grams – is an important indicator of infant health
because of the close relationship between birth weight and
infant morbidity and mortality. There are two categories of
low birth weight babies: those occurring as a result of
restricted foetal growth and those resulting from pre-term
birth. Low birth weight infants have a greater risk of poor
health or death, require a longer period of hospitalisation
after birth, and are more likely to develop significant
disabilities (UNICEF and WHO, 2004).
Risk factors for low birth weight include adolescent motherhood, a previous history of low weight births, engaging in
harmful behaviours such as smoking and excessive alcohol
consumption, having poor nutrition, a low body mass
index, a background of low parental socio-economic status,
and having had in-vitro fertilisation treatment.
One-in-fifteen babies born in OECD countries in 2009 – or
6.7% of all births – weighed less than 2 500 grams at birth
(Figure 1.8.1). The Nordic countries (Iceland, Sweden and
Finland), Estonia, Ireland and Korea reported the smallest
proportions of low-weight births, with less than 5% of live
births defined as low birth weight. Alongside a number of
emerging countries (India, South Africa and Indonesia),
Turkey and Japan are at the other end of the scale, with
rates of low birth weight infants above 9% (Figure 1.8.1).
Since 1980, and more so after 1995, the prevalence of low
birth weight infants has increased in most OECD countries
(Figure 1.8.2). There are several reasons for this rise. The
number of multiple births, with the increased risks of
pre-term births and low birth weight has risen steadily,
partly as a result of the rise in fertility treatments. Other
factors which may have influenced the rise in low birth
weight are older age at childbearing, and increases in the
use of delivery management techniques such as induction
of labour and caesarean delivery, which have increased the
survival rates of low birthweight babies.
Japan, Portugal and Spain have seen large increases in the
past three decades, such that the proportion of low birth
weight babies in these countries is now above the
OECD average (Figure 1.8.2). This contrasts with the proportions of low birth weight babies in Chile, Poland and
Hungary which have declined over the same time period.
Little change has occurred in Finland, Sweden and
Denmark, although Iceland and Norway saw rises.
38
Figure 1.8.3 shows some correlation between the percentage of low birth weight infants and infant mortality rates, a
relationship which is stronger with the inclusion of emerging countries. In general, countries reporting a low proportion of low birth weight infants also report relatively low
infant mortality rates. This is the case, for instance, in the
Nordic countries. Japan is an exception, since it reports the
highest proportion of low birth weight infants but one of
the lowest infant mortality rates.
Comparisons of different population groups within countries show that the proportion of low birth weight infants
can also be influenced by differences in education, income
and associated living conditions. In the United States,
marked differences between groups in the proportion of
low birth weight infants have been observed, with black
infants having a rate almost double that of white infants
(NCHS, 2011). Similar differences have also been observed
among the indigenous and non-indigenous populations in
Australia, Mexico and New Zealand, often reflecting the
disadvantaged living conditions of many of these mothers.
Definition and comparability
Low birth weight is defined by the World Health
Organization (WHO) as the weight of an infant at birth
of less than 2 500 grams (5.5 pounds) irrespective of
the gestational age of the infant. This is based on
epidemiological observations regarding the increased
risk of death to the infant and serves for international
comparative health statistics. The number of low
weight births is then expressed as a percentage of
total live births.
The majority of the data comes from birth registers,
however for Mexico the source is a national health
interview survey. A small number of countries supply
data for selected regions or hospital sectors only.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.8. Infant health: Low birth weight
1.8.1 Low birth weight infants, 2009 and change 1980-2009 (or nearest year)
2009
Change 1980-2009
Iceland
Sweden
Finland
Estonia
Ireland
Korea
Norway
Netherlands
Chile
New Zealand
Slovenia
Canada
Russian Federation
Australia
Denmark
Poland
Luxembourg
France
Switzerland
OECD
Germany
Italy
Austria
Slovak Republic
United Kingdom
Belgium
Czech Republic
Spain
Israel
Portugal
United States
Brazil
Greece
Hungary
Mexico
Japan
Turkey
Indonesia
South Africa
India
4.1
4.1
4.3
4.5
4.8
4.9
5.2
5.5
5.9
5.9
5.9
6.0
6.0
6.1
6.1
6.1
6.4
6.6
6.6
6.7
6.9
7.0
7.1
7.4
7.4
7.6
7.6
7.8
8.2
8.2
8.2
8.3
8.4
8.4
8.4
9.6
11.0
11.1
12.3
27.6
30
20
% of newborns weighing less than 2 500 g
10
0
20.6
-2.4
10.3
n.a.
20.0
n.a.
36.8
n.a.
-31.4
1.7
1.7
3.4
n.a.
8.9
5.2
-19.7
1.6
26.9
29.4
24.4
25.5
25.0
24.6
25.4
10.4
35.7
28.8
178.6
17.1
78.3
20.6
n.a.
42.4
-19.2
n.a.
84.6
n.a.
-14.6
n.a.
-8.0
-50
0
50
100
150
200
% change over the period
Source: OECD Health Data 2011; World Bank and national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523652
1.8.2 Trends in low birth weight infants,
selected OECD countries, 1980-2009
Finland
Japan
Spain
OECD
1.8.3 Low birth weight and infant mortality,
2009 (or nearest year)
Infant mortality (deaths per 1 000 live births)
50
R 2 = 0.67
% of newborns weighing less than 2 500 g
12
ZAF
40
10
30
IDN
8
BRA
20
6
MEX
TUR
10
4
RUS
CHL
FIN EST
SWE
2
1980
ISL
0
1985
1990
1995
2000
2005
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523671
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
0
3
6
SVK
USA
HUN
ISR
JPN
GRC
9
12
15
Low birth weight (%)
Source: OECD Health Data 2011; World Bank and national sources for
non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523690
39
1. HEALTH STATUS
1.9. Perceived health status
Most OECD countries conduct regular health surveys which
allow respondents to report on different aspects of their
health. A commonly-asked question relates to selfperceived health status, of the type: “How is your health in
general?”. Despite the subjective nature of this question,
indicators of perceived general health have been found to
be a good predictor of people’s future health care use and
mortality (for instance, see Miilunpalo et al., 1997).
For the purposes of international comparison however,
cross-country differences in perceived health status are
difficult to interpret because responses may be affected by
the formulation of survey questions and responses, and by
social and cultural factors. Since they rely on the subjective
views of the respondents, self-reported health status may
reflect cultural biases or other influences. And since the
elderly report poor health more often than younger people,
countries with a larger proportion of aged persons will also
have a lower proportion of people reporting good or very
good health. In addition, the institutionalised population,
which has poorer health than the rest of the population, is
often not surveyed.
With these limitations in mind, in almost all OECD
countries a majority of the adult population rate their
health as good or better (Figure 1.9.1). The United States,
New Zealand and Canada are the three leading countries,
with about nine out of ten people reporting to be in good
health. But the response categories offered to survey
respondents in these three countries are different from
those used in European countries and in Asian OECD
countries, which introduces an upward bias in the results
(see box on “Definition and comparability”).
In Mexico and Germany, about two-thirds of the adult
population rate their health as good or better. Less than
half of the adult population in the Slovak Republic, Japan,
Portugal and Korea rate their health as good or very good.
Focusing on within-country differences, men are more
likely to report good health in all countries except in
Australia, New Zealand and Finland where rates are
similar. The difference is especially large in Portugal and
the Czech Republic (Figure 1.9.1). Not surprisingly, people’s
rating of their own health tends to decline with age. In
many countries, there is a particularly marked decline in a
positive rating after age 45 and a further decline after
age 65. People who are unemployed, retired or inactive
report poor or very poor health more often (Baert and de
Norre, 2009). People with a lower level of education or
income also tend to report poorer health (Mackenbach
et al., 2008).
The percentage of the adult population rating their health
as good or very good has remained reasonably stable over
the past 30 years in most countries where long time series
40
are available, although Japan has seen some decline since
the mid-1990s (Figure 1.9.2). The same is generally true for
the population aged 65 years and over.
One possible interpretation of the relative stability of the
indicator of perceived general health may be related to how
it is measured – that is, based on a bounded variable
(i.e. respondents are asked to rank their health on a fivepoint scale that is unchanged over time), whereas life
expectancy is measured without any such limit. Another
interpretation is that people in these countries are living
longer now, but possibly not healthier.
Definition and comparability
Perceived health status reflects people’s overall
perception of their health, including both physical
and psychological dimensions. Typically ascertained
through health interview surveys, respondents are
asked a question such as: “How is your health in
general? Is it very good, good, fair, poor, very poor”.
OECD Health Data provides figures related to the
proportion of people rating their health to be “good/
very good” combined.
Caution is required in making cross-country comparisons of perceived health status, for at least two
reasons. First, people’s assessment of their health is
subjective and can be affected by factors such as
cultural background and national traits. Second, there
are variations in the question and answer categories
used to measure perceived health across surveys and
countries. In particular, the response scale used in the
United States, Canada, New Zealand and Australia is
asymmetric (skewed on the positive side), including
the following response categories: “excellent, very
good, good, fair, poor”. The data reported in OECD
Health Data refer to respondents answering one of the
three positive responses (“excellent, very good or
good”). By contrast, in most other OECD countries, the
response scale is symmetric, with response categories
being: “very good, good, fair, poor, very poor”. The
data reported from these countries refer only to the
first two categories (“very good, good”). Such a difference in response categories biases upward the results
from those countries that are using an asymmetric
scale.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.9. Perceived health status
1.9.1 Percentage of adults reporting to be in good health, 2009 (or nearest year)
Total population
Males and females
Females
1
United States
New Zealand1
Canada1
Switzerland
Australia1
Ireland
Iceland
Norway
Sweden
Israel
Denmark
Netherlands
Belgium
United Kingdom
Austria
Greece
Spain
Luxembourg
France
OECD
Czech Republic
Finland
Turkey
Mexico
Germany
Italy
Slovenia
Poland
Estonia
Hungary
Chile
Korea
Portugal
Japan
Slovak Republic
90.0
89.7
88.5
86.7
84.9
83.4
80.3
80.0
79.9
79.8
79.4
78.5
76.7
76.0
75.5
75.3
74.0
73.9
72.4
69.1
68.2
68.0
68.0
65.5
64.7
63.6
61.7
56.3
54.6
54.2
52.6
44.8
40.0
32.7
31.1
100
80
% of population aged 15 and over
60
40
20
Males
90.7
89.6
88.9
88.2
89.4
89.8
88.2
85.4
85.3
82.8
84.4
83.9
81.9
82.0
82.3
82.5
81.6
81.8
79.5
77.0
77.8
78.7
78.0
77.4
77.1
77.3
75.2
74.3
76.0
73.4
n.a.
78.6
76.4
74.9
71.6
73.4
68.0
72.4
66.9
66.4
68.0
65.5
69.5
71.8
70.1
66.7
63.3
68.1
63.6
64.2
63.0
59.3
58.1
60.2
57.5
58.9
59.6
53.0
52.2
50.0
53.1
40.7
34.6
34.7
30.9
34.4
28.5
20
48.9
45.7
40
60
80
100
% of population aged 15 and over
1. Results for these countries are not directly comparable with those for other countries, due to methodological differences in the survey
questionnaire resulting in an upward bias.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523709
1.9.2 Trends in the percentage of adults reporting to be in good health, selected OECD countries, 1980-2009
Finland
Japan
Netherlands
United States
% of population aged 15 and over
100
80
60
40
20
1980
1985
1990
1995
2000
2005
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523728
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
41
1. HEALTH STATUS
1.10. Diabetes prevalence and incidence
Diabetes is a chronic disease, characterised by high levels
of glucose in the blood. It occurs either because the
pancreas stops producing the hormone insulin (Type 1
diabetes), or through a combination of the pancreas having
reduced ability to produce insulin alongside the body being
resistant to its action (Type 2 diabetes). People with
diabetes are at a greater risk of developing cardiovascular
diseases such as heart attack and stroke if the disease is
left undiagnosed or poorly controlled. They also have
elevated risks for sight loss, foot and leg amputation due to
damage to nerves and blood vessels, and renal failure
requiring dialysis or transplantation.
(Figure 1.10.2). In Mexico and Japan the rate is less than
five new cases per 100 000 population. Alarmingly, there is
evidence that Type 1 diabetes is occurring at an earlier age
among children (IDF, 2009).
Diabetes was the principal cause of death of almost
300 000 persons in OECD countries in 2009, and is the
fourth or fifth leading cause of death in most developed
countries. Among people who died with diabetes, the main
cause of death for approximately half was cardiovascular
disease, and renal failure for an additional 10-20%.
Around one-quarter of medical expenditure is spent on
controlling elevated blood glucose, another quarter on
treating long-term complication of diabetes, and the
remainder on additional general medical care (IDF, 2006).
Increasing costs reinforce the need to provide effective care
for the management of diabetes and its complications
(see Indicator 5.2 “Avoidable admissions: Uncontrolled
diabetes”).
Diabetes is increasing rapidly in every part of the world, to
the extent that it has now assumed epidemic proportions.
Estimates suggest that in OECD countries, 83 million
people, or more than 6% of the population aged 20-79 years
had diabetes in 2010. If left unchecked, the number of
people with diabetes in OECD countries will reach almost
100 million in less than 20 years. This is emphasised by the
young age of the diabetic population, with almost half of
adults with diabetes aged less than 60 years (IDF, 2009).
Less than 5% of adults aged 20-79 years in Iceland, Norway
and the United Kingdom had diabetes in 2010, according to
the International Diabetes Federation. This contrasts with
Mexico and the United States, where more than 10% of the
population of the same age have the disease (Figure 1.10.1).
In most OECD countries, between 5 and 10% of the adult
population have diabetes.
Type 2 diabetes is largely preventable. A number of risk
factors, such as overweight and physical inactivity are
modifiable, and can also help reduce the complications
that are associated with diabetes. But in most countries,
the prevalence of overweight and obesity also continues to
increase (see Indicator 2.3 “Overweight and obesity among
adults”).
Type 1 diabetes accounts for only 10-15% of all diabetes
cases. It is the predominant form of the disease in younger
age groups in most developed countries. In Nordic countries
(Finland, Sweden and Norway) the rate of new cases in
children is notably high. Based on disease registers and
recent studies, the annual number of new cases in children
aged under 15 years is 25 or more per 100 000 population
42
The economic impact of diabetes is substantial. Health
expenditure in OECD countries in 2010 to treat and
prevent diabetes and its complications was estimated at
USD 345 billion (IDF, 2009). In the United States alone, some
USD 116 billion was spent on diabetes-related care in 2007
(ADA, 2008). In Australia, direct health care expenditure
on diabetes in 2004-05 accounted for nearly 2% of the
recurrent health expenditure (AIHW, 2008a).
Definition and comparability
The sources and methods used by the International
Diabetes Federation for publishing national prevalence and incidence estimates of diabetes are
outlined in their Diabetes Atlas, 4th edition (IDF, 2009).
Country data were derived from studies published
between 1980 and February 2009, and were only
included if they met several criteria for reliability.
The IDF noted that studies from several OECD countries – Canada, France, Italy, the Netherlands, Norway,
Slovenia and the United Kingdom – only provided
self-reported data on diabetes. To account for undiagnosed diabetes, the prevalences of diabetes for the
United Kingdom and Canada were multiplied by a
factor of 1.5, in accordance with local recommendations (the United Kingdom) and findings from the
United States (Canada), and doubled for other
countries, based on data from other regional studies.
Prevalence rates were adjusted to the World Standard
Population to facilitate cross-national comparisons.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.10. Diabetes prevalence and incidence
1.10.1 Prevalence estimates of diabetes, adults aged 20-79 years, 2010
%
12
10.8
10.3
10
9.7
8.9
8
7.6
6.4
6
4.5
4.2
4
3.6
2
4.8
5.0
5.2
5.2
5.2
5.3
5.6
5.7
5.7
5.7
5.9
6.4
6.5
6.5
6.6
7.7
7.8
7.9
9.2
8.0
6.7
6.0
3.6
1.6
Un
Ic
el
an
d
N
i t e or
w
d
K i ay
ng
do
m
C
So
u t hin a
h
Af
In r i c a
do
ne
si
a
Ja
pa
Ir e n
la
nd
S
Ne we
w den
Z
Ne e ala
th nd
er
la
n
De ds
nm
ar
k
Ch
Au il e
st
ra
l
Fi ia
nl
an
d
It a
ly
Sl
o v Gr
ak ee
Re c e
pu
bl
ic
Br
az
il
Is
ra
el
OE
CD
Sp
ai
Fr n
an
c
Po e
la
Sl nd
ov
en
ia
In
di
a
Ko
re
Tu a
r
Ge ke y
rm
an
Ca y
na
P da
Un or t
i te ug
a
d
St l
at
es
M
ex
ic
o
0
Note: The data cover both Type 1 and Type 2 diabetes. Data are age-standardised to the World Standard Population.
Source: IDF (2009).
1 2 http://dx.doi.org/10.1787/888932523747
1.10.2 Incidence estimates of Type 1 diabetes, children aged 0-14 years, 2010
Cases per 100 000 population
60
57.4
50
41.0
40
30
27.9
21.7 22.2 22.4
20
10
8.4
9.0
9.9
13.3 13.6
12.2 12.9 13.0
11.3 12.1
10.4 11.1
23.7 24.5
18.8
17.2 18.0 18.0
16.3 16.9
14.7 15.3 15.4 15.5
5.9
2.4
1.5
0.6
il e
It a
it z ly
er
la
n
Gr d
ee
ce
Is
ra
Sl el
ov
Ru
en
ss
i a Hun i a
n
F e gar
de y
ra
tio
Fr n
an
c
Po e
la
nd
Sp
ai
Sl
ov Au n
ak st
Re r i a
pu
bl
Ic i c
el
an
Es d
to
n
B ia
Lu elg
xe ium
m
bo
ur
Ir e g
la
nd
Cz
ec OE
h
Re C D
N e pu
w bli
Ze c
al
Ge and
Ne r ma
th ny
er
la
nd
Ca s
na
De da
nm
Au ar k
Un s t
r
Un i t e d a li a
i te S t
a
d
K i tes
ng
do
No m
rw
S w ay
ed
e
Fi n
nl
an
d
Sw
Ch
n
o
ic
pa
ex
Ja
M
Ch
in
a
0
Source: IDF (2009).
1 2 http://dx.doi.org/10.1787/888932523766
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
43
1. HEALTH STATUS
1.11. Cancer incidence
In 2008, an estimated 5.2 million new cases of cancer were
diagnosed in OECD countries, at an average of 261 per
100 000 population. Incidence rates varied substantially
among countries, being comparatively high in Denmark,
Ireland, Australia, Belgium and New Zealand at over 300
(Figure 1.11.1). In a number of OECD and emerging countries including India, Mexico, Indonesia and Turkey, rates
were below 150.
High-income countries tend to have higher cancer incidence rates than middle- or lower-income ones. People in
high-income countries are more likely to be overweight,
have higher alcohol consumption and be inactive, and each
of these factors increase the risk of several common
cancers. The high levels of cancer incidence in Denmark
are related to these factors, given the above average proportions of Danish women who smoke, and the high
consumption of alcohol. However, Denmark and other high
income countries also have good records of diagnosing
cancers, which contributes to higher rates. In Australia and
New Zealand, high rates of melanoma of the skin contribute to the high overall incidence rate, along with above
average rates of breast and prostate cancer. The lower
incidence of cancer in emerging countries is in part related
to the lesser use of screening tests and issues of data
quality, but also due to the much smaller impact, to date, of
tobacco, poor diet and lack of exercise.
The most commonly diagnosed cancers in OECD countries
in 2008 were colorectal (665 000 cases) and lung cancer
(663 000 cases), each making up 13% of all new cases.
Among men, prostate cancer was the most common cancer
(632 000 cases, or 23% of all new male cancers), followed by
lung and colorectal. Among women, breast cancer was
most common (639 000 cases, or 27% of all new female
cancers), and then colorectal and lung cancer.
Relatively high incidence rates of breast cancer are reported
in Belgium, France, Israel, the Netherlands and Ireland, with
rates close to or exceeding 100 cases per 100 000 females
(Figure 1.11.2). A number of countries have rates which are
less than half this value, at 50 or below – Estonia, Poland and
the Russian Federation, as well as Japan, Korea and a
number of emerging countries. Age, family history of the
disease, previous diagnosis, increased exposure to
hormones, overweight and excessive alcohol drinking all
increase the risk of developing breast cancer.
Incidence rates for breast cancer have increased over the
past decade in almost all OECD countries for which data are
available. These increases are largely due to improvements
in diagnosis and the growing number of women who
receive mammography screening, leading to a subsequent
rise in the detection of new cases. An exception is the
44
United States, where a recent decline in breast cancer
incidence has been linked to a lower use of menopausal
hormones, as well as a decline in mammography screening
(American Cancer Society, 2010) (see Indicator 5.9,
“Screening, survival and mortality for breast cancer”.
Prostate cancer has become the most commonly diagnosed
cancer among males in most OECD countries, particularly
among men over 65 years of age. The rise in the reported
incidence of prostate cancer in many countries since
the 1990s is due largely to the greater use of prostatespecific antigen (PSA) diagnostic tests, although the use of
these tests has also fluctuated because of their cost and
uncertainty about the long-term benefit to patients.
In 2008, the incidence of prostate cancer was highest in
Ireland, France, Norway and Sweden, with an agestandardised rate of more than 110 cases per 100 000 males
(Figure 1.11.3). Among OECD countries, low rates of
prostate cancer were reported in Turkey, Greece, Korea and
Japan.
The causes of prostate cancer are not well-understood. Age
and family history are the main risk factors. Some evidence
suggests that a number of dietary and environmental
factors might also influence the risk of prostate cancer
(American Cancer Society, 2010).
Definition and comparability
Cancer incidence rates are the number of new cancer
cases diagnosed in a year per 100 000 population.
Rates have been age-standardised to the WHO World
Standard Population.
A l l ca n c e r s a re d e f i n e d a s c a n c e r s co d e d t o
ICD-10 C00-C97 (excluding non-melanoma skin
cancer C44), colorectal C18-C21, lung C33-C34, female
breast C50, cervix C53 and prostate C61.
Data are sourced from the International Agency for
Research on Cancer (IARC) GLOBOCAN Database
(Ferlay et al., 2010). Estimates for 2008 are based on
cancer incidence rates over recent years.
The international comparability of cancer incidence
data can be affected by differences in medical
training and practices across countries, as well as the
completeness and quality of cancer registry data.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.11. Cancer incidence
100
321.1
314.1
317.0
309.4
300.4
300.2
297.9
296.6
290.4
289.9
288.5
288.3
286.6
284.0
282.1
274.3
269.4
269.3
264.8
262.4
260.9
260.6
259.7
250.6
250.1
241.4
230.1
225.1
223.2
201.1
200.5
181.0
176.7
162.0
144.8
98.5
150
143.5
128.4
200
171.3
250
202.0
300
309.2
1.11.1 All cancers incidence rates, total population, 2008
Age-standardised rates per 100 000 population
350
50
In
M di a
e
In x i c
do o
ne
s
Tu ia
rk
Gr e y
ee
c
Br e
az
Ru
i
Ch l
ss
ia
il e
n
C
Fe h
de in a
ra
ti
So J on
ut apa
h
A n
Po fric
r tu a
g
Po al
la
E s nd
to
ni
Sp a
F i a in
nl
a
Au nd
s
Sl
ov S tr i a
ak we
Re den
pu
bl
i
OE c
C
Ko D
Sl r e a
o
Un S w i ven
i te t ze ia
d rla
Ki n
ng d
do
m
Ge It al
Lu rm y
xe a
m ny
bo
H u ur g
ng
Cz
a
ec I r y
h sr
Re a e
N e pu l
th bl
er ic
la
n
Ic d s
el
a
C a nd
na
Un No d a
i te r w
d ay
St
at
Ne Fr es
w an
Ze ce
al
B e and
lg
A u ium
st
ra
Ir e l i a
De l an
nm d
ar
k
0
Source: Ferlay et al. (2010).
1 2 http://dx.doi.org/10.1787/888932523785
1.11.2 Female breast cancer incidence rates, 2008
China
India
Mexico
Turkey
Indonesia
Korea
Chile
South Africa
Brazil
Japan
Russian Federation
Greece
Poland
Estonia
Slovak Republic
Hungary
Portugal
Spain
Slovenia
Czech Republic
Austria
OECD
United States
Norway
Germany
Luxembourg
Sweden
Canada
Australia
Iceland
Italy
Finland
United Kingdom
Denmark
New Zealand
Switzerland
Ireland
Israel
Netherlands
France
Belgium
21.6
22.9
27.2
28.3
36.2
38.9
40.1
41.0
42.3
42.7
43.2
44.9
48.9
50.2
53.4
57.9
60.0
61.0
65.5
67.7
69.9
71.6
76.0
76.2
81.8
82.3
82.7
83.2
84.8
86.2
86.3
86.6
87.9
89.1
89.4
89.4
93.9
96.8
96.8
99.7
109.4
0
25
50
75
100
125
150
Age-standardised rates per 100 000 females
Source: Ferlay et al. (2010).
1 2 http://dx.doi.org/10.1787/888932523804
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1.11.3 Male prostate cancer incidence rates, 2008
India
China
Indonesia
Turkey
Greece
Korea
Japan
Russian Federation
Hungary
Mexico
Slovak Republic
Estonia
Poland
Portugal
Brazil
Israel
Spain
Chile
Italy
South Africa
Slovenia
Czech Republic
OECD
Denmark
Netherlands
Luxembourg
United Kingdom
Germany
Austria
United States
Switzerland
Finland
New Zealand
Canada
Iceland
Belgium
Australia
Sweden
Norway
France
Ireland
3.7
4.3
10.6
14.8
17.7
22.4
22.7
26.1
32.9
33.4
39.8
42.8
44.3
50.1
50.3
55.1
57.2
57.4
58.4
59.7
61.6
63.0
70.5
72.5
73.4
74.8
79.7
82.7
83.1
83.8
91.3
96.6
99.7
101.5
102.2
102.3
105.0
114.2
115.6
118.3
126.3
0
25
50
75
100
125
150
Age-standardised rates per 100 000 males
Source: Ferlay et al. (2010).
1 2 http://dx.doi.org/10.1787/888932523823
45
1. HEALTH STATUS
1.12. AIDS incidence and HIV prevalence
The first cases of Acquired Immunodeficiency Syndrome
(AIDS) were diagnosed 30 years ago. The onset of AIDS is
normally caused as a result of HIV (human immunodeficiency virus) infection and can manifest itself as a number
of different diseases, such as pneumonia and tuberculosis,
as the immune system is no longer able to defend the body,
leaving it susceptible to opportunistic infections and
tumors. There is a time lag between HIV infection, AIDS
diagnosis and death, which can be any number of years
depending on the treatment administered. Despite worldwide research, there is no cure currently available.
In 2009, around 50 000 new cases of AIDS were reported
across OECD countries, representing an unweighted
average incidence rate of 14.0 per million population
(Figure 1.12.1). Following the first reporting of AIDS cases in
the early 1980s, the number rose rapidly to reach an
average of more than 40 new cases per million population
across OECD countries at its peak in the middle of
the 1990s, nearly three times the current incidence rate
(Figure 1.12.2). Public awareness and prevention campaigns
contributed to steady declines in reported cases through
the second half of the 1990s. In addition, the development
and greater availability of antiretroviral drugs, which
reduce or slow down the development of the disease, led to
a sharp decrease in incidence during 1996-97.
The United States has consistently had the highest AIDS
incidence rates among OECD countries, although it is
important to note that the case reporting definitions were
expanded in 1993 and hence differ from the definition used
across Europe and other OECD countries. The change in
definition also explains the large increase in cases in the
United States in 1993 (Figure 1.12.2). Among emerging
countries, the situation in South Africa remains dire with
an incidence rate more than 50 times that of the United
States. In excess of 10% of the entire population – and close
to one-in-five of the adult population – was living with HIV
infection in 2009, although there is some evidence of a
slowing in incidence (UNAIDS, 2010).
In Europe, Spain reported the highest incidence rates in the
first decade following the outbreak, although there has
been a sharp decline since 1994, currently leaving Estonia
and Portugal with the highest rates among European
countries. Central European countries such as the Czech
and Slovak Republics, Poland and Hungary, along with
Iceland, Turkey and Germany reported the lowest incidence
rates of AIDS among OECD countries in 2009.
46
In the United States, more than one million people are
living with HIV/AIDS, with one-in-five unaware of their
infection (CDC, 2010a). Almost three-quarters of new cases
of AIDS are among men, and racial and ethnic minorities
continue to be disproportionately affected by the epidemic.
In Canada, Aboriginal people are over-represented. The
predominant modes of transmission of HIV are through
men having sex with men, and heterosexual contact.
However, among eastern European countries injecting drug
use is also a common mode (ECDC and WHO Europe, 2010).
In recent years, the overall decline in AIDS cases in OECD
countries has slowed down. This reversal has been accompanied by evidence of increasing transmission of HIV in
several European countries, attributed to complacency
regarding the effectiveness of treatment and a waning of
public awareness regarding drug use and sexual practice.
Further inroads in AIDS incidence rates will require more
intensive HIV prevention programmes that are focused and
adapted to reach those most at risk of HIV infection
(UNAIDS, 2010).
Definition and comparability
The incidence rate of AIDS is the number of new cases
per million population at year of diagnosis. The prevalence rate of HIV is the proportion of the population
living with the disease at a given time. Note that data
for recent years are provisional due to reporting
delays, which sometimes can be for several years
depending on the country.
The United States expanded their AIDS surveillance
case definition in 1993 to include T-lymphocyte count
criteria. This broadening of the definition led to a
large increase in the number of new cases in the
United States in 1993 and explains some of the
current variations in AIDS incidence between the
United States and other OECD countries.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1. HEALTH STATUS
1.12. AIDS incidence and HIV prevalence
1.12.1 AIDS incidence and estimated HIV prevalence, 2009 (or nearest year)
AIDS incidence
HIV prevalence
Iceland
Slovak Republic
Turkey
India (1998)
Poland
Czech Republic
Hungary
Germany
Japan
Norway
Finland
Luxembourg
Korea
New Zealand
Russian Federation
Israel
Denmark
Canada
Sweden
Greece
Austria
Australia
Ireland
Slovenia
United Kingdom
Belgium
China
Netherlands
France
OECD
Italy
Indonesia
Switzerland
Spain
Portugal
Estonia
Mexico
Chile
United States
Brazil
South Africa
0.0
0.7
1.0
1.1
2.0
2.2
2.3
2.8
3.4
3.7
3.9
4.0
4.4
5.1
5.9
6.1
6.5
6.6
6.8
7.7
7.8
8.0
8.1
8.3
8.9
9.6
10.0
10.8
11.4
14.0
14.3
16.8
16.9
22.6
27.9
28.4
50.5
51.3
122.2
181.8
6 842.9
200
150
100
New cases per million population
50
0
0.31
0.01
0.01
0.20
0.07
0.02
0.01
0.08
0.01
0.08
0.05
0.20
0.02
0.06
0.70
0.10
0.10
0.20
0.09
0.08
0.18
0.09
0.15
0.05
0.14
0.13
0.05
0.13
0.24
0.16
0.24
0.13
0.23
0.28
0.40
0.74
0.20
0.24
0.39
0.31
11.2
0
0.2
0.4
0.6
0.8
1.0
%
Source: OECD Health Data 2011; UNAIDS (2010).
1 2 http://dx.doi.org/10.1787/888932523842
1.12.2 Trends in AIDS incidence rates, selected OECD countries, 1981-2009
Estonia
Portugal
United States
OECD
New cases per million population
300
250
200
150
100
50
0
1981
1986
1991
1996
2001
2006
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523861
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
47
2. NON-MEDICAL DETERMINANTS
OF HEALTH
2.1. Tobacco consumption among adults
2.2. Alcohol consumption among adults
2.3. Overweight and obesity among adults
2.4. Overweight and obesity among children
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
49
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.1. Tobacco consumption among adults
Tobacco is responsible for about one-in-ten adult deaths
worldwide, equating to about 6 million deaths each year
(Shafey et al., 2009). It is a major risk factor for at least two
of the leading causes of premature mortality – circulatory
disease and cancer, increasing the risk of heart attack,
stroke, lung cancer, cancers of the larynx and mouth, and
pancreatic cancer. Smoking also causes peripheral vascular
disease and hypertension. In addition, it is an important
contributory factor for respiratory diseases such as chronic
obstructive pulmonary disease (COPD), while smoking
among pregnant women can lead to low birth weight and
illnesses among infants. It remains the largest avoidable
risk to health in OECD countries.
Smoking prevalence among men is higher in all OECD
countries except Sweden. Male and female rates are
nearly equal in Iceland, Norway and the United Kingdom
(Figure 2.1.2). Female smoking rates continue to decline in
most OECD countries, and in a number of cases (Canada,
Ireland, the Netherlands and the United States) at an even
faster pace than male rates. However, in three countries
female smoking rates have been increasing over the last
ten years (Czech Republic, Greece and Korea), but even in
these countries women are still less likely to smoke than
men. In 2009, the gender gap in smoking rates was particularly large in Korea, Japan and Turkey, as well as in the
Russian Federation, Indonesia and China (Figure 2.1.2).
The proportion of daily smokers among the adult population varies greatly, even between neighboring countries
(Figure 2.1.1). Thirteen of 34 OECD countries had less than
20% of the adult population smoking daily in 2009. Rates
were lowest in Mexico, Sweden, Iceland, the United States,
Canada and Australia. Although large disparities remain,
smoking rates across most OECD countries have shown a
marked decline. On average, smoking rates have decreased
by about one-fifth over the past ten years, with a higher
decline amongst men than women. Large declines
since 1999 occurred in Denmark (31% to 19%), Iceland
(25% to 16%), Norway (32% to 21%), Canada (24% to 16%)
and New Zealand (26% to 18%). Greece maintains the
highest level of daily smoking at 40% of the adult population, along with Chile and Ireland, with around 30%.
Smoking rates are also high in the Russian Federation.
Greece and the Czech Republic are among the few OECD
countries where smoking rates appear to be unchanged or
increasing.
Several studies provide strong evidence of socio-economic
differences in smoking and mortality (Mackenbach et al.,
2008). People in lower social groups have a greater prevalence and intensity of smoking, a higher all-cause mortality
rate and lower rates of cancer survival (Woods et al., 2006).
The influence of smoking as a determinant of overall
health inequalities is such that, if the entire population
was non-smoking, mortality differences between social
groups would be halved (Jha et al., 2006).
In the post-war period, most OECD countries tended to
follow a general pattern marked by very high smoking rates
among men (50% or more) through to the 1960s and 1970s,
while the 1980s and the 1990s were characterised by a
marked downturn in tobacco consumption. Much of this
decline can be attributed to policies aimed at reducing
tobacco consumption through public awareness campaigns,
advertising bans and increased taxation, in response to
rising rates of tobacco-related diseases. In addition to government policies, actions by anti-smoking interest groups
were very effective in reducing smoking rates by changing
beliefs about the health effects of smoking, particularly in
North America (Cutler and Glaeser, 2006).
50
Definition and comparability
The proportion of daily smokers is defined as the
percentage of the population aged 15 years and over
who report smoking every day.
International comparability is limited due to the lack
of standardisation in the measurement of smoking
habits in health interview surveys across OECD countries. Variations remain in the age groups surveyed,
the wording of questions, response categories and
survey methodologies, e.g. in a number of countries,
respondents are asked if they smoke regularly, rather
than daily.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.1. Tobacco consumption among adults
2.1.1 Adult population smoking daily, 2009 and change in smoking rates, 1999-2009 (or nearest year)
2009
Change 1999-2009
India
Mexico
South Africa
Sweden
Brazil
Iceland
United States
Canada
Australia
New Zealand
Finland
Portugal
Slovenia
Denmark
Luxembourg
Slovak Republic
Israel
Switzerland
Belgium
Norway
United Kingdom
Germany
OECD
Netherlands
Austria
Italy
China
Indonesia
Czech Republic
Japan
Korea
Estonia
France
Spain
Hungary
Poland
Turkey
Ireland
Chile
Russian Federation
Greece
10.7
13.3
13.8
14.3
15.5
15.8
16.1
16.2
16.6
18.1
18.6
18.6
18.9
19.0
19.0
19.4
20.3
20.4
20.5
21.0
21.5
21.9
22.1
22.6
23.2
23.3
24.1
24.2
24.6
24.9
25.6
26.2
26.2
26.2
26.5
27.0
27.4
29.0
29.8
33.8
39.7
50
40
30
% of population aged 15 years and over
20
10
0
-34.0
n.a.
-42.5
-25.9
n.a.
-37.3
-16.1
-31.9
-24.9
-30.4
-19.8
-9.7
n.a.
-38.7
-26.9
n.a.
-15.8
-29.4
-19.6
-34.4
-20.4
-11.3
-17.9
-18.7
-4.5
-5.7
-16.6
-15.7
4.7
-25.9
-16.6
-11.8
-6.4
-21.1
-12.3
-2.2
n.a.
-12.1
n.a.
-0.3
5.6
-50
-25
0
25
% change over the period
Source: OECD Health Data 2011; national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523880
2.1.2 Females and males smoking daily, 2009 (or nearest year)
Females
Males
% of population aged 15 years and over
60
55
50
30
20
14
16
18
18
18
18
19
19
21
21
22
22
22
22
15
16
14
15
2
13
27
27
27
26
30
28
27
30
31
32
31
31
27
17
14
24
23
22
21
20
10
22
26
16
7
17
17
16
18
18
20
7
18
17
12
11
19
17
13
19
34
34
26
21
22
47
21
17
16
12
12
7
2
3
Un
Sw
ed
I en
i te c ela
d nd
St
Au ate
st s
ra
C a li a
na
da
In
di
Ne B a
w ra
S o Z e a z il
ut lan
h
Af d
r
No ic a
rw
M ay
ex
Fi ico
nl
D a
L en nd
Un u xe m a
i t e mb r k
d ou
Ki r
ng g
d
Sl om
S w ov
i t z eni
er a
l
B an
Ne elg d
t h ium
er
Sl G l an
ov e ds
ak rm
Re an
pu y
Po bli
r tu c
g
OE al
Au CD
st
ri
Is a
ra
Cz
e
ec
h It l
Re a l
pu y
b
Fr li c
an
Ir e c e
la
n
S d
Hu p a in
ng
ar
y
Ch
Po il e
la
E s nd
to
n
Ja ia
pa
Tu n
rk
e
Ko y
re
Gr a
ee
ce
Ru
s s In C h
i a d in a
n on
Fe e
de si a
ra
tio
n
0
22
33
45
39
39
40
45
44
44
Source: OECD Health Data 2011; national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523899
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
51
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.2. Alcohol consumption among adults
The health burden related to excessive alcohol consumption, both in terms of morbidity and mortality, is considerable in most parts of the world (Rehm et al., 2009; WHO,
2004a). High alcohol intake is associated with numerous
harmful health and social consequences, such as increased
risk of heart, stroke and vascular diseases, as well as liver
cirrhosis and certain cancers. Foetal exposure to alcohol
increases the risk of birth defects and intellectual impairments. Alcohol also contributes to death and disability
through accidents and injuries, assault, violence, homicide
and suicide, and is estimated to cause more than 2 million
deaths worldwide per year. In the Russian Federation, the
sharp rise in premature mortality and decline in life
expectancy during the 1990s was due, in part, to excessive
alcohol consumption (WHO, 2004a). It is, however, one of
the major avoidable risk factors for disease.
Alcohol consumption as measured by annual sales stands
at 9.1 litres per adult on average across OECD countries,
using the most recent data available (Figure 2.2.1). France,
Austria, Portugal, the Czech Republic and Estonia reported
the highest consumption of alcohol, with 12.0 litres or
more per adult per year in 2009. Low alcohol consumption
was recorded in Indonesia, India, Turkey and Israel where
religious and cultural traditions restrict the use of alcohol
among some population groups, as well as in China,
Mexico and some of the Nordic countries (Norway, Iceland
and Sweden).
Although average alcohol consumption has gradually
fallen in many OECD countries over the past three decades,
it has risen in some others such as Finland and Mexico.
There has been a degree of convergence in drinking habits
across the OECD, with wine consumption increasing in
many traditional beer-drinking countries and vice versa.
The traditional wine-producing countries of Italy, France
and Spain, as well as the Slovak Republic and Germany
have seen per capita consumption fall by one third or more
since 1980 (Figure 2.2.1). Alcohol consumption in the
Russian Federation, as well as in Brazil and China has risen
substantially, although in the latter two countries per
capita consumption is still low.
Variations in alcohol consumption across countries and
over time reflect not only changing drinking habits but also
the policy responses to control alcohol use. Curbs on
advertising, sales restrictions and taxation have all proven
52
to be effective measures to reduce alcohol consumption
(Bennett, 2003). Strict controls on sales and high taxation
are mirrored by overall lower consumption in most Nordic
countries, while falls in consumption in France, Italy and
Spain may also be associated with the voluntary and
statutory regulation of advertising, following a 1989
European directive.
Although adult alcohol consumption per capita gives
useful evidence of long-term trends, it does not identify
sub-populations at risk from harmful drinking patterns.
The consumption of large quantities of alcohol at a single
session, termed “binge drinking”, is a particularly dangerous pattern of consumption (Institute of Alcohol Studies,
2007), which is on the rise in some countries and social
groups, especially among young males.
In 2010, the World Health Organization endorsed a global
strategy to combat the harmful use of alcohol, through
direct measures such as medical services for alcoholrelated health problems, and indirect measures such as
policy options for restricting the availability and marketing
of alcohol (WHO, 2010a).
Definition and comparability
Alcohol consumption is defined as annual sales of
pure alcohol in litres per person aged 15 years and
over. The methodology to convert alcoholic drinks to
pure alcohol may differ across countries. Official
statistics do not i ncl u d e u n re co rd e d a lco h o l
consumption, such as home production.
Italy reports consumption for the population 14 years
and over, Sweden for 16 years and over, and Japan
20 years and over. In some countries (e.g. Luxembourg),
national sales do not accurately reflect actual
consumption by residents, since purchases by nonresidents may create a significant gap between
national sales and consumption.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.2. Alcohol consumption among adults
2.2.1 Alcohol consumption, population aged 15 and over, 2009 (or nearest year) and change between 1980 and 2009
2009
Change 1980-2009
Indonesia
India
Turkey
Israel
China
Mexico
Brazil
Norway
South Africa
Iceland
Japan
Sweden
Italy
Canada
Chile
United States
Korea
Slovak Republic
OECD
Greece
New Zealand
Netherlands
Belgium
Germany
Finland
Spain
Australia
Denmark
Switzerland
Poland
United Kingdom
Ireland
Russian Federation
Slovenia
Hungary
Luxembourg
Estonia
Czech Republic
Austria
Portugal
France
0.1
0.7
1.5
2.5
4.4
5.9
6.2
6.7
7.2
7.3
7.4
7.4
8.0
8.2
8.6
8.8
8.9
9.0
9.1
9.2
9.3
9.4
9.7
9.7
10.0
10.0
10.1
10.1
10.1
10.2
10.2
11.3
11.5
11.5
11.8
11.8
12.0
12.1
12.2
12.2
12.3
15
10
Litres per capita (15 years and over)
5
0
-25
47
-17
-11
159
74
188
12
17
70
4
10
-52
-23
-21
-15
n.a.
-38
-9
-19
-21
-18
-28
-32
27
-46
-22
-14
-25
-11
9
18
45
n.a.
-21
-14
n.a.
3
-16
-18
-37
-100
0
100
200
% change over the period
Source: OECD Health Data 2011; WHO (2011a).
1 2 http://dx.doi.org/10.1787/888932523918
2.2.2 Trends in alcohol consumption, selected OECD countries, 1980-2009
France
Hungary
United States
OECD
Litres per capita (15 years +)
20
15
10
5
1980
1985
1990
1995
2000
2005
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523937
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
53
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.3. Overweight and obesity among adults
The rise in overweight and obesity is a major public health
concern. Obesity is a known risk factor for numerous
health problems, including hypertension, high cholesterol,
diabetes, cardiovascular diseases, respiratory problems
(asthma), musculoskeletal diseases (arthritis) and some
forms of cancer. Mortality risk also increases sharply once
the overweight threshold is crossed (Sassi, 2010).
Based on latest available surveys, more than half (50.3%) of
the adult population in the OECD report that they are overweight or obese. Among those countries where height and
weight were measured, the proportion was even greater,
at 55.8%. The prevalence of overweight and obesity among
adults exceeds 50% in no less than 19 of 34 OECD countries.
In contrast, overweight and obesity rates are much lower in
Japan and Korea and in some European countries (France
and Switzerland), although even in these countries rates
are increasing.
The prevalence of obesity, which presents even greater
health risks than overweight, varies nearly tenfold among
OECD countries, from a low of 4% in Japan and Korea, to
30% or more in the United States and Mexico (Figure 2.3.1).
Across the entire OECD region, 17% of the adult population
are obese. Average obesity rates among men and women are
similar, although there are disparities in some countries. In
South Africa, Chile, Turkey and Mexico, a greater proportion
of women are obese, whereas in the Russian Federation,
Luxembourg and Spain men are.
Obesity prevalence has more than doubled over the past
20 years in Australia and New Zealand, and increased by
half in the United Kingdom and the United States
(Figure 2.3.2). Some 20-24% of adults in Australia, Canada,
the United Kingdom and Ireland are obese, about the same
rate as in the United States in the early 1990s. Obesity rates
in many western European countries have also increased
substantially over the past decade. The rapid rise occurred
regardless of where levels stood two decades ago. Obesity
almost doubled in both the Netherlands and the United
Kingdom, even though the current rate in the Netherlands
is around half that of the United Kingdom.
The rise in obesity has affected all population groups,
regardless of sex, age, race, income or education level, but
to varying extents. Evidence from a number of countries
(Australia, Austria, Canada, England, France, Italy, Korea,
Spain and the United States) indicates that obesity tends to
be more common among individuals in disadvantaged
socio-economic groups, especially if they are female (Sassi
et al., 2009). There is also a relationship between the
number of years spent in full-time education and obesity,
with the more educated displaying lower rates. Again, the
gradient in obesity is stronger in women than in men
(Sassi, 2010). A persistent socio-economic gradient in
54
overweight and obesity is an indication that government
policies have so far not addressed the link between obesity,
and social disadvantage.
A number of behavioural and environmental factors have
contributed to the rise in overweight and obesity rates in
industrialised countries, including falling real prices of
food and more time spent being physically inactive.
Overweight and obesity has risen rapidly in children in
recent decades, reaching double-figure rates in most OECD
countries (see also Indicator 2.4 “Overweight and obesity
among children”).
Because obesity is associated with higher risks of chronic
illnesses, it is linked to significant additional health care
costs. There is a time lag between the onset of obesity and
related health problems, suggesting that the rise in obesity
over the past two decades will mean higher health care
costs in the future. A recent study estimated that total
costs linked to overweight and obesity in England in 2015
could increase by as much as 70% relative to 2007 and could
be 2.4 times higher in 2025 (Foresight, 2007).
Definition and comparability
Overweight and obesity are defined as excessive
weight presenting health risks because of the high
proportion of body fat. The most frequently used
measure is based on the body mass index (BMI), which
is a single number that evaluates an individual’s
weight in relation to height (weight/height2 , with
weight in kilograms and height in metres). Based on
the WHO classification (WHO, 2000), adults with a BMI
from 25 to 30 are defined as overweight, and those
with a BMI of 30 or over as obese. This classification
may not be suitable for all ethnic groups, who may
have equivalent levels of risk at lower or higher BMI.
The thresholds for adults are not suitable to measure
overweight and obesity among children.
For most countries, overweight and obesity rates are
self-reported through estimates of height and weight
from population-based health interview surveys.
However, around one-third of OECD countries derive
their estimates from health examinations. These
differences limit data comparability. Estimates from
health examinations are generally higher, and are
more reliable than estimates from health interviews.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.3. Overweight and obesity among adults
2.3.1 Prevalence of obesity among adults, 2009 (or nearest year)
Measured data
Self-reported data
Females
8.1
10.0
10.3
11.2
11.2
11.8
12.4
12.5
13.4
13.8
13.8
13.9
14.7
15.2
15.4
16.0
16.4
16.9
16.9
17.0
18.0
18.1
18.1
19.5
20.1
20.1
20.2
22.1
23.0
23.0
24.2
24.6
25.1
26.5
30.0
33.8
40
30
% of adult population
20
2.8
1.3
3.6
1.1
3.4
2.4
4.1
3.6
3.5
4.3
7.7
8.6
8.0
11.0
9.3
11.3
10.7
11.7
11.5
10.9
12.4
11.2
12.7
12.0
12.5
12.6
13.1
13.7
14.4
13.2
14.4
13.1
14.0
13.7
13.8
15.7
18.5
12.3
16.1
14.6
14.7
17.3
15.8
17.0
17.2
16.6
16.7
17.1
17.0
18.0
18.3
17.5
8.8
18.5
17.7
18.3
20.8
11.8
16.0
21.3
18.9
21.1
19.3
19.0
24.5
24.0
22.0
23.9
22.1
23.2
25.2
23.6
25.5
19.2
26.0
24.2
32.2
India
Indonesia
China
Korea
Japan
Switzerland
Norway
Italy
Sweden
France
Netherlands
Austria
Poland
Denmark
Israel
Belgium
Brazil
Germany
Turkey
Portugal
Spain
Slovenia
OECD
Slovak Republic
Czech Republic
Estonia
South Africa
Greece
Hungary
Russian Federation
Iceland
Finland
Luxembourg
Ireland
United Kingdom
Canada
Australia
Chile
New Zealand
Mexico
United States
2.1
2.4
2.9
3.8
3.9
10
Males
0
0
10
27.4
30.7
27.0
34.5
35.5
20
30
40
% of adult population
Source: OECD Health Data 2011; national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932523956
2.3.2 Increasing obesity rates among the adult population in OECD countries, 1990, 2000 and 2009 (or nearest years)
1990
2000
2009
30
31
34
%
40
23
24
25
25
25
23
22
22
21
16
19
20
18
20
17
14
11
12
13
17
7
8
8
9
11
13
14
17
16
11
13
14
15
15
13
15
15
11
12
14
13
14
13
12
12
9
9
10
12
11
9
6
6
6
6
9
10
9
10
9
2
3
3
4
4
5
6
8
8
10
11
20
27
30
i te
d
St
at
es 1
o1
ic
d1
ex
Un
an
al
M
il e 1
Ch
Ze
w
Ne
li a 1
ra
st
Au
Ki
ng
do
m1
g1
ur
bo
d
i te
Un
Lu
xe
m
Ic
el
an
d
y
ng
ar
ic
pu
Re
Hu
bl
15
CD
Cz
ec
h
OE
na
da
n
Sp
Ca
ai
l
Po
r tu
ga
nd
Ir e
la
d
y
an
an
nl
Fi
rm
el
Is
ra
Ge
lg
iu
m
k
ar
nm
Be
ria
Au
De
st
s
er
la
nd
en
ed
Sw
th
Ne
Fr
an
ce
ly
It a
ay
rw
nd
la
er
No
it z
pa
Sw
Ja
Ko
re
a1
n1
0
1. Data are based on measurements rather than self-reported height and weight.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932523975
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
55
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.4. Overweight and obesity among children
Children who are overweight or obese are at greater risk of
poor health, both in adolescence and in adulthood. Being
overweight in childhood increases the risk of developing
cardiovascular disease or diabetes, as well as related social
and mental health problems. Excess weight problems in
childhood are associated with an increased risk of being an
obese adult, at which point certain forms of cardiovascular
diseases, cancer, osteoarthritis, a reduced quality of life
and premature death can be added to the list of health
concerns (Sassi, 2010).
with excess weight problems, not only across countries, but
also according to their age. In general, older children have
more excess weight than younger children.
Evidence suggests that even if excess childhood weight is
lost, adults who were obese children retain an increased
risk of cardiovascular problems. And although dieting or
increased physical activity can combat obesity, children are
at a greater risk of again putting on weight when they
revert to previous lifestyles. In addition, dieting may lead
to eating disorders, symptoms of stress and postponed
physical development.
Childhood is an important period for forming healthy
behaviours. The school environment provides an opportunity to ensure that children understand the importance of
good nutrition and physical activity, and can benefit from
both. Studies show that locally focussed actions and interventions, especially those targeting 5-12 year-olds, can be
effective in changing behaviours (Sassi, 2010).
Figure 2.4.1 shows estimates by the International Association for the Study of Obesity of the prevalence of overweight (including obesity) in OECD and emerging countries
among school-aged children aged 5-17 years, based on
latest available national studies which measure height and
weight, and using IASO definitions of overweight/obesity.
One-in-five children are affected by excess body weight
across all countries, and in Greece, the United States and
Italy the figure is closer to one third. Only in China, Korea
and Turkey are 10% or less of children overweight. In most
countries, boys have higher rates of overweight and obesity
than do girls. Girls tend to have higher rates in Nordic
countries (Sweden, Norway, Denmark), as well as in the
United Kingdom, the Netherlands and Australia.
Many countries recognise the need for standardised and
harmonised surveillance systems on which to base policy
development to address overweight and obesity among
children. In response to this need, the WHO European
Childhood Obesity Surveillance Initiative (COSI) aims to
routinely measure trends in overweight and obesity in
primary-school children. Figure 2.4.2 presents the proportion of overweight (including obese) for 6- to 9-year-old
children, as measured during the first COSI data collection
round undertaken in 2007-08. Prevalence estimates were
based on the 2007 WHO recommended growth reference
for school-aged children and adolescents (de Onis et al.,
2007). There are important differences among children
56
Rates of overweight among boys and girls are increasing
across the OECD. In many developed countries, child
obesity levels doubled between the 1960s and 1980s, and
have doubled again since then. Even in emerging countries,
the prevalence of obesity is rising, especially in urban areas
where there is more sedentary behaviour and a greater
access to energy-dense foods (Sassi, 2010).
Definition and comparability
Estimates of the prevalence of child overweight were
made by the International Association for the Study of
Obesity (IASO). The estimates are based on national
surveys of measured height and weight among
children. Definitions of overweight and obesity among
children may sometimes vary among countries,
although wherever possible IASO age- and sex-specific
cut-off points were used (Cole et al., 2000). Calculated
for ages 2 to 18, these cut-off points can be used for
different ethnicities, and also link to widely-used adult
cut-off points.
For the WHO European Childhood Obesity Surveillance
Initiative (COSI), trained examiners took anthropometric measurements which were standardised
according to a common protocol. Overweight was
defined as the proportion of children with BMI-for-age
values greater than one standard deviation, based on
WHO recommended cut-offs for school-age children
and adolescents (de Onis et al., 2007). Body weight was
adjusted for the clothes worn when measured, and
extreme values (less than or greater than five standard
deviations) were excluded from calculations.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
2. NON-MEDICAL DETERMINANTS OF HEALTH
2.4. Overweight and obesity among children
2.4.1 Children aged 5-17 years who are overweight (including obese), latest available estimates
Girls
Boys
Greece
United States
Italy
Mexico
New Zealand
Chile
United Kingdom
Canada
Hungary
Iceland
Slovenia
Australia
Spain
Portugal
OECD
Brazil
Russian Federation
Sweden
Finland
India
Netherlands
South Africa
Germany
Czech Republic
Slovak Republic
Denmark
France
Norway
Japan
Switzerland
Poland
Turkey
Korea
China
37.0
35.9
30.9
29.0
28.8
27.1
26.6
26.1
25.9
25.5
24.4
24.0
22.9
21.6
21.4
21.1
19.8
19.5
19.1
18.3
17.9
17.7
17.6
16.9
16.2
15.2
14.9
14.7
14.4
13.1
12.4
10.3
9.9
4.5
50
40
30
% of children aged 5-17 years
20
10
0
45.0
35.0
32.4
28.1
28.2
28.6
22.7
28.9
25.5
22.0
28.7
22.0
32.9
23.5
22.9
23.1
24.2
17.0
23.6
20.6
14.7
13.6
22.6
24.6
17.5
14.1
13.1
12.9
16.2
16.7
16.3
11.3
16.2
5.9
0
10
20
30
40
50
% of children aged 5-17 years
Source: International Association for the Study of Obesity (2011).
1 2 http://dx.doi.org/10.1787/888932523994
2.4.2 Prevalence of overweight (including obesity) among 6- to 9-year-old children in eight OECD countries, 2007-08
Age 6
%
50
Age 7
Age 8
Age 9
46
44
40
38
34
27
24
20
30
29
30
22
19
26
25
23
23
21
10
0
Belgium
Czech Republic
Ireland
Italy
Norway
Portugal
Slovenia
Sweden
Source: WHO Regional Office for Europe, forthcoming.
1 2 http://dx.doi.org/10.1787/888932524013
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
57
3. HEALTH WORKFORCE
3.1. Employment in the health and social sectors
3.2. Medical doctors
3.3. Medical graduates
3.4. Remuneration of doctors (general practitioners and specialists)
3.5. Gynaecologists and obstetricians, and midwives
3.6. Psychiatrists
3.7. Nurses
3.8. Nursing graduates
3.9. Remuneration of nurses
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
59
3. HEALTH WORKFORCE
3.1. Employment in the health and social sectors
The health and social sectors employ a large and growing
number of people in OECD countries. The data reported in
this section come from general labour force surveys and
include not only people working in the health sector but
also those working in the social sector (including long-term
care, child care and other types of social work). The data
include professionals providing direct services to people
together with administrative and other support staff.
On average across OECD countries, employment in the
health and social sectors accounted for just over 10% of
total employment in 2009, an increase from less than 9%
in 1995. The share of people working in the health and
social sectors in 2009 was highest in Nordic countries and
the Netherlands, accounting for over 15% of total employment. It was the lowest in Turkey and Mexico at about 3%
(Figure 3.1.1).
The share of people employed in the health and social sectors
has increased in nearly all OECD countries between 1995
and 2009 (Figure 3.1.1). Exceptions were found in Poland, the
Slovak Republic, Sweden and Iceland, where the share of
health and social sector employment in total employment
declined in recent years.
Between 1995 and 2009, the workforce in the health and
social sectors grew by 2.8% per year on average across
OECD countries, two times faster than the growth rate of
1.3% in total civilian employment (Figure 3.1.2). In Korea,
the number of people working in the health and social
sectors increased at an average rate of over 8% per year
during that period, compared with a growth rate in total
employment of 1.1%. Nonetheless, the share of employment in the health and social sectors in Korea remains low
compared with most other OECD countries.
In Japan, Germany, the Czech Republic and Turkey, the
employment growth rate in the health and social sectors
has also exceeded by a wide margin the growth rate in total
employment in recent years.
60
Across the OECD, the recent economic crisis has hit the
health and social sectors much less than other parts of the
economy. In most countries, employment in the health and
social sectors continued to increase in 2008 and 2009, at a
time when total civilian employment remained flat or
started to decline as economies entered into recession. In
Ireland, for instance, employment in the health and social
sectors grew by 3% from 2008 to 2009 while total employment fell by 8%. Similarly, in Japan, overall employment fell
by 1.6% between 2008 and 2009 whereas employment in
the health and social sectors grew by almost 4%.
Definition and comparability
Employment in the health and social sectors includes
people working in the following groups of the International Standard Industrial Classification (ISIC) Rev. 3:
851 (Human health activities), 852 (Veterinary activities) and 853 (Social work activities). The data are
based on head counts, not taking into account
whether people are working full-time or part-time.
Data for all countries come from labour force surveys,
so as to achieve greater comparability. In many
countries, more specific surveys of health facilities or
health professionals can also provide more specific
data on employment in the health sector and for
specific occupations. Such data sources are used to
provide more detailed information for some of the
more specific health occupations presented in the
following sections.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.1. Employment in the health and social sectors
3.1.1 Employment in the health and social sectors as a share of total civilian employment,
1995 and 2009 (or nearest year)
1995
%
20
2009
20.0
18.4
15.9
15.7
15
15.2
14.6
13.2
12.9
12.5
12.0
11.9
11.8
11.6
11.1
10.4
10
10.1
9.9
9.7
9.5
7.6
7.3
6.8
6.5
6.3
6.3
5.9
5.7
5.3
5
3.6
3.1
2.8
X
LU
IT
A
CZ
E
HU
N
SV
K
ES
P
PO
L ( PR
20
T
00
-0
7)
GR
C
KO
R
TU
M
R
(2 E X
00
009
)
A
T
FR
AU
(2
00 R
308
)
IR
L
DE
U
CH
E
CA
N
AU
S
NZ
L
JP
N OEC
(2
00 D
309
)
L
US
A
GB
L
IS
NO
BE
R
DN
K
SW
N
E
(2 LD
00
308
)
FI
N
0
Source: OECD Annual Labour Force Statistics.
1 2 http://dx.doi.org/10.1787/888932524032
3.1.2 Employment growth rate in the health and social sectors compared with all sectors in the economy,
1995 to 2009 (or nearest year)
Total civilian
Health and social
Average annual growth rate (%)
9
8.1
5.9
6
5.5
5.4
3.9
3.7
3.6
3.6
3.4
3.3
3
3.3
3.1
2.8
2.7
2.6
2.5
2.5
2.5
2.5
2.2
2.2
2.1
2.0
1.7
1.6
1.4
1.2
1.0
0.7
0.5
0
-1.1
K
C
20 ZE
03
-0
8)
SV
K
PO
L ( HU
20 N
00
-0
7)
E(
A
L
IS
FR
DN
SW
JP
N
NZ
(2
00 L
309
)
AU
S
BE
L
GR
C
PR
T
NL
D
OE
CD
TU
C
R
( 2 HE
00
009
)
NO
R
AU
T
CA
N
DE
U
GB
R
US
A
I
T
(2
00 A
308
)
FI
N
P
X
EX
M
ES
LU
L
IR
KO
R
-3
Source: OECD Annual Labour Force Statistics.
1 2 http://dx.doi.org/10.1787/888932524051
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
61
3. HEALTH WORKFORCE
3.2. Medical doctors
This section provides information on the number of
doctors per capita in OECD countries, including a disaggregation by general practitioners and specialists. In 2009,
there were just over three doctors per 1 000 population
across OECD countries. Greece had by far the highest
number of doctors per capita (6.1 per 1 000 population),
followed by Austria. Chile, Turkey, Korea and Mexico had
the lowest number of doctors per capita with between one
and two doctors per 1 000 population. The number of
doctors per capita is lower in some of the major emerging
economies, with less than one doctor per 1 000 population
in Indonesia, India and South Africa.
Between 2000 and 2009, the ratio of physicians per
1 000 population has grown in most OECD countries, at a
rate of 1.7% per year on average (Figure 3.2.1). The growth
rate was particularly rapid in countries which started with
lower levels in 2000 (Turkey, Chile, Korea and Mexico) as
well as in the United Kingdom and Greece. In the United
Kingdom, graduation rates from medical education
programmes have been above the OECD average during that
period, resulting in high and rising numbers of doctors (see
Indicator 3.3 “Medical graduates”). On the other hand, there
was no growth in the number of physicians per capita in
Estonia, France, Israel and Poland, while there was a marked
decline in the Slovak Republic. This decline in the Slovak
Republic can be explained at least partly by a reduction in
the number of medical graduates since the late 1990s. In
France, following the reduction in the number of new
entrants into medical schools during the 1980s and 1990s,
the number of doctors per capita began to decline
since 2006. Due to the time it takes to increase graduate
numbers, this downward trend is expected to continue.
In 2009, 43% of doctors on average across OECD countries
were women, up from 29% in 1990. This ranged from highs
of more than half in central and eastern European
countries (Estonia, Slovenia, Poland, the Slovak Republic,
the Czech Republic, and Hungary) and Finland, to lows of
less than 20% in Korea. The share of female physicians
increased in all OECD countries over this time period with
particularly large increases in the United States, Spain and
Denmark.
The age composition of the physician workforce is one of
the factors contributing to concerns about potential shortages in several countries. In 2009, on average across OECD
countries, about 30% of all doctors were over 55 years of
age. However, this share varies considerably across countries. Israel has the highest share of physicians above the
age of 55 with 46%, whereas more than 35% of all doctors in
Chile, France, Germany, Hungary and Italy are over 55. In
the United Kingdom and Korea, a much lower proportion of
physicians are aged over 55, due to large numbers of new
graduates entering medical practice in the last decade.
The balance in the physician workforce between general
practitioners and specialists has changed over the past few
decades, with the number of specialists increasing much
more rapidly. Although health policy and health research
emphasises the importance and cost-effectiveness of
generalist primary care (Starfield et al., 2005), on average
62
across OECD countries, general practitioners made up only a
quarter of all physicians. There were more than two
specialists for every general practitioner in 2009, while this
ratio was one-and-a-half in 1990. Specialists greatly
out-number generalists in central and eastern European
countries and in Greece. However, some countries have
maintained a more equal balance between specialists and
generalists, such as Australia, Canada, France, and Portugal,
where generalists made up nearly half of all doctors. In
some countries, for example in the United States, general
internal medicine doctors are categorised as specialists
although their practice can be very similar to that of general
practitioners, resulting in some underestimation of the
capacity of these countries to provide generalist care
(Figure 3.2.2).
Forecasting the future supply and demand of doctors is
difficult, because of uncertainties concerning overall
economic growth, changes in physician productivity,
advances in medical technologies, changing roles of physicians versus other care providers, as well as changes in the
health needs of the population. In the United States, the
Department for Health and Human Services (HRSA, 2008)
has estimated that the demand for physicians might
increase by 22% between 2005 and 2020 while the supply
might only increase by 16.5% under a certain set of
assumptions. These projections did not take into account
the expansion of health insurance coverage under the 2010
healthcare reform proposal.
Definition and comparability
The data for most countries refer to practising medical
doctors, defined as the number of doctors who are
providing care directly to patients. In many countries,
the numbers include interns and residents (doctors in
training). The numbers are based on head counts.
Several countries also include doctors who are active
in the health sector even though they may not provide
direct care to patients. The data from Ireland include
all doctors with addresses in Ireland under the age of
70. Portugal reports the number of physicians entitled
to practice (resulting in an over-estimation). Data for
Spain include dentists and stomatologists, while data
for Belgium include stomatologists (also resulting in a
slight over-estimation). Data for Chile include only
doctors working in the public sector.
Not all countries are able to report all their physicians
in the categories of specialists and generalists. For
example, specialty-specific data may not be available
for doctors in training or for those working in private
practice.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.2. Medical doctors
3.2.1 Practising doctors per 1 000 population, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Greece 1
Austria
Russian Federation
Norway
Portugal 2
Switzerland
Iceland1
Sweden
Czech Republic
Germany
Spain
Denmark
Israel
Italy
Estonia
France 1
Ireland1
OECD
Australia
Hungary
Slovak Republic
Belgium
Netherlands1
Finland
Luxembourg
United Kingdom
New Zealand
Canada1
Slovenia
United States
Japan
Poland
Mexico
Korea
Brazil
Turkey1
China
Chile 3
India
South Africa
Indonesia
6.1
4.7
4.3
4.0
3.8
3.8
3.7
3.7
3.6
3.6
3.5
3.4
3.4
3.4
3.3
3.3
3.1
3.1
3.0
3.0
3.0
2.9
2.9
2.7
2.7
2.7
2.6
2.4
2.4
2.4
2.2
2.2
2.0
1.9
1.8
1.6
1.4
1.0
0.7
0.7
0.2
8
6
Per 1 000 population
4
2
0
4.0
2.1
0.4
1.8
1.9
n.a.
0.9
2.2
0.6
1.0
0.7
2.0
0.0
n.a.
0.0
0.0
n.a.
1.7
2.3
n.a.
-0.9
0.4
2.4
1.0
2.8
3.4
1.9
1.5
1.0
0.5
1.8
0.0
2.5
4.3
3.2
5.4
n.a.
4.6
3.8
n.a.
0.0
-2
0
2
4
6
Average annual growth rate (%)
1. Data include not only doctors providing direct care to patients, but also those working in the health sector as managers, educators, researchers, etc.
(adding another 5-10% of doctors).
2. Data refer to all doctors who are licensed to practice.
3. Data for Chile include only doctors working in the public sector.
Source: OECD Health Data 2011; WHO-Europe for the Russian Federation and national sources for other non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932524070
3.2.2 General practitioners, specialists and other doctors as a share of total doctors, 2009 (or nearest year)
Specialists1
GPs
Other physicians 2
9.5
13.5
4.5
56.1
62.3
11.7
77.1
65.0
12.3
62.0
15.8
13.8
16.7
18.0
23.2
61.4
15.9
50.2
56.9
85.4
76.9
19.7
19.6
20.1
20.3
22.7
l
Ko
r
Be ea
lg
iu
m
M
ex
ic
Au o
st
ri
F a
N e inl a
w
n
Ze d
al
an
Un
d
ite Tur
d
k
K i ey
n
Lu gd
xe om
m
bo
ur
g
OE
CD
E
Ne s to
th ni a
er
la
nd
s
It a
Sl l y
ov
en
ia
Is
ra
Cz
N el
e c or w
h
Re ay
pu
b
De li c
nm
Ge ar k
rm
an
Sw y
ed
e
Ic n
S w ela
nd
i
Sl
ov t z er
ak lan
Re d
pu
bl
ic
U n Ir e
l
a
i te
nd
d
St
at
Hu e s
ng
ar
Po y
la
n
Gr d
ee
ce
ga
r tu
Po
20.7
47.4
da
na
Ca
an
Fr
Au
st
ra
li a
0
24.9
49.0
ce
49.8
40
20
40.3
38.4
62.1
75.7
71.1
45.9
61.4
25.1
68.4
29.3
57.7
66.1
29.8
25.9
63.7
53.2
32.0
46.3
33.1
63.4
36.7
32.0
59.7
38.9
48.8
55.7
60
33.2
46.5
46.0
41.9
46.9
47.9
80
51.2
100
1. Specialists include paediatricians, obstetricians/gynaecologists, psychiatrists, medical specialists and surgical specialists.
2. Other doctors include interns/residents if not reported in the field in which they are training, and doctors not elsewhere classified.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524089
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
63
3. HEALTH WORKFORCE
3.3. Medical graduates
Maintaining or increasing the number of doctors requires
either investment in training new doctors or recruiting
trained physicians from abroad. As it takes about ten years
to train a doctor, any current shortages can be met only by
recruiting qualified doctors from abroad, unless there are
unemployed doctors at home. Conversely, any surpluses or
sudden fall in demand may mean that new graduates, in
particular, struggle to find vacant posts at home.
Virtually all OECD countries exercise some form of control
over medical school intakes, often by limiting the number
of available training places, for example in the form of a
numerus clausus. Such control is motivated by different
factors including: i) confining medical entry to the most
able applicants; ii) the desire to control the total number of
doctors for cost-containment reasons (because greater
supply induces greater demand); and iii) the cost of training
itself (in all countries, including the United States, a significant part of medical education costs are publicly funded,
so expansion of the number of medical students involves
significant public expenditure).
Austria, Ireland, Denmark and Greece had the highest
number of medical graduates per 100 000 population in 2009.
In countries such as Ireland and the Czech Republic, a large
share of graduates is made up of foreign students who may
return home upon graduation. Graduation rates were the
lowest in Israel, France, Japan and the United States. The
average across OECD countries was close to ten new medical
graduates per 100 000 population (Figure 3.3.1).
Measured in proportion to the stock of physicians (i.e. a
measure of the replacement rate), the number of new
medical graduates in 2009 was also the highest in Ireland
and Austria, along with Chile and Korea (which still have,
however, a very low number of doctors per capita). It was the
lowest in Israel, France and Spain. The average across OECD
countries was 32.5 medical graduates per 1 000 currently
employed doctors (Figure 3.3.2).
In several countries (e.g. Canada, Denmark and the United
Kingdom), the number of medical graduates has risen
strongly since 2000. In some other countries (e.g. Sweden),
the rise has been more recent. The increased intake in
these countries follow periods of stable or declining graduation numbers in the preceding years, reflecting deliberate
changes in policies to train more doctors (Figure 3.3.3). In
Germany, although the numbers of medical graduates had
started to increase in the past few years, the previous
decline will take time to reverse. Due to current concerns
about a shortage of doctors, Germany has liberalised its
labour market access for doctors from non-EU countries
in 2011.
64
In Italy and France, there was a marked decline in the
number of medical graduates between the mid-1980s and
the mid-1990s, after which it continued to fall but at a
slower rate in the case of France, and stabilised in the case
of Italy. The fall in medical graduate numbers in the past
has had an impact on the age distribution of the physician
workforce; Italy and France are among the OECD countries
with the highest proportion of doctors above the age
55 years. Even with an increase in the number of medical
school admissions in recent years, the number of doctors
leaving the profession will exceed the number of new
entrants during this decade. Israel has the highest share of
doctors above age 55 among OECD countries, and the
lowest replacement rate.
Japan has one of the lowest physician densities among OECD
countries. Following a decline of medical school intakes
from 8 280 students to 7 625 between 1981 and 2007, admissions to medical faculties increased to 8 923 students
in 2011 (MEXT, 2010). Japan also uses medical intake regulation to address geographical inequalities in the distribution
of physicians. The quotas of medical departments in
underserved regions were expanded, and students who
committed to working in underserved areas were given
preference in admission (MHLW, 2007).
Definition and comparability
Medical graduates are defined as the number of
students who have graduated from medical schools
or similar institutions in a given year. Dental, public
health and epidemiology graduates are excluded.
The data for the United Kingdom exclude foreign
graduates, while other countries include them
(foreign graduates account for about 30% of all
medical graduates in the Czech Republic). In
Denmark, the data refer to the number of new doctors
receiving an authorisation to practice.
In Luxembourg, the university does not provide
medical training, so all doctors are foreign-trained,
mostly in Belgium, France and Germany.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.3. Medical graduates
3.3.1 Medical graduates per 100 000 population,
2009 (or nearest year)
Austria
Ireland
Denmark
Greece
Czech Republic
Germany
Iceland
Italy
Australia
Norway
Sweden
Portugal
Netherlands
OECD
Finland
Switzerland
United Kingdom
Hungary
Estonia
Korea
Slovak Republic
Spain
Slovenia
Belgium
New Zealand
Poland
Canada
Turkey
Chile
United States
France
Japan
Israel
3.3.2 Medical graduates per 1 000 physicians,
2009 (or nearest year)
Ireland
Austria
Chile
Korea
Denmark
Turkey
Finland
Australia
Netherlands
Czech Republic
United Kingdom
Germany
Poland
Slovak Republic
Slovenia
OECD
Iceland
New Zealand
Hungary
Canada
Portugal
Sweden
Estonia
Italy
Japan
Belgium
United States
Norway
Greece
Switzerland
Spain
France
Israel
23.6
16.2
15.3
14.3
12.6
12.5
11.6
11.3
10.8
10.7
10.7
10.4
9.9
9.9
9.4
9.4
9.3
9.2
9.0
8.8
8.5
8.5
8.0
7.9
7.8
7.3
7.0
7.0
6.5
6.5
6.0
5.9
4.0
0
5
10
15
20
25
Per 100 000 population
Source: OECD Health Data 2011.
52.8
51.4
47.4
45.5
42.9
42.9
37.8
37.3
36.4
35.3
34.5
34.3
33.7
33.0
33.0
32.5
31.7
30.3
29.8
29.7
28.3
27.5
27.4
27.1
27.0
26.9
26.7
26.6
25.7
24.1
23.9
18.2
11.6
0
10
20
30
40
50
60
Per 1 000 physicians
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524108
1 2 http://dx.doi.org/10.1787/888932524127
3.3.3 Absolute number of medical graduates, selected OECD countries, 1980 to 2010
France
Germany
Canada
Denmark
Italy
Japan
Finland
Norway
United Kingdom
United States
Sweden
Number of graduates
Number of graduates
2 500
20 000
2 000
16 000
1 500
12 000
8 000
1 000
4 000
500
0
1980
1985
1990
1995
2000
2005
2010
0
1980
1985
1990
1995
2000
2005
2010
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524146
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
65
3. HEALTH WORKFORCE
3.4. Remuneration of doctors (general practitioners and specialists)
The remuneration level of doctors is, to a certain extent,
related to the overall level of economic development of a
country, but there are nevertheless significant variations in
their remuneration compared with the average wage in
each country. The structure of remuneration for different
categories of doctors also has an impact on the financial
attractiveness of different medical specialties. In many
countries, governments influence the level and structure of
physician remuneration directly as a key employer of
physicians or as a purchaser of services, or indirectly
through regulation.
practice. The remuneration of specialists has risen faster
than that of general practitioners in countries such as
Finland, France and Ireland. On the other hand, in the
Netherlands, the gap has narrowed slightly, as the income
of GPs grew faster than that of specialists (Figure 3.4.2).
OECD data on physician remuneration distinguishes
between salaried and self-employed physicians, although
in some countries this distinction is increasingly blurred,
as some salaried physicians are allowed to have a separate
practice and some self-employed doctors may receive part
of their remuneration through salaries. A distinction is also
made between general practitioners and all other medical
specialists combined, though there may be wide differences in the income of different medical specialties.
Definition and comparability
As expected for highly-skilled professionals, the remuneration of doctors (both generalists and specialists) is much
higher than that of the average worker in all OECD countries (Figure 3.4.1). Self-employed general practitioners in
Australia earned 1.7 times the average wage in 2008,
whereas in Germany, self-employed GPs earned 3.7 times
the average wage in 2007. In the United Kingdom, selfemployed GPs earned 3.6 times the average wage in 2008.
The income of self-employed GPs in the United Kingdom
rose strongly following the implementation of a new
contract for generalists in 2004 that was designed to
increase their income as well as quality of primary care
(Fujisawa and Lafortune, 2008).
A number of data limitations contribute to an underestimation of remuneration levels in some countries:
1) payments for overtime work, bonuses, other supplementary income or social security contributions
are excluded in some countries (Austria, Ireland for
salaried specialists, Italy, New Zealand, Norway,
Portugal, the Slovak Republic, Slovenia and Sweden);
2) incomes from private practices for salaried doctors
are not included in some countries (e.g. the Czech
Republic, Hungary, Iceland and Portugal); 3) informal
payments, which may be common in certain countries (e.g. Hungary and Greece), are not included; 4) in
Hungary, Mexico, Denmark and the Slovak Republic,
data relate only to public sector employees who tend
to earn less than those working in the private sector;
and 5) in France, the data relate to net income rather
than gross income.
The income of specialists varied from 1.6 times the average
wage for salaried specialists in Hungary to 5.5 times for
self-employed specialists in the Netherlands in 2007. In the
Czech Republic, salaried specialists earned 1.8 times the
average wage while self-employed specialists earned
almost two times more.
In all countries except the United Kingdom, GPs earn less
than all medical specialists combined. In Canada, selfemployed specialists earned 4.7 times the average wage
in 2008, compared with 3.1 times for GPs. In France, selfemployed specialists earned 3.2 times the average wage,
compared with 2.1 times for GPs (the income of both
specialists and GPs are underestimated in France – see
box on “Definition and comparability”). The income gap
between GPs and specialists is particularly large in
Australia, although it has narrowed slightly in recent years.
In many OECD countries, the income gap between general
practitioners and specialists has widened over the past
decade, reducing the financial attractiveness of general
66
The remuneration of doctors refers to average gross
annual income, including social security contributions and income taxes payable by the employee. It
should normally include all extra formal payments,
such as bonuses and payments for night shifts,
on-call and overtime, and exclude practice expenses
for self-employed doctors.
The data for some countries (Australia, Austria, the
Netherlands, the United States, and the United
Kingdom for specialists) include part-time workers,
while in other countries the data refer only to doctors
working full-time. In Ireland, the data for selfemployed GPs include practice expenses, resulting in
an over-estimation.
The income of doctors is compared to the average
wage of full-time employees in all sectors in the
country, except in Iceland, Mexico and New Zealand
where it is compared to the average wage in selected
industrial sectors.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.4. Remuneration of doctors (general practitioners and specialists)
3.4.1 Doctors’ remuneration, ratio to average wage, 2009 (or nearest year)
Specialists
General practitioners (GPs)
Salaried
Self-employed
Salaried
Australia
Austria
Canada
Czech Republic
Denmark1
Estonia
Finland
France 2
Germany
Greece
Hungary3
Iceland 4
Ireland 5
Italy
Mexico
Netherlands
New Zealand
Norway
Slovak Republic
Slovenia
Spain
Turkey
United Kingdom 6
4.3
4.4
4.7
1.8
3.3
4.0
2.1
2.6
3.2
5.0
2.8
1.6
2.8
4.5
2.6
4.6
2.9
5.5
3.6
1.8
n.a.
2.8
n.a.
3.8
2.6
6
4
Ratio to average wage in each country
1.
2.
3.
4.
5.
6.
2
0
Self-employed
1.7
2.7
3.1
n.a.
2.8
1.7
1.8
2.1
3.7
n.a.
1.4
3.0
3.5
n.a.
3.5
1.7
3.5
n.a.
n.a.
1.9
2.5
1.9
2.0
1.9
0
3.6
2
4
6
Ratio to average wage in each country
Data for self-employed specialists is for 2008.
Remuneration is net income rather than gross income resulting in an underestimation.
Data on salaried doctors relate only to public sector employees who tend to receive lower remuneration than those working in the private sector.
Many specialists working in hospitals also earn incomes from private practices which are not included.
Data for self-employed GPs include practice expenses resulting in an over-estimation.
Remuneration of GPs is for 2008.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524165
3.4.2 Growth in the remuneration of GPs and specialists, 2000-09 (or nearest year)
GPs
Specialists
Average annual growth rate (%, in real terms)
6
5.1
5
4.4
4.3
4
3.7
3.7
3
2.7
1.9
2
1
0.9
1.6
1.9
1.7
1.8
1.1
0.7
0.7
0.6
0.4
0
-0.3
-1
-1.0
-1.0
-2
-2.0
-2.1
s
la
er
Ne
th
M
ex
ic
nd
o
el
ra
Is
nd
la
Ir e
y
Hu
ng
ar
ce
Fr
an
d
an
nl
Fi
da
Ca
na
m
iu
lg
Be
ria
st
Au
Au
st
ra
li a
-3
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524184
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
67
3. HEALTH WORKFORCE
3.5. Gynaecologists and obstetricians, and midwives
Gynaecologists are concerned with the functions and
diseases specific to women, especially those affecting the
reproductive system, while obstetricians specialise in pregnancy and childbirth. A doctor will often specialise in both
these areas, and the data reported in this section does not
distinguish between the two. Midwives provide care and
advice to women during pregnancy, labour and childbirth
and the post-natal period. They deliver babies working
independently or in collaboration with doctors and nurses.
In countries with a medicalised approach to pregnancy,
obstetricians provide the majority of care. Where a less
medicalised approach exists, trained midwives are the lead
professional, often working in collaboration with other
health professionals such as general practitioners,
although obstetricians may be called upon if complications
arise. Regardless of the different mix of providers across
countries, the progress achieved over the past few decades
in the provision of pre-natal advice and pregnancy surveillance, together with progress in obstetrics to deal with
complicated births, has resulted in major reductions in
perinatal mortality in all OECD countries.
In 2009, the number of gynaecologists and obstetricians per
100 000 women was the highest in the Czech Republic,
Greece, Italy and the Slovak Republic (Figure 3.5.1). These
are all countries where obstetricians are given a primary
role in providing pre-natal and childbirth care. It was the
lowest in Ireland, New Zealand, Canada and Japan.
Since 2000, the number of gynaecologists and obstetricians
per 100 000 women has increased in most countries, with an
average growth rate of 1.5% per year during that period. The
number of gynaecologists and obstetricians has remained
relatively stable in Estonia and France, while it declined
significantly in Japan and Poland (Figure 3.5.1).
The number of midwives per 100 000 women was highest in
Australia, Iceland and Sweden in 2009 (Figure 3.5.2). Iceland
and Sweden have traditionally had a large number of
midwives assuming primary responsibility for pre-natal care
and normal delivery (Johanson, 2002). On the other hand, the
number of midwives per capita is the lowest in Canada,
Korea and Slovenia. While the number of midwives per
women has increased in Canada and Slovenia over the past
decade, it has fallen in Korea. This decline has coincided
with a continued reduction in fertility rates in Korea. In
Estonia and Hungary, the number of midwives per capita
also decreased between 2000 and 2009. In Hungary, most of
the reduction occurred between 2006 and 2007, as the
number of beds in maternity wards was cut by more than
one-third in the context of a health reform.
68
In the Netherlands, the number of midwives has been
growing faster than the number of gynaecologists and
obstetricians over the past decade and the number of births
in hospitals attended by midwives rose from 8% in 1998 to
26% in 2007 (Wiegers and Hukkelhoven, 2010).
The relative mix of providers has both direct and indirect
implications for the costs of pre-natal and natal services.
Services involving midwives are likely to be cheaper. This
reflects in part the lower training time and hence a lower
compensating pay for midwives in comparison to
gynaecologists and obstetricians. Additionally, obstetricians may be inclined to provide more medicalised
services. A study of nine European countries found that the
cost of delivery is lower in those countries and hospitals
that employ more midwives and nurses than obstetricians
(Bellanger and Or, 2008).
There is little evidence that systems that rely more on
midwives are less effective. A review of a number of studies
finds that midwife-led models of care resulted in fewer
complications (Hatem et al., 2008). Another review found
that midwives are equally effective in providing pre-natal
care and advice in the case of normal pregnancies (Di Mario
et al., 2005), although support from obstetricians is required
for complications.
Definition and comparability
The number of gynaecologists and obstetricians
combines these two specialities.
The figures for gynaecologists and obstetricians, and
for midwives, are presented as head counts, not
taking into account full-time or part-time status.
The number of midwives in Canada may be understated, as they may undercount the number of
personnel actively practicing midwifery in provinces/
territories where there is no regulation requiring licensure as a condition of practice. In Austria, the number
of midwives only includes those employed in hospital,
resulting in an under-estimation of 40 to 50%.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.5. Gynaecologists and obstetricians, and midwives
3.5.1 Gynaecologists and obstetricians per 100 000 females, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Czech Republic
Greece
Italy
Slovak Republic
Israel
Germany
Austria
Estonia
Switzerland
Mexico
Slovenia
Poland
Luxembourg
Sweden
Portugal
OECD
United States
Belgium
Hungary
France
Iceland
Norway
United Kingdom
Finland
Korea
Denmark
Turkey
Australia
Netherlands
Chile
Japan
Canada
New Zealand
Ireland
47.8
47.8
40.8
40.0
37.9
37.6
37.2
37.1
33.1
32.2
30.9
30.8
29.4
29.3
28.7
26.8
26.8
24.2
24.1
23.6
22.8
22.1
22.1
21.3
21.0
18.6
18.4
17.7
15.7
15.3
15.3
14.3
13.6
8.6
50
40
Per 100 000 females
30
20
10
0
1.0
1.6
n.a.
n.a.
-0.2
1.0
2.5
0.2
3.2
4.9
n.a.
-0.8
2.3
1.6
1.1
1.5
-0.1
1.2
n.a.
0.4
n.a.
2.4
3.2
n.a.
n.a.
1.0
n.a.
3.5
2.9
0.5
-0.8
1.4
1.6
n.a.
-2
0
2
4
6
Average annual growth rate (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524203
3.5.2 Midwives per 100 000 females, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Australia
Iceland
Sweden
Turkey
Poland
New Zealand
United Kingdom
Norway
Belgium
Czech Republic
Finland
Luxembourg
OECD
Slovak Republic
France
Switzerland
Italy
Denmark
Estonia
Chile
Greece
Germany
Israel
Japan
Hungary
Spain
Netherlands
Austria1
Slovenia
Korea
Canada
182.3
158.5
144.1
136.3
113.5
112.0
105.4
102.5
97.3
81.6
76.3
71.2
69.8
63.5
60.3
58.8
55.8
53.9
53.6
52.9
46.1
45.5
41.1
37.9
32.5
31.6
30.4
30.0
8.7
5.3
4.5
200
150
Per 100 000 females
100
50
0
3.6
0.9
0.8
n.a.
0.2
n.a.
1.3
1.0
n.a.
n.a.
4.0
n.a.
2.7
7.1
2.3
n.a.
1.1
1.8
-2.7
8.2
1.3
2.8
-1.1
2.1
-2.1
0.1
4.5
1.6
18.6
-1.8
8.7
-5
0
5
10
15
20
Average annual growth rate (%)
1. In Austria, the number of midwives only includes those employed in hospital.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524222
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
69
3. HEALTH WORKFORCE
3.6. Psychiatrists
At any point in time, about 10% of the adult population will
report having some type of mental or behavioural disorder
(WHO, 2001). People with mental health problems may
receive help from a variety of professionals, including
general practitioners, psychiatrists, psychologists, psychotherapists, social workers, specialist nurses and others.
This section focuses on one category of mental health
service provider, psychiatrists, as the availability of comparable data on others, such as psychologists, is more limited.
Psychiatrists are responsible for diagnosing and treating a
variety of serious mental health problems, including
depression, learning disabilities, alcoholism and drug
addiction, eating disorders, and personality disorders such
as schizophrenia.
In Europe, a population-based survey carried out in 2010
indicated that, on average across EU countries, 15% of the
population reported seeking help from a health professional for a psychological or emotional health problem over
the past year (Eurobarometer, 2010). Among the people
who sought help, almost three quarters (73%) had
consulted a general practitioner, while 11% sought help
from a psychiatrist and another 14% from a psychologist
(Figure 3.6.2).
In 2009, the number of psychiatrists in most OECD countries was between 10 and 20 per 100 000 population. The
number was by far the highest in Switzerland with 42 per
100 000 population, followed by several Nordic countries
(Iceland, Norway, Finland and Sweden) and France with
between 21 and 23 psychiatrists per 100 000 population. In
Mexico, Turkey, Chile, Korea and Poland, there were less
than 10 psychiatrists per 100 000 population (Figure 3.6.1).
The number of psychiatrists per capita has increased
since 2000 in most OECD countries for which data are available. Across these OECD countries, the average annual
growth rate was just over 2% between 2000 and 2009. The
rise has been particularly rapid in Poland, Switzerland,
Austria and the United Kingdom. There was a slight
decrease in the number of psychiatrists per capita during
this time period in Israel, France and the United States
(Figure 3.6.1).
As is the case for many other medical specialties, psychiatrists may be unevenly distributed across regions within
each country, with some regions being underserved. For
70
example, in Australia, the number of psychiatrists per
capita is 4.6 times greater in major cities than in remote
regions (AIHW, 2010a).
The role of psychiatrists varies across countries. For example,
in Spain, psychiatrists work in close co-operation with
general practitioners (GPs). Hence, although the number of
psychiatrists is relatively low, consultation rates of psychiatrists by people with mental disorders are higher than in
many other countries that have more psychiatrists, because
of higher referral rates from their GPs (Kovess-Masfety
et al., 2007).
The role of other mental health service providers such as
psychologists also varies across countries. For instance, in
the Netherlands, there is a high number of psychologists
who are very active in providing services that are covered
under health insurance systems. In other countries such as
France, the number of psychologists is lower and the
services that they provide are not covered under public
health insurance (Kovess-Masfety et al., 2007).
Definition and comparability
Psychiatrists are medical doctors who specialise in
the prevention, diagnosis and treatment of mental
illness. They have post-graduate training in psychiatry, and may also have additional training in a psychiatric specialty, such as neuropsychiatry or child
psychiatry. Psychiatrists can prescribe medication,
which psychologists cannot do in most countries.
The figures normally include psychiatrists, neuropsychiatrists and child psychiatrists. Psychologists
are excluded. The numbers are presented as head
counts, regardless of whether psychiatrists work
full-time or part-time.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.6. Psychiatrists
3.6.1 Psychiatrists per 100 000 population, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Switzerland
Iceland
Norway
France
Finland
Sweden
Netherlands
Germany
United Kingdom
Luxembourg
Italy
Israel
Belgium
Denmark
Greece
OECD
Canada
New Zealand
Australia
United States
Austria
Estonia
Ireland
Czech Republic
Hungary
Slovak Republic
Japan
Portugal
Slovenia
Poland
Korea
Chile
Turkey
Mexico
42.2
23.2
22.2
21.8
21.6
20.9
20.0
19.8
19.4
18.2
18.0
17.9
17.7
16.7
16.2
15.4
15.4
15.3
15.0
14.5
14.2
14.0
13.9
13.9
12.3
11.5
10.6
10.2
10.1
9.3
5.1
4.1
3.6
0.9
50
40
Per 100 000 population
30
20
10
0
4.9
n.a.
3.6
-0.5
n.a.
1.3
3.4
2.1
3.8
n.a.
n.a.
-0.7
0.9
2.5
n.a.
2.1
0.7
1.9
1.6
-0.2
4.0
1.4
n.a.
2.1
n.a.
n.a.
1.9
0.6
n.a.
6.6
n.a.
3.0
n.a.
n.a.
-3
0
3
6
9
Average annual growth rate (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524241
3.6.2 Type of provider(s) consulted for mental health problems, selected EU countries, 2010
General practitioner
%
100
92
92
Psychiatrist
Psychologist
90
90
81
81
80
78
76
75
75
73
73
71
71
71
70
71
67
67
67
64
61
60
57
53
50
40
38
30
24
20
17
14
10
8 8
8
10
17
10
6 6
5
11
17
13
12 12
8
11
14
14 14
12
17
12
8 8
7
7 7
22
21
18
11 11
14
8
24
21
14
11
6
E
SW
N
FI
D
NL
X
LU
N
SV
L
PO
U
DE
P
ES
T
ES
C
GR
E
CD
OE
CZ
N
HU
DN
K
A
FR
L
BE
T
PR
T
AU
K
SV
R
GB
L
IR
IT
A
0
0
Note: The question asked during the interview was: In the last 12 months, did you seek help from a professional because of a psychological or
emotional problem? If yes, indicate who in the provided list (multiple answers possible).
Source: Eurobarometer, February-March 2010.
1 2 http://dx.doi.org/10.1787/888932524260
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
71
3. HEALTH WORKFORCE
3.7. Nurses
Nurses are usually the most numerous health profession,
greatly outnumbering physicians in most OECD countries.
Nurses play a critical role in providing health care not only in
traditional settings such as hospitals and long-term care
institutions but increasingly in primary care (especially in
offering care to the chronically ill) and in home care settings.
However, there are concerns in many countries about
shortages of nurses, and these concerns may well intensify
in the future as the demand for nurses continues to increase
and the ageing of the “baby boom” generation precipitates a
wave of retirements among nurses. These concerns have
prompted actions in many countries to increase the training
of new nurses combined with efforts to increase the retention of nurses in the profession (OECD, 2008a).
On average across OECD countries, there were 8.4 nurses
per 1 000 population in 2009 (Figure 3.7.1). The number of
nurses per capita was highest in several Nordic countries,
with 14 to 15 nurses per 1 000 population. The number is
also high in Switzerland and Belgium, although the data for
Belgium relate to all nurses who are licensed to practice,
resulting in an overestimation. The number of nurses per
capita in OECD countries was lowest in Chile (although the
number is underestimated, because it only takes into
account nurses working in the public sector), as well as in
Turkey, Mexico and Greece. The number of nurses per
capita was also low compared with the OECD average in
major emerging economies, such as India, Brazil, Indonesia
and China, where there were fewer than 1.5 nurses per
1 000 population in 2009, although numbers have been
growing quite rapidly in Brazil and China in recent years
(Figure 3.7.1).
The number of nurses per capita increased in almost all
OECD countries over the past decade, at an average rate of
1.8% per year between 2000 and 2009. Chile saw the largest
increase among OECD countries, with an increase of 12% per
year, although the number of nurses per capita remains very
low. The number of nurses per capita also increased rapidly
in Portugal and Korea. In Israel, the number of nurses per
capita declined between 2000 and 2009. It also declined in
the Slovak Republic, although the recent increase in the
number of new nursing graduates may lead to an increase in
the coming years. In Australia and the Netherlands, the
number of nurses per capita declined between 2000
and 2007, but has risen since then.
In 2009, the nurse-to-doctor ratio ranged from five nurses
per doctor in Ireland to less than one nurse per doctor in
Chile, Greece and Turkey (Figure 3.7.2). The number of
nurses per doctor is also relatively low in Italy, Mexico,
Israel, Portugal and Spain. The average across OECD
countries is just below three nurses per doctor, with most
72
countries reporting between two to four nurses per doctor.
In Greece and Italy, there is evidence of an over-supply of
doctors and under-supply of nurses, resulting in an inefficient allocation of resources (OECD, 2009a; Chaloff, 2008).
In response to shortages of doctors and to ensure proper
access to care, some countries have developed more
advanced roles for nurses. Evaluations of nurse practitioners
from the United States, Canada and the United Kingdom
show that advanced practice nurses can improve access to
services and reduce waiting times, while delivering the
same quality of care as doctors for a range of patients,
including those with minor illnesses and those requiring
routine follow-up. Most evaluations find a high patient satisfaction rate, while the impact on cost is either cost-reducing
or cost-neutral. The implementation of new advanced
nursing roles may require changes to legislation and regulation to remove any barrier to extensions in their scope of
practice (Delamaire and Lafortune, 2010).
Definition and comparability
The number of nurses includes those employed in
public and private settings, including the selfemployed. In most countries, they refer specifically
to nurses providing services directly to patients
(“practising”) while other countries also include those
working as managers, educators or researchers.
In those countries where there are different levels of
nurses, the data include both “professional nurses”
who have a higher level of education and perform
higher level tasks and “associate professional nurses”
who have a lower level of education but are nonetheless recognised and registered as nurses.
Midwives, as well as nursing aids who are not recognised as nurses, are normally excluded. However,
about half of OECD countries include midwives
because they are considered as specialist nurses.
Austria reports only nurses working in hospitals,
resulting in an under-estimation. Chile reports only
nurses working in the public sector. Data for Germany
does not include about 250 000 nurses (representing
an additional 30% of nurses) who have three years of
education and are providing services for the elderly.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.7. Nurses
3.7.1 Practising nurses per 1 000 population, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Iceland1
Switzerland
Belgium 2
Denmark
Norway
Ireland1
Germany
Sweden
Luxembourg
United States1
New Zealand
Australia
United Kingdom
Finland
Japan
Canada
OECD
Netherlands
France 1
Czech Republic
Slovenia
Russian Federation
Austria 3
Italy2
Hungary
Estonia
Slovak Republic1
Portugal1
Poland
Spain
Israel
Korea
Greece 1
Mexico
South Africa
Turkey1
China
Indonesia
Brazil
India
Chile 4
15.3
15.2
14.8
14.8
14.2
12.7
11.0
11.0
10.9
10.8
10.5
10.2
9.7
9.6
9.5
9.4
8.4
8.4
8.2
8.1
8.1
8.1
7.6
6.4
6.2
6.1
6.0
5.6
5.2
4.9
4.5
4.5
3.3
2.5
2.2
1.5
1.4
1.4
0.9
0.9
0.5
20
15
Per 1 000 population
1.
2.
3.
4.
10
5
0
1.6
1.8
n.a.
2.2
2.3
0.5
1.5
1.3
n.a.
0.6
3.9
0.2
1.2
0.4
2.1
1.7
1.8
1.2
2.3
0.7
1.8
0.4
0.6
1.5
1.8
0.4
-2.3
4.7
0.4
3.5
-1.6
4.6
2.3
1.4
0.5
n.a.
8.8
n.a.
10.7
2.8
12.1
-5
0
5
10
15
Average annual growth rate (%)
Data include not only nurses providing direct care to patients, but also those working in the health sector as managers, educators, researchers, etc.
Data refer to all nurses who are licensed to practice.
Austria reports only nurses employed in hospitals.
Chile includes only nurses working in the public sector.
Source: OECD Health Data 2011; WHO-Europe for the Russian Federation and national sources for other non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932524279
3.7.2 Ratio of nurses to physicians, 2009 (or nearest year)
5
4
5.0 4.4 4.4
4.3 4.2
4.2 4.2 4.1
4.0 3.9
3.6 3.5 3.5
3.4 3.3
3
3.1 3.1 3.0
3.0
2.8
2.5 2.4
2.3 2.3
2
1
2.1
1.9 1.9 1.8
1.6
1.5 1.4
1.4 1.3
1.2
1.0 1.0
0.9
0.5 0.5 0.5
Ir e
la
C a nd 1
na
da
J 1
De apa
L u nm n
x
Un em ar k
i te bo
d ur
St g
at
e
N e Ic e s 1
w lan
Ze d
Sw al
i a
Ne t ze nd
Un th r l a
i te er l nd
d an
K i ds 1
ng
do
Fi m
nl
a
No nd
rw
Au a
st y
r
S a
S o lov li a
u t en
h ia
A
Be fric
lg a
G e ium 1
rm
S w any
ed
e
OE n
CD
Fr
an
Po c e
la
Cz
ec K nd
h or
Re e a
pu
Hu bli c
Ru
ng
ss
i a E ar y
n
s
Sl F e to
ov d ni
a k er a a
Re t io
pu n
bl
Au ic 1
st
Po r ia
r tu
ga
Sp l
a in
In
di
Is a
r
M ael
ex
ic
o
It a
ly 1
Ch
i
Tu na
rk
Gr e y
ee
c
Br e
az
i
Ch l
il e
0
1. For those countries which have not provided data for practising nurses and/or practising physicians, the numbers relate to the same concept
(“professionally active” or “licensed to practice”) for both nurses and physicians, for the sake of consistency.
Source: OECD Health Data 2011; WHO-Europe for the Russian Federation and national sources for other non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932524298
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
73
3. HEALTH WORKFORCE
3.8. Nursing graduates
Many OECD countries have taken steps in recent years to
expand the number of students in nursing education
programmes in response to concerns about current or
anticipated shortages of nurses. Increasing investment in
nursing education is particularly important as the nursing
workforce is ageing in many countries and the baby boom
generation of nurses approaches retirement.
In 2009, there were 39 newly graduated nurses per
100 000 population on average across OECD countries, up
from 36 in 2007 (Figure 3.8.1). The number was by far the
highest in the Slovak Republic, with 152 graduates per
100 000 population. Since 2006, the number of nursing
graduates in the Slovak Republic has more than doubled,
rising from 3 732 graduates in 2006 to over 8 000 in 2009.
Nurse graduation rates have traditionally been low in
Turkey, Chile, Greece and Italy, four countries which
report a relatively low number of nurses per capita. In
Luxembourg, nurse graduation rates are also low, but many
nurses are foreign-trained.
The institutional arrangements for nursing education
differ across OECD countries. In some countries, the
number of students admitted in nursing programmes is not
limited. This is the case in Belgium, Chile, the Netherlands,
Norway, New Zealand and the United States, although in
this latter case State decisions on public funding for
nursing education have a direct impact on the capacity of
nursing schools to admit students. In most countries,
however, entry into nursing programmes is regulated
(OECD, 2008a).
The expansion of nursing education is also visible in the
number of graduates per 1 000 practising nurses (Figure 3.8.2).
There were 58 nurse graduates per 1 000 employed nurses on
average in OECD countries in 2009, up from an average
of 42 in 2007. The number of new graduates per practising
nurses was highest in the Slovak Republic, Korea and Chile,
although in the latter two countries this is partly explained by
the relatively low number of nurses. The number of new
graduates per practising nurses is the lowest in Luxembourg,
which is compensated by the import of nurses trained in
other countries.
The number of nursing graduates has increased in many
OECD countries over the last decade. This has been the
case, for instance, in France where the number increased
by 60% between 2000 and 2009, and Switzerland where the
number went up by 27% over the same period (Figure 3.8.3).
74
In Italy, concerns about current and future shortages of
nurses have led to a significant increase in student intake in
university nursing programmes in recent years, resulting in
a rise in the number of newly-graduated nurses from less
than 6 000 in 2002 to almost 11 000 in 2009. Nonetheless,
this may not be sufficient to meet demand, given that the
number of nurses leaving the profession annually was estimated to be in the range of 13 000 to 17 000 (Chaloff, 2008).
In Japan, the number of nursing graduates declined slightly
between 2000 and 2006. However, this trend has been
reversed since 2006, and a growing number of graduates is
expected in the years ahead.
The impact of the expansion of nursing education on the
supply of nurses depends on other workforce policies as
well. Policy changes, such as efforts to retain nurses in the
workforce longer by offering them better pay and working
conditions may ensure that the investment in training a
larger number of nurses pays off (Buchan and Black, 2011).
Definition and comparability
Nursing graduates refer to the number of students who
have obtained a recognised qualification required to
become a licensed or registered nurse. They include
graduates from both higher level and lower level
nursing programmes.They exclude graduates from
Masters or PhD degrees in nursing to avoid doublecounting nurses acquiring further qualifications.
The numbers reported by Canada, Greece, Korea,
Slovenia and Sweden do not include graduates from
lower level nursing programmes, nor are graduates
from three-year education programmes focusing on
elderly care included in Germany, resulting in an
under-estimation in graduation rates per capita.
However, the calculation of graduation rates per
practising nurses includes the same categories of
nurses in the numerator and the denominator to
avoid any under-estimation. The United Kingdom
data excludes nursing graduates from overseas.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.8. Nursing graduates
3.8.1 Nursing graduates per 100 000 population,
2009 (or nearest year)
Slovak Republic
Denmark
Australia
Norway
Switzerland
Iceland
Austria
Finland
Sweden1
Netherlands
OECD
Belgium
Japan
Estonia
France
Ireland
Portugal
Hungary
New Zealand
United Kingdom
Korea1
Canada1
Germany
Poland
Slovenia1
Spain
Italy
Luxembourg
Czech Republic
Greece 1
Israel
Chile
Turkey
3.8.2 Nursing graduates per 1 000 nurses,
2009 (or nearest year)
152.0
78.3
75.9
72.2
67.8
64.8
58.7
57.6
42.5
39.3
39.1
37.1
36.8
35.2
34.4
33.1
32.9
31.5
30.6
30.0
29.2
29.0
27.5
22.1
22.0
20.6
18.4
18.0
13.9
13.8
11.4
7.5
6.0
0
40
80
Slovak Republic
Korea
Chile
Slovenia
Greece
Austria
Australia
Portugal
Finland
OECD
Estonia
Denmark
Hungary
Norway
Netherlands
Switzerland
Iceland
Poland
France
Spain
Turkey
Sweden
Canada
Japan
United Kingdom
New Zealand
Italy1
Ireland
Israel
Germany
Czech Republic
Luxembourg
120
160
Per 100 000 population
1. The number of graduates does not include graduates from lower
level nursing programmes, resulting in an under-estimation.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524317
251.8
128.3
123.2
107.0
84.0
78.0
76.2
61.6
58.2
58.1
57.4
52.8
51.1
51.0
45.7
44.6
42.5
42.1
41.9
41.9
41.2
40.5
40.5
39.2
31.0
29.2
28.5
26.0
25.2
25.0
17.2
17.2
0
70
140
210
280
Per 1 000 nurses
Note: The categories of nurses included in the denominator are the
same as the graduate numbers included in the numerator.
1. The denominator data include all nurses licensed to practice.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524336
3.8.3 Absolute number of nursing graduates, selected OECD countries, 1990 to 2010
France
Germany
Finland
Norway
Italy
Japan
Spain
Switzerland
Number of graduates
50 000
Number of graduates
10 000
40 000
7 500
30 000
5 000
20 000
2 500
10 000
0
1990
1995
2000
2005
2010
0
1990
1995
2000
2005
2010
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524355
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
75
3. HEALTH WORKFORCE
3.9. Remuneration of nurses
The remuneration level of nurses is one of the factors affecting job satisfaction and the attractiveness of the profession.
It also has a direct impact on costs, as wages represent one
of the main spending items in health systems.
Gathering comparable data on the remuneration of nurses
is difficult because different countries collect data based on
different sources, covering different categories of nurses.
The data presented in this section generally focus on the
remuneration of nurses working in hospitals, although the
data coverage differs for some countries (see the box on
“Definition and comparability”).
The data are presented in two ways. First, it is compared
with the average wage of all workers in each country,
providing some indication of the relative financial attractiveness of nursing compared to other occupations.
Second, the remuneration level in each country is
converted into a common currency, the US dollar, and
adjusted for purchasing power parity, to provide an indication of the relative economic well-being of nurses
compared with their counterparts in other countries.
In most countries, the remuneration of hospital nurses was
at least slightly above the average wage of all workers
in 2009. In Mexico, the income of nurses was 2.4 times
greater than the average wage. In New Zealand and
Luxembourg, it was 50% and 40% higher, while in the
United States it was 30% greater than the average wage.
However, in other countries, the salary of hospital nurses is
roughly equal to the average wage in the economy, while in
the Slovak Republic and Hungary it is lower (Figure 3.9.1).
When converted to a common currency, the remuneration of
nurses was about four to five times higher in Luxembourg
than in Hungary, the Slovak Republic, Estonia and the Czech
Republic (Figure 3.9.2). Nurses in the United States also had
relatively high earnings compared with their counterparts in
other countries. This partly explains the ability of the United
States to attract many nurses from other countries (Aiken
and Cheung, 2008). In Mexico, although the salary of nurses
appears to be high compared to other workers in the
country, their wage level is low compared to nurses in the
United States and other countries.
The remuneration of nurses in real terms (taking into
account inflation) has increased in all OECD countries over
the past decade, with the exception of Hungary, where it
remained unchanged between 2003 and 2009. The growth
was particularly strong in the Slovak Republic and the
Czech Republic, narrowing the gap to a certain extent with
their counterparts in other European countries. In these
two countries, as well as in New Zealand, the United States,
Australia and Canada, the wages of nurses also grew
significantly faster than that of other workers, making the
profession financially more attractive (Figure 3.9.3).
Concerns about the competitiveness of nurses’ pay, pay
equity, and shortages or uneven geographic distribution of
nurses motivated pay interventions in some countries in
76
recent years. Between 2006 and 2009, the Czech Republic,
Finland, New Zealand and the United Kingdom implemented
some pay increases for certain categories of nurses. These pay
increases led to increased numbers of applicants into nursing
education, but the impact on nurses already in work is more
difficult to assess, as their labour market participation is also
affected by the complex interaction of other aspects such as
working environment and working conditions, career
possibilities and individuals’ priorities (Buchan and Black,
2011). In Iceland, cutbacks in nurse remuneration in response
to the economic crisis have led nurses to increase their
regular working time, while their overtime work was reduced
(Friðfinnsdóttir and Jónsson, 2010).
Definition and comparability
The remuneration of nurses refers to average gross
annual income, including social security contributions and income taxes payable by the employee. It
should normally include all extra formal payments,
such as bonuses and payments for night shifts and
overtime. In most countries, the data relate specifically to nurses working in hospitals, although in
Canada, New Zealand and the United States the data
also cover nurses working in other settings. In some
federal states, such as Canada, the level and structure
of nurse remuneration is determined at the subnational level, which may contribute to variations
across jurisdictions.
Data refer only to registered (“professional”) nurses in
Australia, Canada, Denmark and the United States,
resulting in an overestimation compared to other
countries where lower-level nurses (“associate professional”) are also included.
The data relate to nurses working full-time, with the
exception of Belgium where part-time nurses are also
included (resulting in an under-estimation). The data
for some countries do not include additional income
such as overtime payments and bonuses (e.g. Italy,
Portugal and Slovenia). Informal payments, which in
some countries represent a significant part of total
income, are not reported.
The remuneration of nurses is compared to the average
wage of full-time employees in all sectors in the country,
except in Iceland, Mexico and New Zealand where it is
compared to the average wage in selected industrial
sectors.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
3. HEALTH WORKFORCE
3.9. Remuneration of nurses
3.9.1 Hospital nurses’ remuneration,
ratio to average wage, 2009 (or nearest year)
Mexico
Luxembourg
United States1
Ireland
Australia1
Denmark1
United Kingdom
Canada1
Norway
Spain
Chile
New Zealand
Netherlands
Israel
Iceland
Japan
Finland
Italy
Slovenia
Greece
Mexico
Turkey
Czech Republic
Estonia
Slovak Republic
Hungary
2.4
New Zealand
1.5
Luxembourg
1.4
Iceland
1.3
United States1
1.3
Spain
1.3
Turkey
1.2
1
1.2
Australia1
1.2
Canada
3.9.2 Hospital nurses’ remuneration, USD PPP,
2009 (or nearest year)
Slovenia
1.1
United Kingdom
1.1
Japan
1.1
Italy
1.1
Denmark1
1.1
Greece
1.0
Estonia
1.0
Norway
1.0
Netherlands
1.0
Ireland
1.0
Finland
1.0
Czech Republic
1.0
Slovak Republic
0.9
Hungary
0.8
0
0.5
1.0
1.5
2.0
2.5
3.0
Ratio to average wage in each country
80
68
54
53
52
52
51
49
48
48
47
44
43
42
39
38
37
35
33
26
24
22
20
18
17
0
40
80
USD PPP, thousands
1. Data refer to registered (“professional”) nurses in the United States,
Canada, Australia and Denmark resulting in an over-estimation.
1. Data refer to registered (“professional”) nurses in the United States,
Canada, Australia and Denmark resulting in an over-estimation.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524374
1 2 http://dx.doi.org/10.1787/888932524393
3.9.3 Growth in the remuneration of hospital nurses, 2000-09 (or nearest year)
Remuneration of hospital nurses
Average wage of all workers
Average annual growth rate (%, in real terms)
7
6.5
5.9
6
5
4.1
3.8
4
3.1
3.0
3
2.3
2.9
1.8
1.8
2
2.3
2.5
1
0.6
0.9
0.7
1.1
1.2
1.0
1.3
1.1
1.5
1.1
0.3
0.0
ic
pu
bl
Re
pu
Sl
ov
ak
Re
Cz
ec
h
w
Ne
bl
ic
nd
la
an
al
Ze
Ir e
d
d
an
nl
Fi
da 1
na
Ca
St
d
i te
Un
De
nm
at
ar
es 1
k1
n
pa
Ja
st
Au
rw
No
ra
ay
s
nd
Ne
th
er
la
ar
ng
Hu
0.0
li a 1
0.0
y
0
1. Data refer to registered (“professional”) nurses in the United States, Canada, Australia and Denmark.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524412
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
77
4. HEALTH CARE ACTIVITIES
4.1. Consultations with doctors
4.2. Medical technologies
4.3. Hospital beds
4.4. Hospital discharges
4.5. Average length of stay in hospitals
4.6. Cardiac procedures (coronary angioplasty)
4.7. Hip and knee replacement
4.8. Treatment of renal failure (dialysis and kidney transplants)
4.9. Caesarean sections
4.10. Cataract surgeries
4.11. Pharmaceutical consumption
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
79
4. HEALTH CARE ACTIVITIES
4.1. Consultations with doctors
Consultations with doctors can take place in doctors’
offices or clinics, in hospital outpatient departments or, in
some cases, in patients’ own homes. In many European
countries (e.g. Denmark, Italy, the Netherlands, Norway,
Portugal, the Slovak Republic, Spain and the United
Kingdom), patients are required, or given incentives to
consult a general practitioner (GP) “gatekeeper” about any
new episode of illness. The GP may then refer them to a
specialist, if indicated. In other countries (e.g. Austria, the
Czech Republic, Iceland, Japan and Korea), patients may
approach specialists directly.
The number of doctor consultations per person per year
ranges from 13 in Japan and Korea, and over 11 in the
Czech Republic, Hungary and the Slovak Republic, to less
than 3 in Chile, Mexico and Sweden (Figure 4.1.1). The
OECD average is 6.5 consultations per person per year.
Cultural factors appear to play a role in explaining some of
the variations across countries, but certain characteristics
of health systems may also play a role. Countries which pay
their doctors mainly by fee-for-service tend to have aboveaverage consultation rates (e.g. Japan and Korea), while
countries with mostly salaried doctors tend to have belowaverage rates (e.g. Mexico and Sweden). However, there are
examples of countries, such as Switzerland and the United
States, where doctors are paid mainly by fee-for-service
and where consultation rates are also below average,
suggesting that other factors also play a role. (See Table A.5
in Annex A for more information on the mode of payments
of doctors in each country.)
In Sweden, the low number of doctor consultations may be
explained partly by the fact that nurses play an important
role in primary care (Bourgueil et al., 2006). Similarly, in
Finland, nurses and other health professionals play an
important role in providing primary care to patients in
health centres, lessening the need for consultations with
doctors (Delamaire and Lafortune, 2010).
The average number of doctor consultations per person has
increased in a majority of OECD countries since 2000
(Figure 4.1.1). The rise was particularly strong in Korea and
Switzerland. In Korea, this rise can be at least partly
explained by the rapid increase in the number of physicians over the past decade (see Indicator 3.2 “Medical
doctors”). In the Slovak Republic, the number of doctor
consultations fell by over 2% per year since 2000 at a time
when the number of doctors per capita was also falling. In
Canada, the number of consultations per person also
decreased, but this can be attributed to the reduction in the
proportion of consultations paid through fee-for-services,
the only consultations identified and reported here.
The same information can be used to estimate annual
numbers of consultations per doctor in OECD countries.
This should not be taken as a measure of doctors’ productivity, since consultations can vary in length and effectiveness, and because it excludes the work doctors do on
80
hospital inpatients, administration and research. There are
other comparability limitations reported in the box on
“Definition and comparability”. Keeping these reservations
in mind, this estimate varies greatly across OECD countries
(Figure 4.1.2). Again, it is possible that some cultural factors
play a part, because there is clustering of the two OECD
Asian countries and the central and eastern European
countries at the top of the ranking.
While the average number of doctor consultations per
capita varies greatly across OECD countries, there are also
significant differences among population groups within
each country. Chapter 6 on “Access to Care” provides
additional information on disparities in doctor consultations by income group in a number of countries
(Indicator 6.5 “Inequalities in doctor consultations”).
Definition and comparability
Consultations with doctors refer to the number of
contacts with physicians (both generalists and
specialists). There are variations across countries in
the coverage of different types of consultations,
notably in outpatient departments of hospitals.
The data come mainly from administrative sources,
although in some countries (Ireland, Israel, Italy, the
Netherlands, Spain, Switzerland, New Zealand and the
United Kingdom) the data come from health interview
surveys. Estimates from administrative sources tend
to be higher than those from surveys because of
problems with recall and non-response rates.
The figures for the Netherlands exclude contacts for
maternal and child care. The data for Portugal
exclude visits to private practitioners, while those for
the United Kingdom exclude consultations with
specialists outside hospital outpatient departments.
In Luxembourg, consultations with doctors located
outside the country are not included (these consultations account for a higher number than in other countries). The data for Canada only include consultations
paid on a fee-for-service basis. In Germany, the data
include only the number of cases of physicians’
treatment according to reimbursement regulations
under the Social Health Insurance Scheme (a treatment only counts the first contact over a three-month
period, even if the patient consults a doctor more
often). Telephone contacts are included for several
countries (e.g. the Czech Republic, Ireland, Spain and
the United Kingdom).
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.1. Consultations with doctors
4.1.1 Doctors consultations per capita, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Japan
Korea
Slovak Republic
Hungary
Czech Republic
Germany
Belgium
Spain
Turkey
Italy
Austria
France
Poland
Iceland
Slovenia
Australia
OECD
Estonia
Luxembourg
Israel
Netherlands
Canada
United Kingdom
Denmark
New Zealand
Finland
Portugal
Greece
Switzerland
United States
Ireland
Mexico
Sweden
Chile
13.2
13.0
12.1
12.0
11.2
8.2
7.6
7.5
7.3
7.0
6.9
6.9
6.8
6.6
6.6
6.5
6.5
6.3
6.3
6.2
5.7
5.5
5.0
4.6
4.3
4.2
4.1
4.0
4.0
3.9
3.3
2.9
2.9
1.8
15
10
Annual consultations per capita
5
0
-1.1
3.0
-2.6
0.9
-.3
1.5
-0.6
-1.8
n.a.
2.8
0.3
-1.2
1.8
1.4
n.a.
0.2
0.3
0.0
0.4
-1.5
-0.4
-1.7
-0.6
1.0
1.8
-0.3
1.8
-1.2
3.3
0.7
n.a.
1.7
0.4
1.5
-4
-2
0
2
4
Average annual growth rate (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524431
4.1.2 Estimated number of consultations per doctor, 2009 (or nearest year)
748
1 040
777
1 087
1 341
1 163
1 475
1 421
1 601
1 581
1 799
1 000
1 756
1 846
1 805
1 848
1 929
2 051
2 051
2 146
2 119
2 303
1 873
2 000
2 255
2 616
2 357
3 146
2 713
3 000
3 133
4 000
3 732
5 000
3 164
4 460
6 000
3 973
6 694
6 129
Consultations per doctor
7 000
ra
el
C
i t e hi
le
d
St
at
es
Fi
nl
an
Au d
st
r
M ia
ex
i
De co
nm
ar
Ir e k
l
Po and
r
S w tug
i t z al 2
er
la
S w nd
ed
e
Gr n
ee
ce
Un
Is
d
an
Sl
Ic
el
ly
It a
Tu
rk
e
ov Hun y
ak ga
Re r y
pu
b
C z C a li c
ec na
h
Re d a 1
pu
bl
i
Po c
la
n
Sl
ov d
en
Be ia
lg
iu
m
Lu OE
xe C D
m
bo
G e ur g
rm
Au any
st
ra
li a
Ne Sp
t h a in
er
la
nd
Fr s
an
ce
N e E s to
Un w Z ni a
i te ea
l
d
K i and
ng
do
m
n
pa
Ko
Ja
re
a
0
1. In Canada, the number of doctors only includes those paid fee-for-services to be consistent with the data on consultations.
2. Data for the denominator include all doctors licensed to practice (resulting in an underestimation in the number of consultations per doctor).
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524450
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
81
4. HEALTH CARE ACTIVITIES
4.2. Medical technologies
Progress in medical technologies continues to transform
health care delivery and to improve life expectancy and
quality of life, but it is also one of the main drivers of rising
health expenditure across OECD countries. This section
presents data on the availability and use of two diagnostic
technologies – computed tomography (CT) scanners and
magnetic resonance imaging (MRI) units.
CT scanners and MRI units help physicians diagnose a
range of conditions by producing cross-sectional views of
the inside of the body. Unlike conventional radiography
and CT scanning, newer imaging technology used in
MRI units does not expose patients to ionising radiation
which may cause damage in living tissue.
The availability of CT scanners and MRI units has increased
rapidly in most OECD countries over the past two decades.
Japan has, by far, the highest number of MRI and CT
scanners per capita, followed by the United States for MRI
units and by Australia for CT scanners (Figures 4.2.1
and 4.2.2). At the other end of the scale, the number of
MRI units and CT scanners were the lowest in Mexico,
Hungary and Israel.
Data on the use of MRI and CT scanners are available for a
smaller group of countries, excluding Japan. Based on this
more limited country coverage, the number of MRI and
CT examinations per capita is highest in Greece and the
United States, followed by Luxembourg and Iceland
(Figures 4.2.3 and 4.2.4).
In Greece, most CT and MRI scanners are installed in private
diagnostic centres, and only a minority are found in public
hospitals. There are no regulations concerning the purchase
of MRI units in Greece, while the purchase of CT scanners
requires a licence that is granted following a review that is
based on a criterion of population density. There are also no
guidelines concerning the use of CT and MRI scanners (Paris
et al., 2010). The current situation has led the Greek Ministry
of Health and Social Solidarity to establish an expert
committee to review regulations and propose new criteria
for the purchase of CT and MRI scanners.
In the United States, evidence suggests that there is an
overuse of CT and MRI examinations. Between 1997
and 2006, the number of scans in the United States
increased dramatically while the occurrence of illnesses
has remained constant (Smith-Bindman et al., 2008).
82
Furthermore, payment incentives allow doctors to benefit
from exam referrals which also increase the likelihood of
overuse. Many studies have attempted to assess tangible
medical benefits of the substantial increase in CT and
MRI examinations in the United States but have found no
conclusive evidence of such benefits (Baker et al., 2008).
Other OECD countries are also examining ways to promote
the more rational purchase and use of diagnostic technologies (OECD, 2010b). In the United Kingdom, the National
Institute for Health and Clinical Excellence set up in 2009 a
Diagnostics Advisory Committee to evaluate and make
recommendations for the appropriate use of diagnostic
technologies within the NHS in England (NICE, 2009).
Definition and comparability
For MRI units and CT scanners, the numbers of equipment per million population are reported. MRI exams
and CT exams relate to the number of exams per
1 000 population. In most countries, the data cover
equipment installed both in hospitals and the ambulatory sector.
However, there is only partial coverage for some
countries. CT scanners and MRI units outside hospitals are not included in some countries (Belgium,
Germany and Spain). For the United Kingdom, the
data only include scanners in the public sector. For
Australia, the number of MRI units and CT scanners
includes only those eligible for reimbursement under
Medicare, the universal public health system (in 1999,
60% of total MRI units were eligible for Medicare
reimbursement). Also for Australia, MRI and CT
exams only include those for outpatients and private
inpatients (excluding those in public hospitals). MRI
and CT exams for Ireland only cover public hospitals,
while Korea and the Netherlands only include
publicly financed exams.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.2. Medical technologies
4.2.1 MRI units, 2009 (or nearest year)
Hospital
Outside hospital
Japan
United States
Iceland
Greece
Italy
Korea
Austria
Finland
Denmark
Luxembourg
OECD
Ireland
Netherlands
Belgium1
Spain1
New Zealand
Germany1
Portugal
Turkey
Canada
Estonia
France
Slovak Republic
Australia 2
Czech Republic
United Kingdom 3
Slovenia
Poland
Hungary
Israel
Mexico
4.2.2 CT scanners, 2009 (or nearest year)
Total
Hospital
43.1
25.9
21.9
21.7
21.6
19.0
18.4
16.9
15.4
14.2
12.2
11.9
11.0
10.7
10.0
9.7
9.5
8.9
8.9
8.0
7.5
6.4
6.1
5.9
5.7
5.6
4.5
3.7
2.8
1.9
1.9
0
10
20
30
Outside hospital
Japan
Australia 2
Korea
Iceland
United States
Greece
Switzerland
Italy
Austria
Luxembourg
Portugal
Denmark
OECD
Finland
Germany1
Ireland
Spain1
Estonia
New Zealand
Czech Republic
Canada
Belgium1
Slovak Republic
Poland
Slovenia
Turkey
Netherlands
France
Israel
United Kingdom 3
Hungary
Mexico
40
50
Per million population
Total
97.3
38.7
37.1
34.5
34.3
33.8
32.8
31.7
29.3
26.3
26.0
23.7
22.8
20.4
17.2
15.3
15.1
14.9
14.6
14.1
13.9
13.5
13.3
12.4
11.9
11.6
11.3
11.1
9.4
7.4
7.2
4.3
0
20
40
60
80
100
Per million population
Note: The OECD average does not include countries which only report
equipment in hospital (Belgium, Germany and Spain).
1. Equipment outside hospital not included.
2. Only equipment eligible for reimbursement under Medicare.
3. Any equipment in the private sector not included.
Note: The OECD average does not include countries which only report
equipment in hospital (Belgium, Germany and Spain).
1. Equipment outside hospital not included.
2. Only equipment eligible for reimbursement under Medicare.
3. Any equipment in the private sector not included.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524469
4.2.3 MRI exams, 2009 (or nearest year)
Hospital
Outside hospital
Greece
United States
Iceland
Luxembourg
Turkey
France
Belgium
Austria1
OECD
Netherlands
Spain1
Canada
United Kingdom1
Denmark
Estonia
Czech Republic
Hungary2
Slovak Republic
Australia 3
Germany1
Ireland1
Israel
Korea
Chile
4.2.4 CT exams, 2009 (or nearest year)
Total
Hospital
97.9
91.2
75.5
73.9
67.2
55.2
52.8
50.3
46.6
43.9
43.1
43.0
38.6
37.8
37.2
32.3
31.3
29.8
23.3
17.3
16.0
15.6
13.2
1.7
0
20
40
60
1 2 http://dx.doi.org/10.1787/888932524488
80
100
Per 1 000 population
Outside hospital
Greece
United States
Luxembourg
Belgium
Iceland
Estonia
Austria1
France
OECD
Canada
Israel
Turkey
Australia 3
Korea
Czech Republic
Slovak Republic
Denmark
Spain1
Hungary2
United Kingdom1
Ireland1
Netherlands
Germany1
Chile
Total
320.4
227.9
187.0
179.3
156.2
152.7
138.9
138.7
131.8
125.4
122.8
95.8
93.9
93.5
87.5
85.4
83.8
80.1
73.4
72.8
69.1
65.7
49.0
24.3
0
70
140
210
280
350
Per 1 000 population
Note: The OECD average does not include countries which only report
exams in or outside hospital.
1. Data for exams outside hospital are not available.
2. Data for exams in hospital are not available.
3. Only include exams for outpatients and private inpatients (excluding
exams in public hospitals).
Note: The OECD average does not include countries which only report
exams in or outside hospital.
1. Data for exams outside hospital are not available.
2. Data for exams in hospital are not available.
3. Only include exams for outpatients and private inpatients (excluding
exams in public hospitals).
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524507
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
1 2 http://dx.doi.org/10.1787/888932524526
83
4. HEALTH CARE ACTIVITIES
4.3. Hospital beds
The number of hospital beds provides a measure of the
resources available for delivering services to inpatients in
hospitals. This section presents data on the total number of
hospital beds, including those allocated for curative (acute),
psychiatric, long-term and other types of care. It also
includes an indicator of bed occupancy rates focussing on
curative care beds.
Among OECD countries, the number of hospital beds per
capita is highest in Japan and Korea, with over eight beds
per 1 000 population in 2009 (Figure 4.3.1). Both Japan and
Korea have “social admissions”, that is, a significant part of
hospital beds are devoted to long-term care. The number of
hospital beds is also well above the OECD average in the
Russian Federation, Germany and Austria. On the other
hand, large emerging countries in Asia (India, Indonesia
and China) have relatively few hospital beds compared
with the OECD average. This is also the case for OECD and
emerging countries in Central and South America (Mexico,
Brazil and Chile).
The number of hospital beds per capita has decreased at
least slightly over the past decade in most OECD countries,
falling from 5.4 per 1 000 population in 2000 to 4.9 in 2009.
This reduction has been driven partly by progress in medical technology which has enabled a move to day surgery
and a reduced need for hospitalisation. The reduction in
hospital beds has been accompanied in many countries by
a reduction in hospital discharges and the average length
of stay (see Indicators 4.4 “Hospital discharges” and 4.5
“Average length of stay in hospitals”). Only in Korea, Greece
and Turkey has the number of hospital beds per capita
grown between 2000 and 2009.
Two-thirds of hospital beds are allocated for curative care
on average across OECD countries. The rest of the beds are
allocated for psychiatric (14%), long-term (12%) and other
types of care (8%). In some countries, the share of beds
allocated for psychiatric care and long-term care is much
greater than the average. In Finland, a greater number of
hospital beds is in fact allocated for long-term care than for
curative care, because local governments (municipalities)
use some beds in health care centres (which are defined as
hospitals) for at least some of the institution-based
long-term care (OECD, 2005a). In Ireland, just over half of
hospital beds are allocated for acute care, while 30% are
devoted to long-term care (Figure 4.3.2).
In several countries, the reduction in the number of hospital beds has been accompanied by an increase in their
occupancy rates. The occupancy rate of curative (acute)
care beds stood at 76% on average across OECD countries
in 2009, slightly above the 2000 level (Figure 4.3.3). Israel,
Canada, Norway, Ireland, Switzerland, and the United
Kingdom had the highest occupancy rates in 2009. All of
these countries have fewer curative care beds than most
other OECD countries. On the other hand, the Netherlands,
Turkey and Mexico have the lowest occupancy rates,
84
although the occupancy rate has increased over the past
decade in Turkey and Mexico. In the Netherlands, the low
occupancy rates can be explained at least partly by the fact
that hospital beds include all administratively approved
beds and not only those available for immediate use.
Definition and comparability
Hospital beds are defined as all beds that are regularly
maintained and staffed and are immediately available for use. They include beds in general hospitals,
mental health and substance abuse hospitals, and
other specialty hospitals. Beds in nursing and
residential care facilities are excluded.
Curative care beds are beds accommodating patients
where the principal intent is to do one or more of the
following: manage labour (obstetric), cure non-mental
illness or provide definitive treatment of injury,
perform surgery, relieve symptoms of non-mental illness or injury (excluding palliative care), reduce
severity of non-mental illness or injury, protect
against exacerbation and/or complication of nonmental illness and/or injury which could threaten life
or normal functions, perform diagnostic or therapeutic procedures.
Psychiatric care beds are beds accommodating
patients with mental health problems. They include
beds in psychiatric departments of general hospitals,
and all beds in mental health and substance abuse
hospitals.
Long-term care beds are hospital beds accommodating patients requiring long-term care due to chronic
impairments and a reduced degree of independence
in activities of daily living. They include beds in
long-term care departments of general hospitals,
beds for long-term care in specialty hospitals, and
beds for palliative care.
The occupancy rate for curative (acute) care beds is
calculated as the number of hospital bed-days related
to curative care divided by the number of available
curative care beds (multiplied by 365).
In the Netherlands, hospital beds include all beds that
are administratively approved rather than only those
immediately available for use, resulting in an overestimation (the difference between all administratively
approved beds and beds available for immediate use
was about 10% in 2007). This also results in an underestimation of bed occupancy rates.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.3. Hospital beds
4.3.1 Hospital beds per 1 000 population, 2000 and 2009 (or nearest year)
2009
2000
13.7
Per 1 000 population
15
1.7
0.5
0.7
2.3
2.3
1.8
2.5
2.4
3.1
3
2.8
3.3
3.2
3.3
3.3
3.5
3.3
3.7
3.5
4.6
3.8
4.8
4.7
4.9
4.9
5.4
5.1
5.8
6
5.5
6.5
6.2
6.6
6.5
7.1
6.7
7.7
7.1
9
8.2
8.3
9.7
12
D
IN
IS
R
CA
N
NO
R
PR
T
GB
R
ES
P
US
A
SW
E
TU
R
ZA
F
CH
L
CH
N
BR
A
M
EX
ID
N
IT
A
DN
K
N
IS
L
LU
X
ES
T
CH
OE E
CD
27
IR
L
GR
C
NL
D
SV
N
AU
S
FI
JP
N
RU
S
KO
R
DE
U
AU
T
CZ
E
HU
N
PO
L
FR
A
BE
L
SV
K
0
Source: OECD Health Data 2011; national sources for non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932524545
4.3.2 Hospital beds by function of health care, 2009 (or nearest year)
Countries ranked from highest to lowest number of total hospital beds per capita
Curative care beds
%
100
Psychiatric care beds
Long-term care beds
Other hospital beds
80
60
40
20
R
ES
P
US
A
SW
E
TU
R
T
GB
PR
R
N
NO
CA
K
R
IS
IT
A
DN
SV
N
AU
S
D
NL
C
L
GR
IR
X
ES
T
OE
CD
CH
E
LU
FI
SV
N
K
L
BE
L
A
FR
PO
HU
E
N
T
CZ
AU
R
DE
KO
N
JP
U
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524564
4.3.3 Occupancy rate of curative (acute) care beds, 2000 and 2009 (or nearest year)
2009
2000
62.3
63.4
65.5
70
67.3
67.7
71.2
72.1
74.0
74.2
74.3
74.4
75.3
75.3
75.4
76.1
76.2
76.5
77.6
80
79.0
79.5
84.2
87.9
89.2
90
91.6
96.3
93.0
%
100
52.7
60
R
D1
NL
TU
EX
M
A
US
T
K
SV
ES
N
SV
T
PR
L
X
BE
LU
N
HU
A
FR
E
N
JP
C
CZ
GR
25
OE
CD
L
U
DE
CH
P
ES
T
AU
IT
A
R
GB
E
CH
L
IR
R
NO
N
CA
IS
R
50
1. In the Netherlands, hospital beds include all beds that are administratively approved rather than those immediately available for use.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524583
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
85
4. HEALTH CARE ACTIVITIES
4.4. Hospital discharges
Hospital discharge rates measure the number of patients
who leave a hospital after receiving care. Together with the
average length of stay, they are important indicators of
hospital activities. Hospital activities are affected by a
number of factors, including the demand for hospital
services, the capacity of hospitals to treat patients, the
ability of the primary care sector to prevent avoidable
hospital admissions, and the availability of post-acute care
settings to provide rehabilitative and long-term care
services.
In 2009, hospital discharge rates were the highest in
Austria and France, although the high rate in France is
partly explained by the inclusion of some separations for
same-day procedures (Figure 4.4.1). Discharge rates are also
high in the Russian Federation, Germany, the Slovak
Republic, Poland and the Czech Republic. They are the
lowest in Mexico, Brazil and China. In general, those
countries that have more hospital beds tend to have higher
discharge rates. For example, the number of hospital beds
per capita in Austria and Germany is more than twice than
Spain and the United Kingdom, and discharge rates are
also about twice as large (see Indicator 4.3 “Hospital beds”).
Across OECD countries, the main conditions leading to
hospitalisation in 2009 were circulatory diseases (which
include ischemic heart disease, stroke and other diseases),
pregnancy and childbirth, diseases of the digestive system,
cancers, and injuries and other external causes.
Germany and Austria have the highest discharge rate for
circulatory diseases, followed by the Slovak Republic and
Estonia (Figure 4.4.2). The high rates in the Slovak Republic
and Estonia are associated with high mortality rate from
circulatory diseases which may be used as a proxy
indicator for the occurrence of these diseases (see
Indicator 1.3 “Mortality from heart disease and stroke”).
This is not the case for Germany and Austria.
Austria and Germany also have the highest discharge rates
for cancers (Figure 4.4.3), although the number of new
cancer cases in these countries is only around the OECD
average (see Indicator 1.11 “Cancer incidence”). In Austria,
the high rate is associated with a high rate of hospital
readmissions for further investigation and treatment of
cancer patients (European Commission, 2008a).
Trends in hospital discharge rates for all conditions vary
widely. In about one-third of OECD countries, discharge
rates have increased over the past ten years. These include
countries where discharge rates were low in 2000
(e.g. Korea, Mexico and Turkey) and others where it was
already above-average (e.g. Germany, Poland and the Slovak
Republic). In a second group of countries (e.g. Austria,
Belgium, France, Spain, Sweden and the United Kingdom),
they have remained stable, while in the third group (including Canada, Denmark, Finland and Italy), discharge rates
fell between 2000 and 2009.
86
Trends in hospital discharges reflect the interaction of
several factors. Demand for hospitalisation may grow as
populations age, given that older population groups account
for a disproportionately high percentage of hospital
discharges. For example, in Austria and Germany, 42% of all
hospital discharges in 2008 were for people aged 65 and
over, more than twice their share of the population.
However, population ageing alone may be a less important
factor in explaining trends in hospitalisation rates than
changes in medical technologies and clinical practices. The
diffusion of new medical interventions often gradually
extends to older population groups, as interventions become
safer and more effective for people at older ages (Dormont
and Huber, 2006). However, the diffusion of new medical
technologies may also involve a reduction in hospitalisation
if it entails a shift from procedures requiring overnight
stays in hospitals to same-day procedures. In the group of
countries where discharge rates have decreased over the
past decade, there has been a strong rise in the number of
day surgeries (see Indicator 4.10, for example, for evidence
on the rise in day surgeries for cataracts).
Definition and comparability
Hospital discharge is defined as the release of a
patient who has stayed at least one night in hospital.
It includes deaths in hospital following inpatient care.
Same-day discharges are usually excluded, with the
exceptions of Chile, France, Korea, Norway, Poland,
the Slovak Republic, Turkey and the United States
which include some same-day separations.
Healthy babies born in hospitals are excluded from hospital discharge rates in several countries (e.g. Australia,
Austria, Canada, Chile, Estonia, Finland, Greece, Ireland,
Israel, Japan, Korea, Luxembourg, Mexico, Spain,
Sweden, Turkey). These comprise some 3-6% of all
discharges.
Data for some countries do not cover all hospitals. For
instance, data for Denmark, Ireland, Mexico, New
Zealand, Poland, Sweden and the United Kingdom are
restricted to public or publicly-funded hospitals only.
Data for Portugal relate only to public hospitals on
the mainland (excluding the Islands of Azores
and Madeira). Data for Austria, Canada, Estonia,
Luxembourg and the Netherlands include only acute
care/short-stay hospitals. Data for Israel and Japan
refer to acute care hospitalisations.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.4. Hospital discharges
4.4.1 Hospital discharges per 1 000 population, 2009 (or nearest year)
Per 1 000 population
300
265 263
250
237 237
211
200
201
195 191
185 184
177 173
170 170 168 168 166
162 160 158 158
146 142 141
138 133 132
131 130
150
117 112
107 104
100
98
84
67
61
58
50
A2
IT
A
NL
D
PR
T
JP
N1
ES
P
CH 1
L 1,
2
CA
N1
CH
N
BR
A
M
EX
1
US
L1
2
KO
IR
R 1,
2
OE
CD
IS
R1
NZ
L
IS
L
GB
R
TU
R 1,
1
N
SV
2
CZ
E
GR
C1
HU
N
FI
N1
NO
R2
BE
L
DN
K
ES
T1
CH
E
LU
X1
SW
E1
AU
S
AU
T1
FR
A2
RU
S
DE
U
SV
K2
PO
L
0
1. Excludes discharges of healthy babies born in hospital (between 3-6% of all discharges).
2. Includes same-day separations.
Source: OECD Health Data 2011; WHO-Europe for the Russian Federation and national sources for other non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932524602
4.4.2 Hospital discharges for circulatory diseases
per 1 000 population, 2009 (or nearest year)
Germany
Austria
Slovak Republic
Estonia
Hungary
Poland
Greece
Czech Republic
Finland
Sweden
Norway
France
Belgium
Luxembourg
Italy
Slovenia
Denmark
OECD
United States
Switzerland
Netherlands
Australia
Iceland
Turkey
Korea
New Zealand
Japan
Israel
United Kingdom
Portugal
Spain
Ireland
Canada
Chile
Mexico
35.0
33.5
33.2
31.6
30.1
28.8
28.0
27.8
27.4
25.4
23.8
22.2
20.9
20.8
20.5
19.9
19.9
19.8
19.5
17.3
16.7
16.1
14.4
14.3
14.1
13.9
13.8
13.3
13.2
13.2
12.9
11.6
10.9
7.1
2.3
0
10
20
30
40
Per 1 000 population
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524621
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4.4.3 Hospital discharges for cancers
per 1 000 population, 2009 (or nearest year)
Austria
Germany
Hungary
Japan
France
Greece
Slovak Republic
Poland
Slovenia
Finland
Estonia
Norway
Czech Republic
Luxembourg
Korea
Sweden
Denmark
OECD
Switzerland
Italy
Belgium
Iceland
Australia
Portugal
Netherlands
United Kingdom
Spain
Turkey
Ireland
New Zealand
Chile
Canada
Israel
United States
Mexico
29.2
24.5
23.2
20.6
19.9
19.2
18.9
18.6
17.8
17.2
16.3
16.0
15.7
15.6
15.4
14.1
13.9
13.8
13.1
12.5
11.9
11.8
11.5
10.8
10.7
9.4
9.4
8.5
8.3
7.6
6.7
6.1
6.1
5.7
2.8
0
10
20
30
40
Per 1 000 population
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524640
87
4. HEALTH CARE ACTIVITIES
4.5. Average length of stay in hospitals
The average length of stay in hospitals (ALOS) is often used
as an indicator of efficiency. All other things being equal, a
shorter stay will reduce the cost per discharge and shift
care from inpatient to less expensive post-acute settings.
However, shorter stays tend to be more service intensive
and more costly per day. Too short a length of stay could
also cause adverse effects on health outcomes, or reduce
the comfort and recovery of the patient. If this leads to a
greater readmission rate, costs per episode of illness may
fall only slightly, or even rise.
In 2009, the average length of stay in hospitals for all causes
among OECD countries was the lowest in Mexico, Turkey
and Israel. It was also low in Norway and Denmark, as well
as in the United States, all at less than five days. The
average length of stay was highest in Japan, followed by
Korea. The OECD average was about 7 days (Figure 4.5.1).
Several factors can explain these cross-country differences.
The abundant supply of beds and the structure of hospital
payments in Japan provide hospitals with incentives to
keep patients longer (see Indicator 4.3 “Hospital beds”).
Financial incentives inherent in hospital payment methods
can also influence length of stay in other countries.
The average length of stay in hospitals has fallen over the
past decade in nearly all OECD countries – from 8.2 days
in 2000 to 7.2 days in 2009 on average across OECD countries.
It fell particularly quickly in some of the countries that had
relatively high levels in 2000 (e.g. Japan, Switzerland and the
United Kingdom). Several factors explain this decline,
including the use of less invasive surgical procedures,
changes in hospital payment methods, and the expansion of
early discharge programmes which enable patients to return
to their home to receive follow-up care.
Focusing on average length of stay for specific diseases or
conditions can remove the effect of different mix and
severity of conditions leading to hospitalisation across
countries. Figure 4.5.3 shows that ALOS following a normal
delivery ranges from less than two days in Mexico, Turkey,
88
the United Kingdom, Iceland and Canada, to over 5 days in
the Slovak Republic and Switzerland. ALOS for normal
delivery has become shorter in nearly all countries over the
past decade.
Lengths of stay following acute myocardial infarction (AMI,
or heart attack) also declined over the past decade. In 2009,
ALOS following AMI was the lowest in Turkey and some of
the Nordic countries (Norway, Denmark and Sweden), at
less than five days. It was the highest in Korea, Germany,
Greece, Finland and Estonia, at around ten days or more
(Figure 4.5.2). However, care is required in making crosscountry comparisons. For example, ALOS in Finland may
include patients originally admitted for AMI but who are no
longer receiving acute care, and might therefore be considered long-term care patients.
Definition and deviations
Average length of stay (ALOS) refers to the average
number of days that patients spend in hospital. It is
generally measured by dividing the total number of
days stayed by all inpatients during a year by the
number of admissions or discharges. Day cases are
excluded.
In the calculation of ALOS, days and discharges of
healthy babies born in hospitals are excluded in
several countries (e.g. Australia, Austria, Canada,
Chile, Estonia, Finland, Greece, Ireland, Israel, Japan,
Korea, Luxembourg, Mexico, Spain, Sweden, Turkey).
Including healthy newborns would reduce the ALOS
in these countries (e.g. by 0.6 day in Canada).
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.5. Average length of stay in hospitals
4.5.1 Average length of stay in hospital for all causes, 2000 and 2009 (or nearest year)
2000
2009
3.9
4.3
4.3
4.6
4.5
4.9
5
4.8
5.6
5.1
5.7
5.6
5.8
5.7
5.8
6.0
5.9
6.2
6.1
6.7
6.4
6.9
6.7
7.2
7.0
7.2
7.3
7.2
7.7
7.7
7.5
8.6
7.8
9.7
10
8.7
9.7
15
13.6
14.6
20
12.5
18.5
Days
25
IS
L
NL
D
CH
L
SW
E
FR
A
ZA
F
HU
N
US
A
DN
K
NO
R
IS
R
TU
R
ID
N
M
EX
IT
A
SV
N
PO
L
IR
L
AU
S
PR
T
BE
L
CA
N
GB
R
SV
K
LU
X
CZ
E
ES
OE T
CD
GR
C
ES
P
AU
T
FI
N
DE
U
CH
E
NZ
L
CH
N
JP
N1
KO
R
RU
S
0
1. The data for Japan refer to average length of stay for acute care (excluding long-term care beds in hospitals).
Source: OECD Health Data 2011; WHO-Europe for the Russian Federation and national sources for other non-OECD countries.
1 2 http://dx.doi.org/10.1787/888932524659
4.5.2 Average length of stay following acute myocardial
infarction (AMI), 2009 (or nearest year)
Korea
Germany
Greece
Finland
Estonia
Ireland
New Zealand
Spain
United Kingdom
Portugal
Belgium
Chile
Italy
Switzerland
Austria
Slovenia
OECD
Mexico
Iceland
Czech Republic
Netherlands
France
Canada
Israel
Australia
Hungary
Poland
Luxembourg
United States
Slovak Republic
Sweden
Denmark
Norway
Turkey
13.7
10.8
10.0
9.9
9.8
8.4
8.2
8.1
8.1
7.9
7.8
7.7
7.7
7.6
7.5
7.5
7.2
6.9
6.8
6.7
6.5
6.3
6.2
6.2
6.0
5.9
5.9
5.7
5.3
5.0
4.5
4.2
4.2
4.2
0
5
10
15
Days
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524678
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4.5.3 Average length of stay for normal delivery,
2009 (or nearest year)
Slovak Republic
Switzerland
Czech Republic
Hungary
Belgium
France
Austria
Poland
Greece
Luxembourg
Slovenia
Italy
Finland
Germany
Norway
OECD
Chile
Israel
Denmark
Portugal
Korea
Spain
Australia
Sweden
Ireland
New Zealand
United States
Netherlands
Canada
Iceland
United Kingdom
Turkey
Mexico
5.4
5.1
4.8
4.5
4.3
4.3
4.1
4.1
4.0
4.0
4.0
3.5
3.2
3.2
3.1
3.1
3.0
2.8
2.7
2.7
2.5
2.5
2.4
2.2
2.1
2.1
2.1
1.9
1.8
1.8
1.8
1.5
1.4
0
2
4
6
Days
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524697
89
4. HEALTH CARE ACTIVITIES
4.6. Cardiac procedures (coronary angioplasty)
Heart diseases are a leading cause of hospitalisation and
death in OECD countries (see Indicator 1.3). Coronary angioplasty is a revascularisation procedure that has revolutionised the treatment of ischemic heart diseases (heart
attack and angina) over the past 20 years. It involves the
threading of a catheter with a balloon attached to the tip
through the arterial system into the diseased coronary
artery. The balloon is inflated to distend the coronary artery
at the point of obstruction. The placement of a stent to keep
the artery open accompanies the majority of angioplasties.
Drug-eluting stents (a stent that gradually releases drugs)
are increasingly being used to stem the growth of scar-like
tissue surrounding the stent.
There is considerable variation across OECD countries in
the use of coronary angioplasty (Figure 4.6.1). Germany,
Belgium and the United States had the highest rates of
angioplasty in 2009, followed by Norway and Austria. The
rate of use of angioplasty is the lowest in Mexico and Chile.
The use of angioplasty has increased rapidly since 1990 in
most OECD countries, overtaking coronary bypass surgery
as the preferred method of revascularisation around the
mid-1990s – about the same time that the first published
trials of the efficacy of coronary stenting began to appear
(Moïse et al., 2003). On average across OECD countries,
angioplasty now accounts for 75% of all revascularisation
procedures (Figure 4.6.2). Although angioplasty has in
many cases replaced bypass surgery, it is not always a
substitute since bypass surgery is still the preferred
method for treating patients with multiple-vessel obstructions, diabetes and other conditions (Taggart, 2009).
A number of reasons can explain cross-country variations
in the rate of angioplasty, including: i) differences in the
incidence and prevalence of ischemic heart diseases;
ii) differences in the capacity to deliver and pay for these
procedures; iii) differences in clinical treatment guidelines
and practices; and iv) coding and reporting practices.
The large variations in the number of revascularisation
procedures across countries do not seem to be closely
related to the incidence of ischemic heart disease (IHD), as
measured by IHD mortality (see Figure 1.3.1). IHD mortality
in Germany and Belgium are not too far from the OECD
average, but these two countries have the highest rate of
revascularisation procedures. On the other hand, IHD
mortality in Finland is above the OECD average, while
revascularisation rates are below average.
90
In the United States, there has been a decline in the overall
rate of revascularisation procedures between 2000 and 2009,
driven by an almost 30% decrease in the number of coronary
artery bypass graft (CABG) per capita, while the rate of angioplasty remained relatively stable. One of the reasons why
the angioplasty rate did not increase is due to the greater use
of drug-eluting stents which reduces the likelihood that the
same patient will need another revascularisation. The
combination of stable angioplasty rate, together with a
reduction in repeat revascularisation, indicates that increasing numbers of patients have received an angioplasty over
time (Epstein et al., 2011).
Coronary angioplasty is an expensive intervention,
although it is much less costly than a coronary bypass
because it is less intrusive. In 2007, the average estimated
price of an angioplasty was about USD 14 400 in the United
States, USD 9 300 in Canada and Sweden, and USD 7 000 in
France (Koechlin et al., 2010).
Definition and comparability
The data relate to inpatient procedures, excluding
coronary angioplasties performed or recorded as
day cases. Classification systems and registration
practices vary across countries, and the same procedure can be recorded differently (e.g. an angioplasty
with the placement of a stent can be counted as one
or two procedures). Some countries report only the
main procedure which may result in a significant
under-estimation of the total number. This is the case
for Italy, Luxembourg and Switzerland. In Ireland,
the data only include activities in publicly-funded
hospitals (it is estimated that over 10% of all hospital
activity in Ireland is undertaken in private hospitals).
In countries such as the Netherlands, approximately
25% of all coronary angioplasties are registered as day
cases, and these are not reported here.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.6. Cardiac procedures (coronary angioplasty)
4.6.1 Coronary angioplasty per 100 000 population, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Germany
Belgium
United States
Norway
Austria
Czech Republic
Slovenia
Luxembourg
Iceland
Israel
France
OECD
Denmark
United Kingdom
Greece
Sweden
Poland
Hungary
Netherlands
Australia
Finland
Switzerland
Spain
Italy
Portugal
New Zealand
Canada
Ireland
Chile
Mexico
582
427
377
250
230
221
207
201
198
198
194
188
184
178
177
175
173
172
166
159
139
134
134
133
118
117
105
82
7
2
600
500
400
Per 100 000 population
300
200
100
0
n.a.
7.2
0.5
9.9
n.a.
n.a.
n.a.
4.9
2.3
-1.2
3.5
6.2
6.2
n.a.
n.a.
14.6
1.8
n.a.
7.4
4.2
8.6
8.1
13.6
4.7
11.2
5.2
-0.5
6.5
n.a.
11.0
-4
0
4
8
12
16
Average annual growth rate (%)
Note: Some of the variations across countries are due to different classification systems and recording practices.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524716
4.6.2 Coronary angioplasty as a percentage of total revascularisation procedures, 2000-09
Australia
Canada
Belgium
Denmark
New Zealand
United States
France
Spain
OECD20
OECD20
% of total revascularisation procedures
90
% of total revascularisation procedures
90
80
80
70
70
60
60
50
50
40
40
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Note: Revascularisation procedures include coronary bypass and angioplasty.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524735
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
91
4. HEALTH CARE ACTIVITIES
4.7. Hip and knee replacement
Significant advances in surgical treatment have provided
effective options to reduce the pain and disability associated
with certain musculoskeletal conditions. Joint replacement
surgery (hip and knee replacement) is considered the most
effective intervention for severe osteoarthritis, reducing
pain and disability and restoring some patients to nearnormal function.
Ostheoarthritis is one of the ten most disabling diseases in
developed countries (WHO, 2010b). Worldwide estimates
are that 10% of men and 18% of women aged over 60 years
have symptomatic osteoarthritis, including moderate and
severe forms. Age is the strongest predictor of the development and progression of osteoarthritis. It is more common
in women, increasing after the age of 50 especially in the
hand and knee. Other risk factors include obesity, physical
inactivity, smoking, excess alcohol and injuries (European
Commission, 2008b). While joint replacement surgery is
mainly carried out among people aged 60 and over, it can
also be performed among people of younger ages.
There is considerable variation across countries in the rate
of hip and knee replacement (Figures 4.7.1 and 4.7.2).
Germany, Switzerland and Austria have high rates of both
hip and knee replacement. The United States and Germany
have the highest rate of knee replacement, even though the
population structure of the United States is much younger
than that of Germany. A number of reasons can explain
cross-country variations in the rate of hip and knee
replacement, including: i) differences in the prevalence of
osteoarthritis problems; ii) differences in the capacity to
deliver and pay for these expensive procedures; and
iii) differences in clinical treatment guidelines and practices.
There are currently too few comparable studies on the
prevalence of osteoarthritis to draw any conclusions on
cross-country variations. Nor is there any evidence as to
whether the age- and sex-specific incidence of osteoarthritis has changed in recent decades. However, the
number of people suffering from osteoarthritis has
increased, and is expected to continue to increase in the
coming years, for two reasons: 1) population ageing, which
is resulting in a growing number of people over 60 with a
greater risk of suffering from osteoarthritis; and 2) the
growing prevalence of obesity, which is the main risk factor
for osteoarthritis beyond age and sex.
The number of hip and knee replacement has increased
rapidly over the past decade in most OECD countries
(Figures 4.7.3 and 4.7.4). On average, the rate of hip replace-
92
ment increased by over 25% between 2000 and 2009. The
growth rate was even higher for knee replacement, nearly
doubling over the past decade. In the United States, both
hip replacement and knee replacement rates nearly
doubled since 2000. In Denmark, while the hip replacement
rate increased by only about 20% between 2000 and 2009,
the knee replacement rate almost tripled. The growth rate
was more modest in other countries such as France and
Israel.
The growing volume of hip and knee replacement is
contributing to health expenditure growth as these are
expensive interventions. In 2007, the average estimated
price of a knee replacement was nearly USD 15 000 in the
United States and Australia, USD 12 000 in France, and about
USD 10 000 in Canada, Germany and Sweden. The estimated
price of a hip replacement was even higher, reaching more
than USD 17 000 in the United States, about USD 16 000 in
Australia, and between USD 11 000 and 12 000 in Canada,
France and Sweden (Koechlin et al., 2010).
Definition and comparability
Hip replacement is a surgical procedure in which the
hip joint is replaced by a prosthetic implant. It is
generally conducted to relieve arthritis pain or treat
severe physical joint damage following hip fracture.
Knee replacement is a surgical procedure to replace
the weight-bearing surfaces of the knee joint in order
to relieve the pain and disability of osteoarthritis. It
may also be performed for other knee diseases such
as rheumatoid arthritis.
Classification systems and registration practices vary
across countries, which may affect the comparability
of the data. In Ireland, the data only include activities
in publicly-funded hospitals (it is estimated that over
10% of all hospital activity in Ireland is undertaken in
private hospitals). Some countries only include total
hip replacement, excluding partial hip replacement
(e.g. Estonia).
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.7. Hip and knee replacement
4.7.1 Hip replacement surgery, per 100 000 population,
2009 (or nearest year)
Germany
Switzerland
Belgium
Austria
Denmark
Norway
France
Luxembourg
Sweden
Netherlands
Slovenia
United Kingdom
Finland
United States
Iceland
Czech Republic
Australia
OECD
Italy
New Zealand
Greece
Canada
Ireland
Hungary
Spain
Portugal
Estonia
Slovak Republic
Israel
Poland
Chile
Korea
Mexico
4.7.2 Knee replacement surgery, per 100 000 population,
2009 (or nearest year)
Germany
United States
Switzerland
Austria
Finland
Denmark
Belgium
Luxembourg
Australia
Canada
United Kingdom
Iceland
Sweden
Netherlands
France
OECD
Czech Republic
Spain
New Zealand
Italy
Korea
Slovenia
Norway
Portugal
Israel
Hungary
Ireland
Chile
Mexico
296
287
240
238
236
232
224
222
214
213
194
194
188
184
173
166
154
154
150
149
140
123
117
99
93
88
88
78
51
44
19
17
8
0
100
200
300
Per 100 000 population
Source: OECD Health Data 2011.
213
213
200
188
178
168
168
160
158
143
141
132
127
124
119
118
111
102
102
100
98
93
75
62
47
45
42
5
3
0
100
200
300
Per 100 000 population
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524754
1 2 http://dx.doi.org/10.1787/888932524773
4.7.3 Trend in hip replacement surgery,
2000-09, selected countries
4.7.4 Trend in knee replacement surgery,
2000-09, selected countries
Canada
France
Denmark
Israel
Sweden
Switzerland
Switzerland
United States
OECD25
OECD21
Per 100 000 population
300
Per 100 000 population
300
250
250
200
200
150
150
100
100
50
50
0
0
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524792
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524811
93
4. HEALTH CARE ACTIVITIES
4.8. Treatment of renal failure (dialysis and kidney transplants)
End-stage renal failure (ESRF) is a condition in which the
kidneys are permanently impaired and can no longer
function normally. Some of the main risk factors for
end-stage renal failure include diabetes and hypertension,
two conditions which are becoming more prevalent in
OECD countries. In the United States, diabetes and hypertension alone accounted for over 60% of the primary
diagnoses for all ESRF patients (37% for diabetes and
24% for hypertension) (USRDS, 2008). When patients reach
end-stage renal failure, they require treatment either in the
form of dialysis or through kidney transplants. Treatment
through dialysis tends to be more costly and results in a
poorer quality of life for patients than a successful kidney
transplant, because of its recurrent nature.
Taking into account both types of treatment, the proportion
of people treated for end-stage renal failure has increased at
a rate of over 5% per year on average across OECD countries
over the past two decades. This means that the prevalence
of treatment for ESRF has more than doubled since 1990.
Japan and the United States have the highest rates, with
190 and 180 ESRF patients per 100 000 population respectively (Figure 4.8.1). They are followed by Portugal which has
registered one of the highest growth rates since 1990. It is
not clear why these countries report such high rates of treatment, but it does not seem to be solely related to a higher
prevalence of diabetes, which is not particularly higher in
these countries compared with other OECD countries (see
Indicator 1.10 “Diabetes prevalence and incidence”).
In most OECD countries, a majority of ESRF patients are
being treated through dialysis as opposed to receiving a
kidney transplant. This is because while the prevalence of
people suffering from end-stage renal failure has strongly
increased, the number of transplants is limited by the
number of donors. The exceptions are Finland, Iceland, the
Netherlands and Ireland, where most ESRF patients have
received a kidney transplant.
The proportion of people undergoing dialysis is much
higher in Japan and the United States (Figure 4.8.2). In
Japan, nearly all ESRF patients are treated through dialysis,
with very low rates of kidney transplants. In all countries,
there has been a large rise in the number of persons
undergoing dialysis over the past 20 years, with the OECD
average more than doubling.
94
Given the supply constraints, kidney transplants are
normally performed on patients with end-stage renal
failure when these persons cannot live without difficult
dialysis sessions. When successful, these transplants
greatly improve quality of life, without strict diet and
activity limitation. Advances in surgical techniques and the
development of new drugs preventing rejection have made
it possible to carry out more transplants, and to improve
their rate of success, than was the case 20 years ago. The
prevalence of people living with a functioning kidney transplant has steadily increased since 1990 in all countries with
available data. The OECD average more than doubled, rising
from 15 to 36 people per 100 000 population between 1990
and 2009 (Figure 4.8.3). In 2009, Portugal, the United States,
the Netherlands and Austria reported the highest rates of
people with a functioning kidney transplant. On the other
hand, the proportion of people having received a kidney
transplant was the lowest in Japan, followed by the Slovak
Republic, Greece and Korea.
In many countries, waiting lists to receive a kidney transplant have increased, as the demand for transplants has
greatly outpaced the number of donors. The rate of transplants is also affected by cultural factors and traditions;
transplants may still be less accepted in certain countries
such as Japan.
Definition and comparability
The number of patients treated for end-stage renal
failure (ESRF) refers to the number of patients who are
receiving different forms of renal replacement therapy:
haemodialysis/haemoinfiltration, intermittent peritoneal dialysis, continuous ambulatory peritoneal
dialysis, continuous cyclical peritoneal dialysis, or
living with a functioning kidney transplant.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.8. Treatment of renal failure (dialysis and kidney transplants)
4.8.1 Prevalence of patients treated for end-stage renal failure, 2009 and change between 1990 and 2009
2009 (or nearest year)
Dialysis
Change 1990-2009
(or nearest year)
Functioning kidney transplants
Japan (2003)
United States
Portugal
Canada
Germany
Israel
Belgium
Greece
Korea
OECD
Austria
France
Czech Republic
Spain
Hungary
New Zealand
Netherlands
Denmark
Australia
Ireland
Finland
United Kingdom
Slovak Republic
Iceland
190.4
180.2
150.6
113.1
111.3
110.4
107.2
106.5
101.8
101.7
97.5
97.5
97.1
94.0
89.2
84.9
84.7
84.6
83.2
78.6
78.1
78.0
66.8
53.9
200
150
100
Number of patients per 100 000 population
50
0
n.a.
5.0
7.9
5.6
6.7
5.3
5.3
5.4
n.a.
5.4
4.2
4.7
n.a.
5.0
9.9
5.0
4.3
4.9
4.4
n.a.
4.7
4.9
n.a.
4.7
0
2
4
6
8
10
Average annual growth rate (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524830
4.8.2 Prevalence of patients undergoing dialysis,
1990 and 2009 (or nearest year)
1990
Japan (2003)
United States
Portugal
Greece
Germany
Korea
Italy
Turkey
Poland
Israel
Canada
OECD
Hungary
Belgium
Czech Republic
Luxembourg
New Zealand
France
Slovak Republic
Austria
Spain
Denmark
Australia
Mexico
United Kingdom
Ireland
Netherlands
Finland
Iceland
2009
125.7
1990
186.3
96.1
85.0
80.7
78.6
76.5
74.7
71.9
70.4
66.9
65.2
64.0
63.0
61.1
61.0
52.4
52.1
51.8
49.9
49.6
48.0
47.1
47.1
41.7
37.2
36.8
32.1
19.1
0
50
100
150
200
Number of patients per 100 000 population
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524849
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4.8.3 Prevalence of patients living with a functioning
kidney transplant, 1990 and 2009 (or nearest year)
Portugal
United States
Netherlands
Austria
Canada
Finland
France
Spain
Belgium
Ireland
Israel
Denmark
OECD
United Kingdom
Australia
Czech Republic
Iceland
New Zealand
Germany
Estonia
Hungary
Korea
Greece
Slovak Republic
Japan (2003)
2009
54.5
54.5
47.9
47.6
46.3
46.0
45.3
44.4
44.2
41.4
40.0
36.6
36.4
36.3
36.1
35.9
34.8
32.5
30.6
29.5
25.2
23.3
21.5
15.0
4.1
0
15
30
45
60
Number of patients per 100 000 population
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524868
95
4. HEALTH CARE ACTIVITIES
4.9. Caesarean sections
Rates of caesarean delivery as a percentage of all live births
have increased in all OECD countries in recent decades,
although in a few countries this trend has reversed over the
past few years. Reasons for the increase include reductions
in the risk of caesarean delivery, malpractice liability
concerns, scheduling convenience for both physicians and
patients, and changes in the physician-patient relationship, among others. Nonetheless, caesarean delivery
continues to result in increased maternal mortality,
maternal and infant morbidity, and increased complications for subsequent deliveries (Minkoff and Chervenak,
2003; Bewley and Cockburn, 2002; Villar et al., 2006). These
concerns, combined with the greater financial cost (the
average cost associated with a caesarean section is at least
two times greater than a normal delivery in many OECD
countries; Koechlin et al., 2010), raise questions about the
appropriateness of some caesarean delivery that may not
be medically required.
In 2009, caesarean section rates were the lowest in the
Netherlands (14% of all live births), and were relatively low
also in many Nordic countries (Finland, Iceland, Norway
and Sweden). In the Netherlands, home births are a
common option for women with low-risk pregnancies, and
30% of all births occurred at home in 2004 (Euro-Peristat,
2008). Among OECD countries, caesarean section rates
were highest in Turkey and Mexico (at over 40%), but the
rates were even higher in some major non-member
countries such as Brazil and China. The average rate across
OECD countries was 26% (Figure 4.9.1).
Caesarean rates have increased rapidly over the past two
decades in most OECD countries (Figure 4.9.2). The increase
temporarily slowed during the 1990s in some OECD
countries such as Canada and the United States, as a result
of changes in obstetrical practice including trial of normal
labor and delivery after a woman has had a previous
caesarean to reduce the number of repeat caesareans
(Lagrew and Adashek, 1998). But caesarean rates soon
resumed their upward trend, due in part to reports of
complications from trial of labour and continued changes in
patient preferences (Sachs et al., 1999). Other trends, such as
increases in first births among older women and the rise in
multiple births resulting from assisted reproduction, also
contributed to the global rise in caesarean deliveries.
On average across OECD countries, caesarean rates
increased from 14% of all births in 1990 to nearly 20%
in 2000 and 26% in 2009. The growth rate since 2000 has
96
been particularly rapid in Denmark, the Czech Republic,
Poland and the Slovak Republic. Finland and Iceland are the
only two OECD countries that have slightly reversed the
trend of rising caesarean rates since 2000.
The continued rise in caesarean deliveries is only partly
related to changes in medical indications. A study of
caesarean delivery trends in the United States found that
the proportion of “no indicated risk” caesareans rose from
3.7% of all births in 1996 to 5.5% in 2001 (Declercq et al.,
2005). In France, a 2008 study by the French Hospital
Federation found higher caesarean rates in private for-profit
facilities than in public facilities, even though the latter are
designed to deal with more complicated pregnancies (FHF,
2008). A review of caesarean delivery practice in Latin
American countries in the late 1990s found similarly higher
caesarean rates in private hospitals (Belizan et al., 1999).
While caesarean delivery is required in some circumstances, the benefits of caesarean versus vaginal delivery
for normal uncomplicated deliveries continue to be
debated. Professional associations of obstetricians and
gynaecologists in countries such as Canada now encourage
the promotion of normal childbirth without interventions
such as caesarean sections (Society of Obstetricians and
Gynaecologists of Canada et al., 2008).
Definition and comparability
The caesarean section rate is the number of caesarean
deliveries performed per 100 live births.
In Portugal, the denominator is limited to the number
of live births which took place in National Health
Service Hospitals on the mainland, resulting in an
over-estimation of caesarean rates. In Mexico, the
number of caesarean sections is estimated based on
public hospital reports and data obtained from
National Health Surveys. Estimation is required to
correct for under-reporting of caesarean deliveries in
private facilities. The combined number of caesarean
deliveries is then divided by the total number of live
births as estimated by the National Population Council.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.9. Caesarean sections
4.9.1 Caesarean sections per 100 live births, 2009 and change between 2000 and 2009
2009 (or nearest year)
Change 2000-09 (or nearest year)
Netherlands
Finland
Iceland
Norway
Sweden
Belgium
India
Slovenia
Russian Federation
Israel
France
Denmark
Estonia
Czech Republic
South Africa
Poland
United Kingdom
New Zealand
Spain
OECD
Ireland
Canada
Slovak Republic
Austria
Luxembourg
Germany
Australia
United States
Switzerland
Hungary
Portugal
Korea
Italy
Mexico
Turkey
China
Brazil
14.3
15.7
15.8
17.1
17.1
17.3
17.8
17.8
18.0
18.8
20.0
20.6
20.7
21.2
21.3
22.8
23.7
24.0
24.9
25.8
26.0
26.6
27.0
28.6
29.7
30.3
30.8
32.3
32.4
32.5
33.0
35.1
38.4
42.0
42.7
46.2
47.4
50
40
Per 100 live births
30
20
10
0
2.4
-0.1
-1.3
2.8
2.1
0.8
n.a.
5.5
n.a.
1.8
1.7
5.4
4.0
5.7
n.a.
6.4
1.9
1.9
1.7
3.2
2.5
3.1
7.0
5.8
3.4
4.2
3.7
4.4
4.3
n.a.
3.7
0.5
1.6
4.5
n.a.
n.a.
n.a.
-3
0
3
6
9
Average annual growth rate (%)
Source: OECD Health Data 2011; WHO (2008a).
1 2 http://dx.doi.org/10.1787/888932524887
4.9.2 Caesarean sections per 100 live births, 1990-2009 (or nearest year)
1990
2000
2009
33.0
32.5
32.4
32.3
30.8
30.3
29.7
28.6
27.0
26.6
26.0
25.8
24.0
23.7
22.8
21.2
20.7
20.6
20.0
18.8
17.8
17.3
17.1
17.1
15.8
14.3
20
15.7
30
24.9
42.7
38.4
40
35.1
42.0
Per 100 live births
50
10
d
Ic
an
nl
Fi
el
an
No d
rw
a
Sw y
ed
B e en
lg
iu
Sl m
ov
en
ia
Is
ra
e
Fr l
an
De c e
nm
ar
Cz
Es k
ec
to
h
Re ni a
pu
bl
ic
Un
i te Pol
a
d
K i nd
Ne ngd
o
w
Ze m
al
an
d
Sp
a in
OE
CD
Ir e
la
nd
Sl
ov C a
ak na
Re d a
pu
bl
i
Au c
Lu
st
xe
ria
m
bo
u
Ge rg
rm
an
A
y
Un us tr
i t e a li
a
d
S
Sw t at
e
it z
s
er
la
n
Hu d
ng
a
Po r y
r tu
ga
l
Ko
re
a
It a
ly
M
ex
ic
o
Tu
rk
ey
Ne
th
er
la
nd
s
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524906
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
97
4. HEALTH CARE ACTIVITIES
4.10. Cataract surgeries
In the past two decades, the number of surgical procedures
carried out on a same-day basis, without any need for hospitalisation, has grown in most OECD countries. Advances
in medical technologies, particularly the diffusion of less
invasive surgical interventions, and better anaesthetics
have made this development possible. These innovations
have also improved patient safety and health outcomes for
patients, and have in many cases helped to reduce the unit
cost per intervention by shortening the length of stay in
hospitals. However, the impact of the rise in same-day
surgeries on health spending depends not only on changes
in their unit cost, but also on the growth in the sheer
number of procedures performed, and needs to take into
account any additional cost related to post-acute care and
community health services.
Cataract surgery provides a good example of a high-volume
surgery which is now carried out predominantly on a
same-day basis in most OECD countries. Day surgery now
accounts for over 90% of all cataract surgeries in a majority
of countries (Figure 4.10.1). However, the use of day surgery
is still relatively low in some countries, such as Poland, the
Slovak Republic and Hungary. This may be explained by
more advantageous reimbursement for inpatient stays,
national regulations, and obstacles to changing individual
practices of surgeons and anaesthetists (Castoro et al.,
2007), but these low rates may also reflect limitations in
data coverage (the lack of registration of day surgeries
carried outside hospitals in Poland).
The number of cataract surgeries performed on a same-day
basis has grown very rapidly over the past decade in many
countries. In France, the share rose from 32% in 2000 to 78%
in 2009. In Portugal, it has grown at a rate of over 50% per
year since 2000 (Figure 4.10.2). Whereas less than 10% of
cataract surgeries in Portugal were performed on a sameday basis in 2000, this proportion increased to 92% in 2009.
In Luxembourg also, the number of cataract surgeries
carried out as day cases has risen rapidly over the past
decade, although they still account for only one-quarter of
all cataract surgeries. In Norway, the growth in cataract
surgeries performed as day cases since 2000 substituted for
some that previously required hospitalisation; the overall
number of procedures remained constant, but the share of
day case surgeries increased from 87% to 97%.
98
The total number of cataract surgeries has also grown
substantially over the past decade, so that it has now
become the most frequent surgical procedure in many
OECD countries. Population ageing is one of the factors
behind this rise, but the proven success, safety and costeffectiveness of cataract surgery as a day procedure has
been a more important factor (Fedorowicz et al., 2004). In
Sweden, there is evidence that cataract surgeries are now
being performed on patients suffering from less severe
vision problems compared to ten years ago. This raises the
question of how the needs of these patients should be
prioritised relative to other patient groups (Swedish
Association of Local Authorities and Regions and National
Board of Health and Welfare, 2010).
Definition and comparability
Cataract surgeries consist of removing the lens of the
eye because of the presence of cataracts and replacing
it with an artificial lens. The surgery may be carried
out as a day case or as an inpatient case (involving an
overnight stay in hospital). Although same-day interventions may either be performed in a hospital or in a
clinic, the data for many countries (e.g. Ireland,
Hungary, the Netherlands, Poland) only include interventions carried out in hospitals. Caution is therefore
required in making cross-country comparisons, given
the different coverage of day surgeries in several
countries.
The data for Denmark only include cataract surgeries
carried out in public hospitals, excluding procedures
carried out in the ambulatory sector and in private
hospitals. In Ireland too, the data cover only procedures in public hospitals. It is estimated that over
10% of all hospital activity in Ireland is undertaken in
private hospitals. The data for Spain only partially
include the activities in private hospitals.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.10. Cataract surgeries
4.10.1 Share of cataract surgeries carried out as day cases, 2000 and 2009 (or nearest year)
74.2
78.0
78.9
61.7
68.1
65.2
71.2
80
79.6
79.6
85.4
85.3
91.9
92.5
93.6
2009
84.1
94.5
95.3
90.5
96.0
87.3
96.9
83.1
97.6
98.0
98.3
98.8
99.4
82.0
82.8
99.9
98.2
99.6
92.8
97.1
2000
% of total cataract surgeries
100
23.9
24.4
31.5
32.0
40
33.8
37.6
41.6
52.7
60
4.1
9.3
13.7
14.3
20
Po
la
bl
pu
ov
ak
Re
nd
ic
y
Hu
ng
ar
g
ur
ia
bo
en
m
ov
Sl
Sl
Un
Cz
ec
Lu
xe
M
ex
ic
o
el
Is
ra
ce
Fr
an
bl
pu
h
Re
er
it z
ic
nd
la
nd
Ir e
la
17
Sw
Po
OE
CD
It a
ly
l
r tu
ga
m
d
iu
Be
Ic
lg
el
an
li a
a in
st
Au
w
i te
Ne
d
ra
d
Sp
ay
an
Ze
No
al
ed
rw
en
m
Ki
Sw
ng
do
ar
nm
la
er
De
th
Ne
i te
Un
k
s
nd
d
a
an
Fi
nl
to
ni
da
na
Es
d
Ca
St
at
es
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524925
4.10.2 Trends in cataract surgeries, inpatient and day cases, 2000-09 (or nearest year)
Day cases
Inpatient cases
Average annual growth rate in cataract surgeries per capita (%)
60
54.1
50
40
34.7
30
20
14.4
13.4
9.9
10
9.8
9.4
8.3
7.9
5.7
4.9
4.9
4.8
4.7
3.7
3.5
1.0
0.5
0
-4.9
-5.9
-10
-8.6
-5.4
-8.8
-9.4
-12.7
-13.5
-12.6
-14.8
-16.5
-20
-16.7
-20.6
-24.9
ay
No
rw
o
M
ex
ic
d
an
nl
Fi
da
na
al
Ze
Ne
w
Ca
an
d
li a
ra
st
la
er
it z
Sw
Au
nd
en
ed
Sw
ar
nm
De
la
er
th
Ne
k
s
nd
nd
la
Ir e
Be
lg
iu
m
el
ra
Is
ce
an
Fr
bo
m
xe
Lu
Po
r tu
ur
ga
g
l
-30
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524944
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
99
4. HEALTH CARE ACTIVITIES
4.11. Pharmaceutical consumption
The consumption of pharmaceuticals is increasing across
OECD countries, not only in terms of expenditure (see
Indicator 7.4 “Pharmaceutical expenditure”), but also the
volume or quantity of drugs consumed. One of the factors
contributing to this rise is a growing demand for drugs to
treat ageing-related diseases. However, the rise in pharmaceutical consumption is also observed in countries with
younger populations, indicating that other factors, such as
physicians’ prescription habits, also play a role.
This section discusses the volume of consumption of
four categories of pharmaceuticals: antidiabetics, antidepressants, anticholesterols and antibiotics. Consumption of these drugs is measured through the defined daily
dose (DDD) unit, as recommended by the WHO Collaborating Center for Drug Statistics (see the box on “Definition
and comparability”).
There is much variation in the use of drugs for the treatment of diabetes, with consumption in Iceland and Estonia
almost half that in Finland or Germany (Figure 4.11.1). This
is partly explained by the prevalence of diabetes, which is
low in Iceland and higher in Germany (see Indicator 1.10
“Diabetes prevalence and incidence”). However, some of
the highest consumers are not countries with high diabetes
prevalence. Between 2000 and 2009, the consumption of
antidiabetics increased by 75% on average across all
countries. The growth rate was particularly strong in the
Slovak Republic (although from a low level), Portugal,
Germany and Finland. Reasons apart from a rising prevalence of diabetes are increases in the proportion of people
treated, and the average dosages used in treatments
(Melander et al., 2006).
Iceland reports the highest level of consumption of antidepressants, followed by Australia, Denmark and Sweden
(Figure 4.11.2). Variations in consumption across countries
may be due to differences in the prevalence of depression.
For example, according to the WHO World Mental Health
Surveys, self-reported prevalence of depression in France
was about twice that in Germany in the mid-2000s (Kessler
and Üstün, 2008) which may partly explain the higher
consumption in France. However, country differences in
drug prescription guidelines and behaviors also contribute.
In France, the increase in antidepressant consumption has
been associated with a longer duration in pharmaceutical
treatments, although the inappropriate use of antidepressants has also been identified as a contributing
factor (Grandfils and Sermet, 2009). The consumption of
antidepressants has grown substantially in all countries
over the past decade, by over 60% on average.
Anticholesterol consumption ranges from a high of
126 DDDs per 1 000 people per day in Australia to a low
of 21 in Estonia (Figure 4.11.3). While this might partly
100
reflect differences in the prevalence of cholesterol levels in
the population, again, differences in clinical guidelines for
the control of bad cholesterol also play a role. Guidelines in
Australia target lower bad cholesterol levels than those in
European countries; and differences also exist in target
levels within Europe (National Heart Foundation of
Australia et al., 2005; Hockley and Gemmill, 2007). Both the
epidemiological context – for instance, growing obesity –
and increased screening and treatment explain the very
rapid growth in the consumption of anticholesterols across
OECD countries.
The consumption of antibiotics varies from 11 DDDs per
1 000 people per day in the Netherlands to 39 in Greece
(Figure 4.11.4). Since over-consumption of antibiotics has
been linked to bacterial resistance, many countries have
launched information campaigns targeting physicians and
patients in order to reduce consumption. Consumption has
stabilised in many countries and decreased in others such as
Estonia, Slovenia, Hungary, Portugal, the Slovak Republic
and France. In contrast, consumption has risen in countries
that had below-average levels in 2000, such as the
Netherlands, Austria and Denmark, as well as in Greece.
Definition and comparability
Defined daily dose (DDD) is the assumed average
maintenance dose per day for a drug used for its main
indication in adults. DDDs are assigned to each active
ingredient(s) in a given therapeutic class by international expert consensus. For instance, the DDD for
oral aspirin equals 3 grams, which is the assumed
maintenance daily dose to treat pain in adults. DDDs
do not necessarily reflect the average daily dose
actually used in a given country. DDDs can be aggregated within and across therapeutic classes of the
Anatomic-Therapeutic Classification (ATC). For more
detail, see www.whocc.no/atcddd.
Data generally refer to outpatient consumption
except for the Czech Republic, Finland and Sweden,
where data also include hospital consumption. Greek
figures may include parallel exports.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
4. HEALTH CARE ACTIVITIES
4.11. Pharmaceutical consumption
4.11.1 Antidiabetics consumption,
2000 and 2009 (or nearest year)
2000
Iceland
Estonia
Denmark
Norway
Slovak Republic
Sweden
Slovenia
Australia
Belgium
OECD
Spain
Hungary
Luxembourg
Czech Republic
France
Netherlands
Korea
Portugal
United Kingdom
Germany
Finland
4.11.2 Antidepressants consumption,
2000 and 2009 (or nearest year)
2009
2000
28.9
36.0
44.4
47.1
50.0
50.0
54.3
54.6
54.8
58.5
62.0
62.4
62.8
64.6
65.7
65.9
68.1
69.1
70.5
79.4
79.9
0
20
40
60
80
100
Defined daily dose, per 1 000 people per day
Source: OECD Health Data 2011.
4.11.3 Anticholesterols consumption,
2000 and 2009 (or nearest year)
2000
71.5
Spain
74.0
Slovenia
74.1
Czech Republic
76.3
OECD
85.3
Netherlands
89.4
Iceland
89.5
Portugal
90.3
Finland
91.2
France
91.7
Luxembourg
95.6
Slovak Republic
97.3
Hungary
98.1
Denmark
99.4
Norway
104.0
Belgium
110.0
United Kingdom
121.1
Australia
125.9
0
27.0
38.1
40.1
41.8
43.2
48.6
49.8
52.5
55.5
57.7
60.9
66.4
66.9
71.9
74.1
78.2
79.9
98.3
0
20
40
60
80
100
Defined daily dose, per 1 000 people per day
1 2 http://dx.doi.org/10.1787/888932524982
2000
62.3
Sweden
25.5
2009
27.0
Germany
14.4
4.11.4 Antibiotics consumption,
2000 and 2009 (or nearest year)
20.5
Korea
10.8
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932524963
Estonia
Korea
Estonia
Hungary
Slovak Republic
Czech Republic
Netherlands
Germany
Slovenia
Luxembourg
France
OECD
Norway
Spain
United Kingdom
Finland
Belgium
Portugal
Sweden
Denmark
Australia
Iceland
2009
50
100
150
Defined daily dose, per 1 000 people per day
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525001
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
Netherlands
Estonia
Slovenia
Germany
Norway
Sweden
Austria
Denmark
Hungary
United Kingdom
Finland
Czech Republic
Spain
Ireland
OECD
Iceland
Israel
Portugal
Australia
Poland
Slovak Republic
Korea
Belgium
Luxembourg
Italy
France
Greece
2009
11.4
13.2
14.4
14.9
15.2
15.8
15.9
16.0
16.0
17.3
18.0
19.4
19.7
20.8
21.1
21.7
22.4
22.9
23.6
23.6
26.3
26.9
27.5
28.2
28.7
29.6
38.6
0
10
20
30
40
Defined daily dose, per 1 000 people per day
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525020
101
5. QUALITY OF CARE
Care for chronic conditions
5.1.
Avoidable admissions: Respiratory diseases
5.2.
Avoidable admissions: Uncontrolled diabetes
Care for acute exacerbation of chronic conditions
5.3.
In-hospital mortality following acute myocardial infarction
5.4.
In-hospital mortality following stroke
Patient safety
5.5.
Obstetric trauma
5.6.
Procedural or postoperative complications
Care for mental disorders
5.7.
Unplanned hospital re-admissions for mental disorders
Cancer care
5.8.
Screening, survival and mortality for cervical cancer
5.9.
Screening, survival and mortality for breast cancer
5.10. Survival and mortality for colorectal cancer
Care for communicable diseases
5.11. Childhood vaccination programmes
5.12. Influenza vaccination for older people
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
103
5. QUALITY OF CARE • CARE FOR CHRONIC CONDITIONS
Care for chronic conditions
5.1. Avoidable admissions: Respiratory diseases
Chronic conditions like asthma and chronic obstructive
pulmonary disease (COPD) are either preventable or
manageable through proper prevention or primary care
interventions. Proper management of these chronic conditions in primary care settings can reduce exacerbation and
costly hospitalisation. Hospital admission rates serve as a
proxy for primary care quality, so high admission rates may
point to poor care co-ordination or care continuity. They
may also indicate structural constraints such as the supply
of family physicians (AHRQ, 2009; Starfield et al., 2005).
Females have consistently higher rates for asthma admissions compared to males. On average, the female admission rate is 85% higher. Recent research shows that the
incidence of asthma among women has increased and
“that asthmatic women have poorer quality of life and
increased utilisation of health care compared to males
despite having similar medical treatment and baseline
pulmonary function” (Kynyk et al., 2011). The admission
rate differences may therefore highlight the need for more
effective and targeted care in primary care settings.
Asthma is a condition that affects the airways that carry air
in and out of the lungs. Asthma symptoms are usually
intermittent and treatment can be highly effective, even
often reversing the effects of bronchial irritation. COPD, on
the other hand, is a progressive disease and people who
have COPD usually have a smoking history. Many people
with COPD respond well to bronchodilators but not to the
same extent that asthmatics do.
The gender specific breakdown for COPD is a mirror image
of the asthma figure with males having consistently higher
admission rates than females (except for Denmark,
Iceland, Norway and Sweden). On average, males have an
admission rate that is around 53% higher than females.
This is partly due to higher incidence and prevalence of
COPD among men associated with higher smoking rates.
Asthma is a very common chronic condition affecting
between 150 to 300 million people worldwide and causing
some 250 000 deaths globally each year (WHO, 2011b). It is
estimated that around 30 million people have asthma in
the European region (Masoli et al., 2004). COPD affects
around 64 million worldwide and currently is the fourth
leading cause of death (WHO, 2011c). In Europe, COPD kills
between 200 000 to 300 000 people each year and its
economic burden is estimated to be EUR 102 billion per
year (European Lung Foundation, 2011).
Figures 5.1.1 and 5.1.2 show an 11-fold difference in hospital
admission rates for asthma and a five-fold difference for
COPD between the highest and lowest country rates. For
asthma, the Slovak Republic, the United States and Korea all
have rates that are around double the OECD average.
Conversely, Portugal, Canada, Mexico, Italy, Sweden and
Germany have rates that are less than half the OECD average.
The high admission rates for the United States and Korea
have persisted over time. Both countries face similar
problems in terms of a less developed primary care system
with deficits in the supply of family physicians (American
Academy of Family Physicians, 2009; Macinko et al., 2007;
Kwon et al., 2010; Cho and Rho, 2003).
104
Ireland, New Zealand, Australia and Austria all have high
admission rates for COPD relative to the OECD average. In
Ireland, this high admission rate is associated with high
smoking prevalence, a major risk factor for COPD. Portugal,
France and Switzerland have rates that are less than half
the OECD average.
Definition and comparability
The asthma and COPD indicators are defined as the
number of hospital discharges of people aged 15 years
and over per 100 000 population, adjusted to take
account of the age and sex composition of each
country’s population structure. Differences in diagnosis
and coding between asthma and COPD across countries
may limit the precision of the specific disease rates.
Differences in disease classification systems, for
example between ICD-9 CM and ICD-10 AM, may also
affect the comparability of the data.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CARE FOR CHRONIC CONDITIONS
5.1. Avoidable admissions: Respiratory diseases
5.1.1 Asthma hospital admission rates, population aged 15 and over, 2009 (or nearest year)
Female
Portugal
Canada
Mexico
Italy
Sweden
Germany
Netherlands
Switzerland
Iceland
Hungary
Denmark
Czech Republic
Slovenia
France
Ireland
Spain
Norway
Belgium
OECD
Austria
Australia
Israel
Poland
United Kingdom
Finland
New Zealand
Korea
United States
Slovak Republic
15.1
15.7
19.0
19.2
19.3
20.8
27.5
30.9
33.3
35.0
36.5
37.0
38.1
43.4
43.5
43.9
47.6
48.4
51.8
52.8
66.6
68.4
68.9
73.7
75.9
80.7
101.5
120.6
166.8
200
150
Rates per 100 000 population
100
50
0
20
10
21
9
27
11
24
14
25
13
26
15
38
17
38
23
42
23
43
26
48
24
47
26
43
33
54
32
58
28
61
23
64
27
60
35
66
36
59
46
38
45
51
46
54
48
93
73
116
0
Male
93
89
85
100
95
112
110
164
216
60
120
180
240
Rates per 100 000 population
Note: Rates are age-sex standardised to 2005 OECD population. 95% confidence intervals are represented by H.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525039
5.1.2 COPD hospital admission rates, population aged 15 and over, 2009 (or nearest year)
Female
91
111
114
126
137
139
146
149
154
183
198
201
206
213
217
222
228
229
230
234
243
248
277
310
312
319
364
400
300
Rates per 100 000 population
200
100
45
107
48
123
71
123
106
123
65
84
143
137
43
84
105
136
167
164
159
135
203
136
159
173
241
229
157
266
202
284
238
280
305
324
Portugal
France
Switzerland
Mexico
Slovenia
Italy
Sweden
Spain
Finland
Czech Republic
Netherlands
Canada
OECD
Germany
Slovak Republic
United Kingdom
Poland
Korea
Belgium
Iceland
United States
Israel
Norway
Hungary
Denmark
Austria
Australia
New Zealand
Ireland
71
79
0
0
100
Male
185
187
276
241
209
189
215
251
259
303
233
330
318
308
226
236
333
207
310
275
397
370
354
437
200
300
400
500
Rates per 100 000 population
Note: Rates are age-sex standardised to 2005 OECD population. 95% confidence intervals are represented by H.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525058
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
105
5. QUALITY OF CARE • CARE FOR CHRONIC CONDITIONS
5.2. Avoidable admissions: Uncontrolled diabetes
Diabetes is one of the most significant non-communicable
diseases globally, and is also a leading cause of mortality. In
the United States for example, where there are an estimated 26 million diabetics, diabetes was a contributory
factor to around 230 000 deaths in 2007. In Europe, an estimated 55 million people live with diabetes. Across the
world, the population of diabetics is expected to rise from
285 million in 2010 to 438 million by 2030 (IDF, 2009) (see
also Indicator 1.10, “Diabetes prevalence and incidence”).
Austria has taken steps to improve diabetes care via its
disease management programme (DMP) which was implemented in 2007. Findings from a recent study showed that
the Austrian diabetes DMP improved process quality and
enhanced weight loss, but did not significantly improve
diabetes control (Sönnichsen et al., 2010). The same
research also noted that quality depends more on the care
offered by a specific family physician than on the widespread implementation of a programme.
Diabetes is implicated in cardiovascular disease, hypertension, kidney disease and lower limb amputation. It is also
the leading cause of blindness in industrialised countries
and the most common cause of end-stage renal disease in
the United States, Europe, and Japan. Furthermore, studies
have shown that people who have diabetes are more likely
to have depression and find it more difficult to follow
treatment guidelines (Mezuk et al., 2008; Egede, 2004).
In Korea, the high rate of admissions can only be partly
explained by higher diabetes prevalence related to changing
lifestyle brought about by recent economic development
(Cho, 2010). It is also linked to a less developed primary care
infrastructure (Chun et al., 2009).
Major risk factors for diabetes include being overweight or
obese, physically inactive, having familial history of
diabetes, having high blood pressure and having a history
of cardiovascular disease. The multi-centre Diabetes
Prevention Program (DPP, 2002) showed that modest weight
loss and dietary changes can delay or even prevent the
onset of diabetes. Researchers in the DPP trial also found
that intensive counselling on effective diet, exercise, and
behaviour modification reduced the risk of developing
diabetes by almost 60%. This finding applied to all ethnic
groups, and for both males and females. These lifestyle
changes had their greatest impact on older age groups
where the interventions led to a 70% reduction in risk.
These findings underline the importance of having
diabetes prevention and management programmes
embedded in primary care settings.
Figure 5.2.1 shows that there are large variations in admission rates for uncontrolled diabetes across OECD countries.
Austria, Hungary, Korea and Mexico have rates that are more
than double the OECD average. Spain, Israel, Australia
and New Zealand have very low admissions rates for
uncontrolled diabetes. Despite having high disease prevalence, Canada has moderately low admission rates. This
may be indicative of the impact of Canada’s Integrated
Strategy on Health Living and Chronic Disease and the
Canadian Diabetes Strategy (PHAC, 2005). Male admission
rates for uncontrolled diabetes are around 20% higher than
females, though several countries, notably Finland, Sweden
and Denmark, have considerably higher male admission
rates compared to females.
106
Figure 5.2.2 shows that uncontrolled diabetes admission
rates do not appear to be strongly correlated with diabetes
prevalence, with some countries such as Canada, Portugal
and the United States having high prevalence rates but
low admission rates. Conversely, Finland, Sweden and
Denmark have lower prevalence rates but higher admission
rates. The absence of any meaningful correlation suggests
that factors other than disease “volume” are at play when
explaining hospital admissions.
Definition and comparability
The indicator for uncontrolled diabetes is defined as
the number of hospital discharges of people aged
15 years and over with diabetes Type I or II without
mention of a short-term or long-term complication
per 100 000 population. The rates have been adjusted
to take account of the age and sex composition of
each country’s population structure. Differences in
coding practices between countries may affect the
comparability of data. Variations in disease classification systems, for example between ICD9-CM and
ICD10-AM, may also affect comparability.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CARE FOR CHRONIC CONDITIONS
5.2. Avoidable admissions: Uncontrolled diabetes
5.2.1 Uncontrolled diabetes hospital admission rates, population aged 15 and over, 2009 (or nearest year)
Female
Israel
7.5
Australia
7.6
New Zealand
Canada
15.2
16.3
18.8
Switzerland
16
17
22
27
United Kingdom
20
Czech Republic
28
32.4
Ireland
27
33.1
Italy
30
23.9
16
17
21
31.4
21
28
34
39
36
Slovenia
40
Norway
42
50.3
OECD
46
50.3
Germany
46
65.4
Denmark
54
65.9
Poland
61
66.0
Sweden
53
Finland
67
42.0
46.7
78.3
108.9
127.5
129.2
100
16
United States
21.2
200
150
Rates per 100 000 population
Portugal
Iceland
20.4
187.9
3
4
6
9
7
9
6
9
14
Spain
3.3
7.0
50
44
50
54
54
77
70
82
90
Mexico
122
Korea
115
Hungary
128
Austria
163
0
Male
0
93
137
130
55
110
211
165
220
Rates per 100 000 population
Note: Rates are age-sex standardised to 2005 OECD population. 95% confidence intervals are represented by H.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525077
5.2.2 Uncontrolled diabetes hospital admission rates and prevalence of diabetes, 2009 (or nearest year)
Admissions per 100 000 population
140
R 2 = 0.05
120
KOR
MEX
100
80
FIN
SWE
60
POL
DNK
NOR
40
SVN
IRL
20
GBR
ISL
CAN
NZL
2
4
PRT
USA
ISR
0
0
DEU
ITA
6
8
10
12
Prevalence of diabetes (%)
Note: Prevalence estimates of diabetes refer to adults aged 20-79 years and data are age-standardised to the World Standard Population. Hospital
admission rates refer to the population aged 15 and over and are age-standardised to 2005 OECD population.
Source: IDF (2009) for prevalence estimates; OECD Health Data 2011 for hospital admission rates.
1 2 http://dx.doi.org/10.1787/888932525096
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
107
5. QUALITY OF CARE • CARE FOR ACUTE EXACERBATION OF CHRONIC CONDITIONS
Care for acute exacerbation of
chronic conditions
5.3. In-hospital mortality following acute myocardial infarction
Although coronary artery disease remains the leading
cause of death in most industrialised countries, mortality
rates have declined since the 1970s (see Indicator 1.3
“Mortality from heart disease and stroke”). Much of the
reduction can be attributed to lower mortality from AMI,
due to better treatment in the acute phase. Care for AMI
has changed dramatically in recent decades, with the introduction of coronary care units in the 1960s (Khush et al.,
2005) and with the advent of treatment aimed at rapidly
restoring coronary blood flow in the 1980s (Gil et al., 1999).
This success is all the more remarkable as data suggest
that the incidence of AMI has not declined for most countries (Goldberg et al., 1999; Parikh et al., 2009). However,
numerous studies have shown that a considerable proportion of AMI patients fail to receive evidence-based care
(Eagle et al., 2005).
AMI case-fatality rate is a good measure of acute care
quality because it reflects the processes of care for AMI,
such as effective medical interventions including thrombolysis, early treatment with aspirin and beta-blockers, and
co-ordinated and timely transport of patients. AMI casefatality rates have been used for hospital benchmarking in
several countries including Canada, Denmark, the United
Kingdom and the United States.
Crude and age-sex standardised in-hospital case-fatality
rates within 30 days of admission for AMI ranges widely,
with the lowest rates found in Denmark and Norway
(Figure 5.3.1). The highest rate is in Mexico, where annual
AMI mortality including deaths outside hospital is also the
highest. Mexican case-fatality data only refer to hospitals
in the public sector and the quality of pre-hospital emergency medical services is poor (Peralta, 2006), possibly
contributing to the high mortality rates in hospitals. Japan
has the second highest case-fatality rates although it has
the lowest AMI mortality. Beyond the quality of care
provided in hospitals, differences in hospital transfers,
average length of stay, emergency retrieval times and
average severity of AMI may influence reported 30-day
case fatality. The case-fatality rates for women are typically
higher than for men, but the gender difference is not statistically significant for most countries. There are, however,
some exceptions. Mexico has a large gender disparity,
suggesting room for improving the survival of female
patients with AMI.
Patient-based data, which follow patients in and out of
hospitals and across hospitals, is a more robust indicator
for international comparison as admission-based data may
108
bias case-fatality rates downwards if unstable cardiac
patients are commonly transferred to tertiary care centres
and the transfer is recorded as a live discharge in a country.
But it is only available for a relatively small group of
countries. With the exception of Denmark, the relative
performance of countries, measured by patient-based data,
is similar to admission-based data (Figure 5.3.1). New
Zealand and Sweden have a low case-fatality rate regardless of the measure used.
Case-fatality rates for AMI are decreasing over time, with
the majority of countries recording statistically significant
reductions between 2000 and 2009 (Figure 5.3.2). The
improvement is particularly marked in Nordic countries,
the Czech Republic, Ireland and Austria. Across countries,
improvements in AMI case-fatality rates reflect advances in
treatment such as the increased rates and timeliness of
reperfusion therapy, which seeks to restore blood flow to
the part of the heart muscle damaged during heart attack
(Fox et al., 2007; Tu et al., 2009).
Definition and comparability
In-hospital case-fatality rate following AMI is defined as
the number of people who die within 30 days of being
admitted (including same day admissions) to hospital
with an AMI. Ideally, rates would be based on individual
patients; however, only some countries have the ability
to track patients in and out of hospitals, across hospitals
or even within the same hospital because they do not
currently use a unique patient identifier. In order to
increase country coverage, this indicator is also
presented based on individual hospital admissions and
restricted to mortality within the same hospital, so
differences in practices in discharging and transferring
patients may influence the findings.
Both crude and age-sex standardised rates are presented for admission-based data. Standardised rates
adjust for differences in age (45+ years) and sex and
facilitate more meaningful international comparisons. Crude rates are likely to be more meaningful for
internal consideration by individual countries.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CARE FOR ACUTE EXACERBATION OF CHRONIC CONDITIONS
5.3. In-hospital mortality following acute myocardial infarction
5.3.1 Admission-based and patient-based in-hospital case-fatality rates within 30 days after admission for AMI,
2009 (or nearest year)
Admission-based rates (same hospital)
Age-sex standardised rate
Patient-based rates
(in and out of hospital)
Crude rate
21.5
Mexico
Japan
Belgium
Germany
Portugal
Korea
Slovak Republic
Austria
Spain
OECD
Netherlands
United Kingdom
Luxembourg
Finland
Slovenia
Switzerland
Israel
Czech Republic
Ireland
United States
Poland
Canada
Italy
Australia
New Zealand
Iceland
Sweden
Norway
Denmark
22.1
9.7
12.8
8.6
13.4
6.8
10.4
6.6
9.7
6.3
7.8
5.7
7.3
5.7
8.6
5.6
8.4
5.4
7.9
5.3
7.2
5.2
9.1
5.2
5.0
4.8
10.6
4.7
6.4
4.5
6.9
4.5
6.8
4.3
6.6
4.3
6.8
4.3
5.9
3.9
4.8
3.8
5.9
3.7
6.5
3.2
5.2
3.2
5.3
3.0
2.9
7.1
6.6
2.5
5.0
2.3
3.9
25
20
Rates per 100 patients
15
10
5
n.a.
n.a.
n.a.
n.a.
n.a.
7.6
n.a.
n.a.
n.a.
7.2
6.8
7.6
6.8
7.8
n.a.
n.a.
6.7
n.a.
n.a.
6.4
n.a.
n.a.
n.a.
5.4
n.a.
5.5
n.a.
6.9
0
0
5
10
15
20
25
Age-standardised rates per 100 patients
Note: Rates age-sex standardised to 2005 OECD population (45+). 95% confidence intervals represented by H.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525115
5.3.2 Reduction in in-hospital case-fatality rates within 30 days after admission for AMI, 2000-09 (or nearest year)
2000
2009
2005
Age-sex standardised rates per 100 patients
12
10
8
8.1
10.3
11.1
4.8
3.8
5.2
6.6
6.8
5.7
9.4
6.6
5.6
9.0
6.3
5.3
7.6
8.3
5.5
7.1
6.6
4.3
4.3
4.6
4.5
9.9
6.2
5.2
4.3
5.9
4.6
4.3
5.8
5.2
3.8
6.9
3.7
3.2
4.1
3.2
6.4
6.2
2.5
3.9
2.9
4.2
3.4
2.3
2
8.1
9.0
6.3
4
10.5
6
l
Po
r tu
ga
ria
st
Au
a in
Sp
s
la
er
th
m
xe
Lu
Ne
bo
ur
nd
g
d
an
Fi
nl
el
ra
pu
Re
h
ec
Is
bl
ic
nd
la
Ir e
Cz
CD
OE
es
Un
i te
d
Ca
St
na
at
da
li a
st
Au
al
Ze
w
Ne
ra
d
an
en
ed
Sw
rw
No
De
nm
ar
k
ay
0
Note: Rates age-sex standardised to 2005 OECD population (45+). 95% confidence intervals represented by H.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525134
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
109
5. QUALITY OF CARE • CARE FOR ACUTE EXACERBATION OF CHRONIC CONDITIONS
5.4. In-hospital mortality following stroke
Stroke and other cerebrovascular disease is the fourth most
common cause of death in OECD countries, accounting for
over 8% of all deaths on average (OECD, 2011a). Estimates
suggest that it accounts for 2-4% of health care expenditure
and also significant costs outside of the health care system
due to its impact on disability (OECD, 2003a). In ischemic
stroke, representing about 85% of cases, the blood supply to
a part of the brain is interrupted, leading to a necrosis of
the affected part, while in hemorrhagic stroke, the rupture
of a blood vessel causes bleeding into the brain, usually
causing more widespread damage.
Treatment for ischemic stroke has advanced dramatically
over the last decade. Until the 1990s, it was largely
accepted that the damage to the brain was irreversible and
treatment focused on prevention of complications and
rehabilitation. But following the spectacular improvements
in AMI survival rates that were achieved with early thrombolysis, clinical trials demonstrated clear benefits of
thrombolytic treatment for ischemic stroke in Japan (Mori
et al., 1992), the United States (e.g. NINDS, 1995) and
European countries (e.g. Hacke et al., 1995). Dedicated
stroke units were introduced in many countries, to facilitate timely and aggressive diagnosis and therapy for
ischemic and haemorrhagic stroke victims, achieving
better survival than after usual care (Seenan et al., 2007).
Stroke survival reflects quality of acute care, particularly
effective treatment methods such as thrombolysis and
prompt and adequate care delivery. Consequently, stroke
case-fatality rates have been used for hospital benchmarking within and between OECD countries.
While the standardised case-fatality rate for ischemic stroke
was about 5% on average across OECD countries in 2009,
there were large differences between the highest rate in
Mexico (17.6%) and Slovenia (9.7%) and the lowest rates in
Korea and Japan (1.8%) (Figure 5.4.1). The average standardised rate for hemorrhagic stroke is 19% (Figure 5.4.2),
about four times greater than the rate for ischemic stroke,
reflecting the more severe effects of intracranial bleeding.
The cross-country difference ranges between 6.5% in
Finland and 38.6% in Belgium. Countries that achieve better
survival for one type of stroke tend to do well for the other
type. Given the initial steps of care for stroke patients are
similar, this suggests that system-based factors play a role in
explaining differences across countries. For example, Nordic
countries (Denmark, Finland, Iceland, Norway and Sweden)
have been at the forefront of establishing dedicated stroke
110
units in hospitals, contributing to the below-average casefatality rates for both ischemic and hemorrhagic stroke.
Other factors such as patterns of hospital transfers, average
length of stay, emergency retrieval times and average severity of stroke may also influence the rates.
Case-fatality rates for ischemic stroke have declined by
26% on average across OECD countries between 2000
and 2009 (Figure 5.4.3). The trend is similar for hemorrhagic stroke with an average reduction of 17% during the
same period. These reductions suggest widespread
improvement in the quality of care for stroke patients.
Definition and comparability
In-hospital case-fatality rate following ischemic and
hemorrhagic stroke is defined as the number of
people who die within 30 days of being admitted
(including same day admissions) to hospital. Ideally,
rates would be based on individual patients; however,
not all countries have the ability to track patients in
and out of hospitals, across hospitals or even within
the same hospital because they do not currently use a
unique patient identifier. Therefore, this indicator is
based on unique hospital admissions and restricted
to mortality within the same hospital, so differences
in practices in discharging and transferring patients
may influence the findings.
The Czech Republic, Denmark, Finland, Korea,
Luxembourg, New Zealand, the Netherlands, Poland,
Slovenia, Sweden and the United Kingdom also
provided patient-based (in and out of hospitals) data.
Their relative performance is generally similar as the
case-fatality rate within the same hospital, although
the rates are obviously higher.
Both crude and age and sex standardised rates are
presented. Standardised rates adjust for differences
in age (45+ years) and sex and facilitate more meaningful international comparisons. Crude rates are
likely to be more meaningful for internal consideration by individual countries.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CARE FOR ACUTE EXACERBATION OF CHRONIC CONDITIONS
5.4. In-hospital mortality following stroke
5.4.1 In-hospital case-fatality rates within 30 days after
admission for ischemic stroke, 2009 (or nearest year)
Age-sex standardised rate
5.4.2 In-hospital case-fatality rates within 30 days after
admission for hemorrhagic stroke, 2009 (or nearest year)
Age-sex standardised rate
Crude rate
17.6
Mexico
Slovenia
Belgium
Slovak Republic
United Kingdom
Canada
Portugal
Ireland
Spain
Czech Republic
Australia
Netherlands
New Zealand
OECD
Luxembourg
Switzerland
Germany
Sweden
Israel
Italy
Austria
United States
Iceland
Finland
Norway
Denmark
Japan
Korea
Belgium
Mexico
Slovak Republic
Slovenia
Luxembourg
Ireland
Spain
Portugal
Netherlands
New Zealand
United States
Israel
Canada
United Kingdom
OECD
Czech Republic
Italy
Australia
Denmark
Switzerland
Iceland
Germany
Sweden
Austria
Norway
Korea
Japan
Finland
18.3
9.7
15.3
8.6
15.3
7.1
10.7
6.7
12.9
6.3
11.0
6.2
11.1
6.1
10.2
6.1
11.0
5.8
10.3
5.7
11.4
5.7
8.6
5.4
9.6
5.2
9.0
4.5
8.3
4.3
8.2
4.0
8.0
3.9
8.4
3.5
5.9
3.4
7.3
3.1
6.3
3.0
4.2
2.8
8.0
2.8
5.8
2.8
6.5
2.6
4.6
1.8
3.4
1.8
2.5
0
5
10
45.8
29.3
29.0
25.5
29.0
25.1
28.8
24.3
30.6
23.9
25.2
23.9
27.4
23.0
25.4
22.4
27.3
21.1
25.5
21.0
22.6
20.9
24.2
20.6
24.4
19.3
23.3
19.0
22.6
18.0
21.3
17.6
22.2
17.2
22.2
16.4
19.7
14.8
19.9
14.1
19.7
13.8
17.6
12.8
17.2
12.1
15.6
11.6
16.6
9.8
10.2
9.7
10.9
6.5
9.3
0
15
20
Rates per 100 patients
Crude rate
38.6
10
20
30
40
50
Rates per 100 patients
Note: Rates age-sex standardised to 2005 OECD population (45+).
95% confidence intervals represented by H.
Note: Rates age-sex standardised to 2005 OECD population (45+).
95% confidence intervals represented by H.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525153
1 2 http://dx.doi.org/10.1787/888932525172
5.4.3 Reduction in in-hospital case-fatality within 30 days after admission for ischemic stroke, 2000-09 (or nearest year)
Age-sex standardised rates per 100 patients
12
10
8
7.9
7.2
6.3
8.1
7.1
6.2
na
Ca
ga
r tu
Po
da
l
7.0
7.9
6.1
nd
la
Ir e
6.6
6.9
6.1
a in
ic
bl
pu
Re
Cz
ec
h
Sp
7.2
5.8
7.6
6.3
5.7
st
Au
er
th
ra
s
nd
la
an
al
Ne
Ze
w
li a
5.5
5.7
6.4
5.4
d
6.2
5.1
4.6
Ne
xe
m
bo
CD
ur
g
en
Lu
Sw
ed
el
ra
Is
ria
st
at
St
d
Un
i te
Au
es
d
an
nl
Fi
rw
No
De
nm
ar
k
ay
0
OE
4.1
3.0
4.5
4.2
3.8
3.9
5.1
4.0
3.5
3.9
3.7
3.1
3.7
3.0
3.0
3.9
3.2
2.8
3.5
3.4
2.6
2
3.5
2.8
6.1
7.9
4
9.0
9.7
6
Note: Rates age-sex standardised to 2005 OECD population (45+). 95% confidence intervals represented by H.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525191
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
111
5. QUALITY OF CARE • PATIENT SAFETY
Patient safety
5.5. Obstetric trauma
Patient safety has recently become one of the most prominent issues in health policy, as increased evidence of a high
rate of errors during the delivery of medical care has begun
to undermine the trust that patients and policy makers
have historically bestowed on the medical profession. As
early as 1991, the landmark Harvard Medical Practice Study
found that adverse events occur in 1 to 4% of all hospital
admissions (Brennan et al., 1991). The US Institute of
Medicine integrated the available evidence on medical
errors and estimated that more people die from medical
errors than from traffic injuries or breast cancer (Kohn
et al., 2000). One recent Swedish study showed that over
12% of hospital admissions had adverse events, of which
70% were preventable, resulting in an increased length of
stay of 6 days (Soop et al., 2009). The Council of the
European Union adopted in 2009 a Recommendation on
patient safety, including the prevention and control of
healthcare associated infections (European Union, 2009).
The obstetric trauma indicators are intended to flag cases of
potentially preventable third- and fourth-degree perineal
tears during vaginal delivery. Such tears extending to the
perineal muscles, anal sphincter and bowel wall require
surgical treatment after birth. Possible complications
include continued perineal pain and anal incontinence.
These types of tears are not possible to prevent, but can be
reduced by employing appropriate labour management and
care standards. A third- or fourth-degree trauma is more
likely to occur in the case of first vaginal delivery, high baby’s
birth weight, labour induction, occiput posterior position,
prolonged second stage of labour and instrumental delivery.
The proportion of deliveries involving higher degree lacerations is a useful indicator of the quality of obstetrical care
and can assist in reducing these adverse events. Obstetric
trauma indicators have been used by the US Joint Commission as well as by different international quality initiatives
analysing obstetric data. As the risk of a perineal laceration
is significantly increased in instrument-assisted labour
(vacuum, forceps), rates for this patient population are
reported separately.
Figures 5.5.1 and 5.5.2 show the variation in reporting rates
of obstetric trauma during vaginal delivery with and
without instrument. Canada, the United States and
Sweden have the highest rates of obstetric trauma with
instrument. Switzerland, Sweden and Denmark stand out
as having the highest reported rates for obstetric trauma
without instrument. There are no marked differences in
the position of countries in relation to the OECD average
between the two indicators. Belgium, Finland, France,
Ireland, Israel, Italy, Portugal, Slovenia and Spain have
112
consistently low reported obstetric trauma rates for both
indicators. The difference in the incidence of anal sphincter tears between Finland and the other Nordic countries
(Denmark, Norway, Sweden) may be explained by the
variation in delivery method and episiotomy practice
(Laine et al., 2009). Findings from a recent study showed
that enhanced midwifery skills in managing vaginal
delivery reduce the risk of obstetric anal sphincter injuries
(Hals et al., 2010). Differences in indicator values between
the countries may not only reflect safety of care, but also
differences in recording and reporting practices. For
example, Canada has very stringent rules for the coding
of obstetric trauma. This may partly explain why the
Canadian rates appear to be high in comparison with other
countries.
Definition and comparability
Patient safety indicators are derived from the Quality
Indicators developed by the US Agency for Healthcare
Research and Quality (AHRQ). AHRQ’s Patient Safety
Indicators (PSIs) are a set of indicators that provide
information on hospital complications and adverse
events following surgeries, procedures, and childbirth.
The PSIs were developed after a comprehensive literature review, analysis of ICD-9-CM codes, clinician panel
review, implementation of risk adjustment, and empirical analyses (AHRQ, 2006).
The two obstetric trauma indicators are defined as
the proportion of instrument assisted/non-assisted
vaginal deliveries with third- and fourth-degree
obstetric trauma codes in any diagnosis and procedure field. Therefore, any differences in the definition
of principal and secondary diagnoses have no
influence on the calculated rates.
Several differences in data reporting across countries
may influence the calculated rates of obstetric patient
safety indicators. These relate primarily to differences in coding practice and data sources. Some
countries report the obstetric trauma rates based on
administrative hospital data and others based on
obstetric register, which may influence the results.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE •
PATIENT SAFETY
5.5. Obstetric trauma
5.5.1 Obstetric trauma, vaginal delivery with instrument, 2009 (or nearest year)
Crude rates (%)
16
14
13.67
12.46
12
11.09
10
8
6.55
6.32
6
7.90
7.71
7.53
7.44
5.50
4
2.55
2
1.56
2.05
1.70
1.61
3.77
3.58
3.38
3.32
3.10
2.78
na
at
Ca
St
Un
i te
d
Sw
da
es
en 1
al
ed
an
d
nd
Ze
Ne
w
it z
Sw
Ge
er
rm
st
Au
De
la
an
y
li a
ra
ar
k
m
nm
do
CD
Ki
Un
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Ne
d
th
ng
OE
rw
No
la
er
nl
Fi
ay 1
s1
nd
d1
an
nd
Ir e
Sp
la
a in
ly
It a
m
Be
lg
an
iu
ce
l
ga
r tu
Fr
Sl
Po
ov
Is
en
ra
ia
el
0
1. Obstetric register data.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525210
5.5.2 Obstetric trauma, vaginal delivery without instrument, 2009 (or nearest year)
Crude rates (%)
3.5
3.18
3.14
3.06
3.0
2.67
2.5
2.15
2.13
2.12
2.05
2.03
2.02
2.0
1.76
1.61
1.5
1.34
1.0
0.5
0.47
0.44
0.37
0.68
0.63
0.60
0.54
0.74
er
it z
Sw
Sw
ed
la
nd
en 1
k
De
nm
ar
da
Ca
ng
Ki
d
Un
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na
m
do
an
rm
Ge
la
er
Ne
th
St
y
s1
nd
es
at
li a
ra
d
st
i te
Un
Au
ay 1
No
rw
d
Ze
al
an
CD
OE
Ne
w
nd
la
Ir e
ly
It a
m
iu
lg
Be
Po
r tu
ga
l
d1
an
nl
Fi
a in
Sp
el
ra
Is
ia
en
ov
Sl
Fr
an
ce
0
1. Obstetric register data.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525229
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
113
5. QUALITY OF CARE • PATIENT SAFETY
5.6. Procedural or postoperative complications
Efforts to improve patient safety have sparked interest in
reporting sentinel and adverse events arising from health
care. Sentinel events are rare but dramatic incidents where
medical errors may lead to tangible harm to patients. These,
sometimes referred to as “never events”, indicate failure of
safeguards to protect patients during care delivery. Foreign
body left in during procedure is such an occurrence that
reflects serious process problems. The indicator captures
errors relating to the failure to remove surgical instruments
(i.e. needles, knife blades, gauze swabs) at the end of a
procedure. The most common risk factors that might cause
retained bodies after surgery are emergencies, unplanned
changes in procedure, changes in the surgical team during
the procedure and patient obesity (Gawande et al., 2003).
Preventive measures include counting procedures, a
methodical wound exploration and effective communication among the surgical team.
Adverse events are unintended incidents caused by health
care that could lead to harm to patients. Such complications can never be fully avoided, given the high-risk nature
of some interventions and the underlying health problems
of patients. Thus, in contrast to the sentinel events, isolated adverse events do not necessarily indicate a patient
safety issue. While accidental puncture or laceration
during a surgical procedure is a recognised risk, increased
rates of such complications may indicate system problems,
such as inadequate training or fatigued health staff. Postoperative pulmonary embolism and deep vein thrombosis
cause unnecessary pain and death, but can be prevented
through the appropriate use of anticoagulants and other
preventive measures. Sepsis after elective surgery is a
severe complication that can lead to multiple organ
dysfunction and death. It usually results from less severe
infections, which should be avoided or properly treated.
Many cases of postoperative sepsis can be prevented
through the appropriate use of prophylactic antibiotics,
sterile surgical techniques and good postoperative care.
Figures 5.6.1 to 5.6.4 show reported complication rates
related to surgical and medical care. There are considerable
differences across countries for these four indicators. For
example, Switzerland has the highest rate for reported
foreign bodies left in during procedure, a very low rate for
postoperative pulmonary embolism or deep vein thrombosis, and the lowest rate for postoperative sepsis. A
similar variance in indicator results can be found for
Canada, Spain and France. Some countries have consistently higher (Australia, New Zealand) or lower reporting
rates (Denmark, Germany).
114
Differences in procedural or postoperative patient safety
indicators may reflect differences in recording and reporting practices rather than safety of care. In countries where
documentation and hospital billing are not directly related,
hospitals and physicians have less incentive to report
diagnoses accurately and completely. Although there may
be reservations whether the current results accurately
reflect patient safety performance at the national level and
are internationally comparable, these indicators show that
numerous patients certainly have been affected by patient
safety events. International efforts to harmonise documentation and data systems, and the results of ongoing validation studies, will provide more information on validity and
reliability of patient safety measures based on administrative hospital data in the future.
Definition and comparability
See Indicator 5.5 “Obstetric trauma” for definition,
source and methodology underlying the patient safety
rates. All procedural or postoperative complications
are defined as the number of discharges with ICD
codes for complication in any secondary diagnosis
field, divided by the total number of discharges
(medical and surgical or surgical only) for patients
aged 15 and older. The rates have been age-sex
standardised, apart from postoperative sepsis rate.
This is due to the use of modified exclusion criteria
within the algorithm for the calculation of this indicator. In addition, the patient safety rates have been
adjusted by the average number of secondary
diagnoses (SDx) (Drösler et al., 2011) in order to improve
inter-country comparability. Despite this adjustment,
the results for the two countries (Finland and Italy)
that are reporting less than 1.5 diagnoses per record
may be under-estimated.
Other differences in data reporting across countries
may influence the calculated rates of patient safety
indicators. These include differences in coding
practice, coding rules (e.g. definition of principal and
secondary diagnoses), coding for billing purposes and
the use of diagnosis type markers (e.g. “present at
admission”).
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE •
PATIENT SAFETY
5.6. Procedural or postoperative complications
5.6.1 Foreign body left in during procedure,
2009 (or nearest year)
5.6.2 Accidental puncture or laceration,
2009 (or nearest year)
SDx-adj. standardised rates
SDx-adj. standardised rates
Age-sex standardised rates
Age-sex standardised rates
13.8
Switzerland
Australia
Canada
New Zealand
Belgium
United Kingdom
Spain
OECD
Portugal
France
United States
Finland1
Germany
Italy1
Israel
Sweden
Ireland
Denmark
8.7
9.8
9.4
9.7
9.5
8.6
7.8
5.7
5.1
5.6
5.7
5.7
n.a.
5.5
4.8
4.9
3.4
2.6
1.8
1.3
5.4
7.5
4.5
3.3
2.0
2.8
2.4
9.7
6.1
3.4
1.5
13.3
3.2
2.7
2.0
0
5
Canada
Belgium
New Zealand
Switzerland
Australia
Portugal
OECD
Sweden
United Kingdom
Finland1
United States
France
Denmark
Ireland
Italy1
Spain
Germany
Israel
10
15
20
Rates per 100 000 hospital discharges
525
517
432
546
405
410
318
n.a.
255
220
219
205
170
174
144
170
29
166
65
13
75
73
44
392
356
352
98
119
368
155
117
100
114
122
160
55
0
200
400
600
Rates per 100 000 hospital discharges
Note: Some of the variations across countries are due to different
classification systems and recording practices. 95% confidence intervals
represented by H.
SDx: Secondary diagnoses adjustment.
1. The average number of secondary diagnoses is < 1.5.
Note: Some of the variations across countries are due to different
classification systems and recording practices. 95% confidence intervals
represented by H.
SDx: Secondary diagnoses adjustment.
1. The average number of secondary diagnoses is < 1.5.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525248
5.6.3 Postoperative pulmonary embolism or deep vein
thrombosis, 2009 (or nearest year)
SDx-adjusted rates
Age-sex standardised rates
Crude rates
902
780
812
820
749
722
692
697
680
299
677
664
389
428
391
215
203
0
868
634
536
624
595
1 271
1 000
1 500
2 000
Rates per 100 000 hospital discharges
Note: Some of the variations across countries are due to different
classification systems and recording practices. 95% confidence intervals
represented by H.
SDx: Secondary diagnoses adjustment.
1. The average number of secondary diagnoses is < 1.5.
1 455
1 451
1 485
New Zealand
1 224
Belgium
1 099
1 062
1 077
Spain
United States
Israel
Sweden
694
France
674
1 411
1 612
1 035
1 027
991
1 019
926
OECD
858
769
698
754
705
Denmark
541
Germany
Switzerland
538
500
Australia
Canada
506
422
491
378
1 951
1 863
Ireland
1 653
631
631
566
591
548
285
335
5.6.4 Postoperative sepsis,
2009 (or nearest year)
SDx-adj. standardised rates
1 020
994
1 019
Australia
United States
France
United Kingdom
Sweden
Ireland
Finland1
New Zealand
Portugal
Norway
OECD
Canada
Switzerland
Italy1
Denmark
Israel
Germany
Spain
Belgium
1 2 http://dx.doi.org/10.1787/888932525267
152
0
708
354
500
1 000
1 500
2 000
Rates per 100 000 hospital discharges
Note: Some of the variations across countries are due to different
classification systems and recording practices.
SDx: Secondary diagnoses adjustment.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525305
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525286
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
115
5. QUALITY OF CARE • CARE FOR MENTAL DISORDERS
Care for mental disorders
5.7. Unplanned hospital re-admissions for mental disorders
The burden of mental illness is substantial, accounting for
between 3 and 16% of total expenditure on health across
OECD countries. Severe disorders such as schizophrenia
and bipolar disorder are among the top ten causes of years
lost due to disability worldwide (WHO, 2008b).
Canada and the United Kingdom, involving patients in care
and service plan development. These developments may
also have some implications on re-admission rates and
make it more complex to identify those re-admissions that
are truly unplanned.
Mental health care has become a policy priority in many
OECD countries, coinciding with dramatic changes in the
delivery of mental health services. Starting in the 1970s
with de-institutionalisation and the development of
modern psychiatric drugs, care has shifted from large
psychiatric hospitals towards community-based integrated
care involving a multidisciplinary team. Preventive and
rehabilitative care and social integration have also been
emphasised more than previously. Paradoxically, these
shifts have made it harder to track mental health care at
the population level, as few countries have a health information infrastructure suitable for following patients across
a variety of delivery settings.
Unplanned re-admission is only one measure of the quality
and performance of mental health care systems, and
further indicators in domains such as treatment, care
continuity, co-ordination and outcomes are needed for a
better and more complete understanding of the performance of mental health care systems across countries.
Patients with severe mental disorders still receive specialised care at hospitals but if appropriate and co-ordinated
follow-up is provided after discharges, patients are not
usually re-admitted to hospital within 30 days. A high rate of
unplanned re-admissions is therefore an indicator of the
quality of several dimensions of the mental health system.
As part of monitoring quality of mental health care,
unplanned 30 day hospital re-admission rates are used in
organisations in different countries such as the Canadian
Institute for Health Information, the Care Quality Commission in the United Kingdom and the National Mental Health
Performance Monitoring System in the United States.
Re-admission rates for schizophrenia vary a lot across
countries, with Nordic countries and Poland at the higher
end, and the Slovak Republic and the United Kingdom at
the lower end (Figure 5.7.1). Re-admission rates for bipolar
disorders are also highest in Poland and in Nordic countries
(Figure 5.7.2). Most countries have similar rates for men
and women for both mental disorders.
Mental health care systems have been developing new
organisational and delivery models over the past few
decades. Some countries, such as Italy, Norway and the
United Kingdom, use community-based “crisis teams” to
stabilise patients on an outpatient basis, while Canada and
the United States also emphasise community mental
health care delivery. Other countries, such as Denmark and
Finland, use interval care protocols to place unstable
patients in hospital for short periods. Countries such as
Denmark are also proactive in identifying patients in need
of care through outreach teams following discharges, possibly leading to high re-admissions. A further development
is a more patient-centred approach in countries such as
116
Definition and comparability
Few administrative databases can distinguish between
unplanned and planned re-admissions. Therefore, the
indicator is defined as the number of re-admissions
per 100 patients with a diagnosis of schizophrenia or
bipolar disorder. The denominator is comprised of all
patients with at least one admission during the year
for the condition as principal diagnosis or as one of the
first two listed secondary diagnosis. The numerator is
re-admissions for any mental disorder to the same
hospital within 30 days of discharge but excludes
same-day admissions (less than 24 hours). The data
have been age-sex standardised based on the 2005
OECD population structure, to remove the effect of
different population structures across countries.
The absence of unique patient identifiers in many
countries does not allow the tracking of patients
across hospitals. Rates are therefore biased downwards as re-admissions to a different hospital cannot
be observed. However, the 11 countries which were
able to estimate re-admission rates to the same or
other hospitals, show that rates based on the two
different specifications were closely correlated and
the ranking of countries was similar (except for the
Czech Republic), suggesting that re-admissions to the
same hospital can be used as a valid approximation.
ICD-code specifications of hospital re-admissions for
bipolar disorder have changed since the last data
collection, so a direct comparison with previously
published data is not possible.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CARE FOR MENTAL DISORDERS
5.7. Unplanned hospital re-admissions for mental disorders
5.7.1 Schizophrenia re-admissions to the same hospital, 2009 (or nearest year)
Female
Male
27.7
Norway
28.9
Poland
28.0
24.4
Sweden
24.2
Israel
23.2
21.4
Ireland
21.6
19.3
Finland
18.8
Belgium
16.7
17.1
13.6
14.4
13.6
13.6
Italy
14.0
New Zealand1
13.5
11.3
Spain
11.1
Canada 2
Switzerland
8.9
United Kingdom
8.1
10
4.5
4.5
Slovak Republic
4.5
20
11.2
11.4
10.9
11.3
9.5
9.8
8.4
9.2
7.8
8.4
Czech Republic
9.6
40
30
Rates per 100 patients
20.7
18.2
19.2
18.5
OECD
16.9
0
27.3
24.4
23.2
21.6
21.5
Denmark1
24.0
30.5
27.7
28.4
25.7
0
10
20
30
40
Rates per 100 patients
Note: Rates age-sex standardised to 2005 OECD population. 95% confidence intervals represented by H.
1. Data do not include patients with secondary diagnosis of schizophrenia and bipolar disorder.
2. Only re-admissions within 30 days of the initial hospitalisation were counted as re-admissions.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525324
5.7.2 Bipolar disorder re-admissions to the same hospital, 2009 (or nearest year)
Female
22.8
22.6
21.3
19.5
18.5
18.4
16.4
14.9
14.3
10.7
10.5
10.3
9.5
8.8
7.3
6.6
4.9
40
30
Rates per 100 patients
20
10
29.9
30.2
Poland
Sweden
Norway
Ireland
Denmark1
Israel
Finland
New Zealand1
OECD
Belgium
Spain
Canada 2
United Kingdom
Italy
Switzerland
Czech Republic
Mexico
Slovak Republic
30.5
0
Male
24.6
21.1
22.8
22.2
23.3
19.4
18.5
16.5
17.1
15.6
20.1
18.9
18.6
20.3
15.3
15.2
14.9
13.9
10.6
10.9
10.7
10.5
10.6
10.0
9.0
7.4
5.7
6.2
2.8
0
10.2
10.2
8.8
7.0
7.0
10
20
30
40
Rates per 100 patients
Note: Rates age-sex standardised to 2005 OECD population. 95% confidence intervals represented by H.
1. Data do not include patients with secondary diagnosis of schizophrenia and bipolar disorder.
2. Only readmissions within 30 days of the initial hospitalisation were counted as readmissions.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525343
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
117
5. QUALITY OF CARE • CANCER CARE
Cancer care
5.8. Screening, survival and mortality for cervical cancer
Cervical cancer is preventable and curable if detected early.
The main cause of cervical cancer, which accounts for
approximately 95% of all cases, is sexual exposure to the
human papilloma virus, HPV (IARC, 1995; Franco et al.,
1999). Three indicators are presented to reflect variation in
cervical cancer care across OECD countries: cervical cancer
screening rates in women aged 20-69 years, five-year
relative survival rates, and mortality rates.
The primary prevention of cervical cancer attributable to
human papilloma virus types 16 and 18 by prophylactic
vaccines has been shown to be highly effective and recommended in many countries worldwide (Shefer et al., 2008;
Koulova et al., 2008). The secondary prevention of cervical
cancer by the Pap-smear and HPV DNA testing increases the
probability of detecting premalignant lesions which can be
effectively treated. Population-based cancer screening programmes have been promoted by the Council of the European Union and the European Commission (European
Union, 2003; European Commission, 2008c), but the periodicity and target groups vary among member states. There
has been much discussion whether cervical cancer screening needs to be reevaluated and the cost-effectiveness
investigated after introduction of HPV vaccination programmes (Goldhaber-Fiebert et al., 2008; Wheeler et al., 2009).
In 2009, screening rates for cervical cancer were the highest
in the United States, at 86% (Figure 5.8.1). The United
Kingdom, Norway and Sweden also achieved high coverage,
with close to 80% of the target population. Screening rates
were the lowest in the Slovak Republic and Hungary,
although in Hungary a high proportion of screening activity
takes place outside organised screening settings, resulting in
underreporting. In several countries (Canada, Finland,
Hungary, Iceland, Norway, the Slovak Republic, the United
Kingdom and the United States), screening rates have
declined at least slightly between 2000 and 2009.
Survival rates are one of the key measures of the effectiveness of health care systems and are commonly used to track
progress in treating a disease over time. They reflect both
how early the cancer was detected and the effectiveness of
the treatment. Over the periods 1997-2002 and 2004-09, the
five-year relative survival rates improved in most countries
due to improved effectiveness of screening and treatment
(Figure 5.8.2). In the most recent period (2004-09), survival
rates continued to be the lowest in Ireland and the United
Kingdom, while they were the highest in Norway and Korea.
Mortality rates reflect the effect of cancer care in past years
and improved diagnosis of early-stage cancers with a better
prognosis, as typically happens when screening is wide-
118
spread. The mortality rates for cervical cancer declined
for most OECD countries between 2000 and 2009, apart
from Luxembourg, Ireland, Israel, Portugal and Greece
(Figure 5.8.3). Mexico has experienced a sharp decrease in
cervical cancer mortality from 14.5 per 100 000 females to 9.6,
although it still has the highest rate among OECD countries.
Definition and comparability
Screening rates for cervical cancer reflect the proportion of women who are eligible for a screening test and
actually receive the test. As policies regarding screening periodicity and target population differ across
countries, the rates are based on each country’s
specific policy. An important consideration is that
some countries ascertain screening based on surveys
and other based on encounter data, which may influence the results. Survey-based results may be affected
by recall bias. If a country has an organised screening
programme, but women receive care outside the
programme, rates may be underreported.
Relative cancer survival rates reflect the proportion of
patients with a certain type of cancer who are still
alive after a specified time period (commonly
five years) compared to those still alive in absence of
the disease. Relative survival rates capture the excess
mortality that can be attributed to the diagnosis. For
example, a relative survival rate of 80% does not
mean that 80% of the cancer patients are still alive
after five years, but that 80% of the patients that were
expected to be alive after five years, given their age
at diagnosis and sex, are in fact still alive. All the
survival rates presented here have been agestandardised using the International Cancer Survival
Standard (ICSS) population. The survival rates are not
adjusted for tumour stage at diagnosis, hampering
assessment of the relative impact of early detection
and better treatment.
See Indicator 1.4 “Mortality from cancer” for definition,
source and methodology underlying the cancer
mortality rates.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CANCER CARE
5.8. Screening, survival and mortality for cervical cancer
5.8.1 Cervical cancer screening, percentage women
screened aged 20-69, 2000 to 2009 (or nearest year)
2009
2000
2
United States
United Kingdom1
Norway1
Sweden1
New Zealand1
Canada 2
Spain 2
France 2
Slovenia1
Finland1
Iceland1
Denmark1
Netherlands1
Chile1
Korea 2
Belgium1
Ireland1
Australia1
OECD17
Estonia1
Luxembourg1
Czech Republic 1
Italy1
Mexico 1
Turkey1
Japan 2
Hungary1
Slovak Republic1
2004-09
85.9
90.6
Norway
78.7
82.0
78.9
78.2
78.5
Korea
78.4
Japan
77.4
73.1
75.3
77.2
67.5
65.6
66.3
67.3
Netherlands
65.3
62.5
61.2
61.3
52.0
36.2
65.1
Canada
64.9
65.4
63.3
62.0
Austria
61.7
United Kingdom
23.7
28.4
66.4
Czech Republic
24.5
22.9
23.2
62.3
Germany
24.9
22.6
58.0
Ireland
25
50
66.3
65.3
Denmark
47.7
39.0
38.9
67.9
United States
50.5
33.3
66.4
64.6
Finland
Portugal
61.1
59.9
63.1
OECD16
Belgium
63.2
58.6
67.3
67.0
65.6
64.5
68.1
68.1
Iceland
66.1
65.6
70.2
70.2
63.0
France
69.0
74.0
74.2
Sweden
69.8
70.3
78.2
75
100
% of women screened
54.3
0
2. Survey.
76.8
70.6
New Zealand
72.4
1997-2002
68.8
Slovenia
73.0
72.3
0
1. Programme.
5.8.2 Cervical cancer five-year relative survival rate,
1997-2002 and 2004-09 (or nearest period)
64.4
64.3
62.9
62.5
62.2
58.8
57.6
25
50
75
100
Age-standardised rates (%)
Note: 95% confidence intervals represented by H.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525362
1 2 http://dx.doi.org/10.1787/888932525381
5.8.3 Cervical cancer mortality, females, 2000 to 2009 (or nearest year)
2000
2009
14.5
Age-standardised rates per 100 000 females
16
14
9.6
10.0
12
7.5
6.5
6.8
5.9
5.2
5.2
1.7
4.0
3.1
3.7
3.2
3.4
4.4
3.3
3.4
3.2
3.8
3.2
3.8
2.6
3.0
2.4
2.5
2.3
1.9
2.2
3.0
2.2
2.3
2.2
3.0
2.1
2.5
2.1
3.3
2.1
2.1
1.9
2.4
1.7
1.7
1.7
2.3
1.6
1.6
1.5
1.4
1.5
1.3
0.8
0.8
1.2
2.0
2.4
4
2.5
2.0
6
2
5.2
6.7
8
6.1
5.4
8.3
10
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Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525400
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
119
5. QUALITY OF CARE • CANCER CARE
5.9. Screening, survival and mortality for breast cancer
Breast cancer is the most prevalent form of cancer in
women, accounting for almost 460 000 deaths worldwide
in 2008 (WHO, 2011d). One in nine women will acquire
breast cancer at some point in her life and one in thirty will
die from the disease. There are a number of risk factors
that increase a person’s chance of getting this disease such
as age, family history of breast cancer, estrogen replacement therapy, alcohol use and others. Overall spending for
breast cancer care typically amounts to about 0.5-0.6% of
total health expenditure (OECD, 2003a). Variation in breast
cancer care across OECD countries is indicated by mammography screening rates in women aged 50-69 years,
relative survival rates, and mortality rates.
The promotion of screening mammography (European
Union, 2003) and self-examination have led to the detection
of the disease at earlier stages. Most OECD countries have
adopted breast cancer screening programmes as the most
effective way for detecting the disease. The periodicity and
population target groups vary across member states and
are still the subjects of debate. EU guidelines (European
Commission, 2006) promote a desirable target screening rate
of at least 75% of eligible women in European countries.
Screening rates continue to vary widely across OECD countries in 2009, ranging from 12% in Turkey and 16-17% in the
Slovak Republic and Mexico, up to over 80% in Finland, the
Netherlands and the United States (Figure 5.9.1). Some
countries that already had high screening rates in 2000
experienced a reduction over the past decade, including
Finland, the United States, Norway and the United Kingdom.
By contrast, the rates have increased a lot in Hungary and
the Slovak Republic, although they remain well below the
OECD average.
Breast cancer survival rates reflect advances in public
health interventions, such as greater awareness of the
disease, screening programmes, and improved treatment.
In particular, the introduction of combined breast conserving surgery with local radiation and neoadjuvant therapy
have increased survival as well as the quality of life of
survivors (Mauri et al., 2008). Resources and patterns for
breast cancer treatment vary substantially across OECD
countries, leading to an interest in comparing survival
rates under the EUROCARE, CONCORD and International
Cancer Benchmarking Partnership studies (Sant et al., 2009;
120
Coleman et al., 2008, 2011). The relative five-year breast
cancer survival rates have improved in all countries
between 1997-2002 and 2004-09 (Figure 5.9.2). Most OECD
countries have survival rates of over 80%, with notable
increases in Ireland, the Czech Republic and Slovenia.
Recent studies suggest that some of the differences in
survival rates could be due to variations in the implementation of screening programmes and different improvement rates between middle aged and elderly patients
(Rosso et al., 2010).
Mortality rates reflect the effect of improvements in early
detection and treatment of breast cancer. Overall, the
breast cancer mortality rates have declined in most OECD
countries over the past decade (Figure 5.9.3). Improvements
were substantial in Estonia, the Czech Republic, the
Netherlands, the United Kingdom, Luxembourg and
Norway. The exceptions are Korea, Japan, Iceland and
Mexico, but the increases in these countries were modest
and the mortality rates continue to be among the lowest in
OECD countries.
Definition and comparability
Mammography screening rates reflect the proportion
of eligible women patients who are actually screened.
As policies regarding target age groups and screening
periodicity differ across countries, the rates are based
on each country’s specific policy. Some countries
ascertain screening based on surveys and others
based on encounter data, and this may influence
results. Survey-based results may be affected by recall
bias. If a country has an organised screening
programme, but women receive care outside of the
programme, rates may be underreported.
Survival rates and mortality rates are defined in
Indicator 5.8 “Screening, survival and mortality for
cervical cancer”.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CANCER CARE
5.9. Screening, survival and mortality for breast cancer
5.9.1 Mammography screening, percentage of women
aged 50-69 screened, 2000 to 2009 (or nearest year)
2009
1
Finland
Netherlands1
United States 2
France 2
Norway1
United Kingdom1
Denmark1
Ireland1
Canada 2
Spain 2
Israel1
New Zealand1
OECD15
Luxembourg1
Iceland1
Italy1
Belgium1
Australia1
Greece 2
Germany2
Estonia1
Korea1
Hungary1
Czech Republic1
Slovenia 2
Chile1
Japan 2
Mexico 1
Slovak Republic1
Turkey1
2000
2004-09
84.4
87.4
United States
82.1
80.5
81.1
86.9
76.7
75.3
Japan
86.1
Canada
85.6
74.0
Norway
82.4
73.7
Finland
84.2
73.1
76.3
71.8
69.5
86.3
Belgium
86.2
61.0
53.8
86.0
83.1
84.5
New Zealand
62.2
59.9
77.0
84.4
Netherlands
79.5
OECD16
78.7
61.0
61.0
60.0
59.0
50.0
53.8
France
53.6
Korea
52.0
74.5
82.8
82.2
76.7
Portugal
82.0
49.1
Denmark
82.0
76.2
48.5
United Kingdom
75.0
51.4
26.7
83.5
83.3
Germany
54.9
55.9
81.3
47.2
16.6
16.0
6.9
81.2
Austria
31.8
23.8
22.5
79.3
80.3
Ireland
72.3
Czech Republic
70.8
78.6
76.9
Slovenia
12.4
25
86.6
86.5
86.3
Sweden
66.9
63.0
89.3
87.3
Iceland
72.5
72.7
1997-2002
88.6
74.1
79.2
0
1. Programme.
5.9.2 Breast cancer five-year relative survival rate,
1997-2002 and 2004-09 (or nearest period)
50
75
100
% of women screened
67.9
0
2. Survey.
20
40
60
80
100
Age-standardised rates (%)
Note: 95% confidence intervals are represented by H.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525419
1 2 http://dx.doi.org/10.1787/888932525438
5.9.3 Breast cancer mortality, females, 2000 to 2009 (or nearest year)
2009
9.7
10.8
33.4
28.6
31.5
30.5
25.6
25.0
29.4
30.6
24.7
27.0
24.1
28.8
24.6
23.6
23.2
24.5
22.3
22.1
25.8
27.2
21.6
23.6
21.4
25.4
21.0
23.9
19.9
19.8
20.3
23.1
22.9
19.8
19.7
18.9
19.7
19.8
19.3
21.2
19.1
19.4
19.1
18.6
21.1
18.5
20.0
18.1
20.8
17.7
17.4
4.9
6.1
10
15.7
13.4
15
10.8
11.4
20
18.6
16.4
22.5
25
24.3
25.6
27.0
30
26.1
2000
Age-standardised rates per 100 000 females
35
5
i
Po c
la
nd
Sw
ed
e
Gr n
ee
ce
Sl
ov Ic e
ak lan
R
d
Un epu
i te bli
c
d
St
at
es
OE
C
Es D
S w ton
it z ia
er
la
n
Au d
st
ria
Lu
xe I t a l y
m
bo
u
Ge rg
rm
an
Un
y
i te Fr a
nc
d
Ki
ng e
do
Sl m
N e ove
n
w
Ze ia
Ne ala
th nd
er
la
nd
s
Is
ra
Hu el
ng
ar
Ir e y
la
De nd
nm
ar
k
Re
pu
bl
l
li a
ra
Cz
ec
h
Au
st
ga
d
Po
r tu
ay
an
nl
Fi
rw
No
a in
Sp
o
il e
Ch
n
ic
ex
M
pa
Ja
Ko
re
a
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525457
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
121
5. QUALITY OF CARE • CANCER CARE
5.10. Survival and mortality for colorectal cancer
Colorectal cancer is the third most commonly diagnosed
form of cancer worldwide, after lung and breast cancer,
with approximately one million new cases diagnosed per
year (Parkin et al., 2005). There are several factors that place
certain individuals at increased risk for the disease, including age, the presence of polyps, ulcerative colitis, a diet
high in fat, and genetic background. The disease is more
common in the United States and Europe, and is rare in
Asia. In Asian countries where people are gradually
adopting western diets, such as Japan, the incidence of
colorectal cancer is increasing (IARC, 2011). It is estimated
that approximately 610 000 people worldwide died due to
colorectal cancer in 2008 (WHO, 2011d). Total spending on
the treatment of colorectal cancer in the United States is
estimated to reach USD 14 billion per year (Mariotto et al.,
2011). Two indicators are presented to reflect variation in
outcomes for patients with colorectal cancer across OECD
countries: five-year relative survival rates and mortality
rates.
Colorectal cancer screening is recommended by using fecal
occult blood testing, sigmoidoscopy or colonoscopy in
adults, beginning at age 50 and continuing until age 75
(USPSTF, 2008). These diagnostic methods are effective in
detecting early-stage cancer and adenomatous polyps.
Although organised screening programmes are being
introduced or piloted in several OECD countries, data on
screening rates for colorectal cancer are not yet available at
an international level.
Colorectal survival rates have been used to compare
European countries in the EUROCARE study (Sant et al., 2009)
and around the world in the CONCORD study (Coleman
et al., 2008). Advances in diagnosis and treatment have
increased survival over the last decade. There is compelling
evidence in support of the clinical benefit of improved
surgical techniques, radiation therapy and combined
chemotherapy. All countries show improvement in survival
between 1997-2002 and 2004-09 (Figure 5.10.1). Japan and
122
Iceland have the highest relative survival rates, at over 66%.
The Czech Republic has the lowest rate, although survival
rates have increased remarkably from 41% to nearly 50%
between the two periods. Recent data from the EUROCARE
project showed that survival for colorectal cancer continued
to increase in Europe, and in particular in eastern European
countries (Verdecchia et al., 2007).
There are differences in colorectal cancer survival between
genders across OECD countries (Figure 5.10.2). In nearly all
countries, survival rates are higher for females, with the
exception of Korea.
Mortality rates reflect the effect of cancer care and changes
in incidence, thus careful interpretation of the relationship
between survival and mortality trends is required
(Dickman and Adami, 2006). Most countries experienced a
decrease in mortality for colorectal cancer between 2000
and 2009 (Figure 5.10.3), with the exceptions of Korea,
Portugal, Slovenia, Poland, Mexico, Greece, Chile and
Estonia. Central and eastern European countries tend to
have higher mortality rates than other OECD countries.
Despite a decrease in mortality for colorectal cancer over
the past decade, Hungary continues to have the highest
mortality rate for colorectal cancer, followed by the Slovak
Republic and the Czech Republic. Countries with high
relative survival rates, like Japan, Iceland and the United
States, also have below-average mortality rates.
Definition and comparability
Survival and mortality rates are defined in Indicator 5.8
“Screening, survival and mortality for cervical cancer”.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CANCER CARE
5.10. Survival and mortality for colorectal cancer
5.10.1 Colorectal cancer, five-year relative survival rate,
1997-2002 and 2004-09 (or nearest period)
2004-09
Japan
5.10.2 Colorectal cancer, five-year relative survival rate
by sex, 2004-09 (or nearest period)
1997-2002
Female
68.0
67.3
66.1
Iceland
64.7
Belgium
United States
Korea
Canada
Norway
57.1
New Zealand
57.0
Finland
Netherlands
57.9
Sweden
57.3
Canada
Austria
60.4
59.9
54.6
61.7
Germany
62.1
Denmark
50.1
United Kingdom
48.1
Ireland
52.9
49.0
Czech Republic
41.1
0
25
50
50.3
55.3
Czech Republic
75
100
Age-standardised rates (%)
52.6
54.1
Ireland
49.6
55.4
52.9
58.9
United Kingdom
53.3
56.0
56.0
Denmark
55.5
58.9
58.1
60.1
Slovenia
55.8
45.5
59.5
63.5
57.0
Slovenia
60.9
59.9
63.8
OECD
Portugal
France
61.7
61.7
64.6
Sweden
57.4
Portugal
62.5
61.2
Finland
60.7
63.5
62.8
65.3
Netherlands
61.0
64.4
64.2
Norway
61.8
66.7
66.0
62.0
63.1
53.3
OECD16
66.0
New Zealand
58.9
Germany
64.8
62.1
66.9
61.8
63.1
57.0
Austria
69.3
Belgium
63.4
59.1
Iceland
United States
63.7
52.6
69.2
Korea
64.5
62.5
Japan
Male
48.8
50.8
0
25
50
75
100
Age-standardised rates (%)
Note: 95% confidence intervals represented by H.
Note: 95% confidence intervals represented by H.
Source: OECD Health Data 2011.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525476
1 2 http://dx.doi.org/10.1787/888932525495
5.10.3 Colorectal cancer mortality 2000 to 2009 (or nearest year)
2000
2009
27.7
26.0
24.5
25.5
27.0
24.8
20.7
21.4
24.3
21.2
19.8
20.9
21.0
20.6
23.1
19.9
20.2
19.5
22.8
19.2
19.5
18.9
20.4
18.5
18.3
20.2
17.8
17.2
17.0
21.5
17.0
18.0
16.8
17.6
16.6
18.5
16.3
18.3
16.3
18.2
16.2
15.6
12.7
14.8
16.5
14.5
14.0
14.3
12.6
11.0
11.1
15
11.6
11.9
17.1
20
14.3
21.3
25
21.6
30
27.0
25.3
31.0
35
37.6
33.1
34.3
Age-standardised rates per 100 000 population
40
5
4.8
5.5
10
M
ex
ic
o
Ch
il e
Gr
ee
ce
F
Un in
i te lan
d
d
St
at
e
Au
s
S w s tr a
i t z li a
er
la
nd
Ko
re
Au a
st
ri
Fr a
an
ce
Un
i te Ja
pa
d
Ki
ng n
do
m
Ic
el
an
d
It a
ly
Is
ra
S el
Lu we
xe d e n
m
bo
ur
Ca g
na
da
OE
CD
Sp
G e a in
rm
an
Ir e y
la
n
E d
Ne s to
th ni a
er
la
n
Po ds
r tu
g
No al
rw
ay
Ne Pol
w and
Ze
al
a
De nd
nm
a
C z Slo r k
ec
ve
h
Sl
R ni
ov ep a
a k ub
Re li c
pu
b
Hu li c
ng
ar
y
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525514
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
123
5. QUALITY OF CARE • CARE FOR COMMUNICABLE DISEASES
Care for communicable diseases
5.11. Childhood vaccination programmes
Childhood vaccination continues to be one of the most
cost-effective health policy interventions. All OECD countries or, in some cases, sub-national jurisdictions have
established vaccination programmes based on their
interpretation of the risks and benefits of each vaccine.
Coverage of these programmes can be considered as a
quality of care indicator. Pertussis, measles and hepatitis B
are taken here as examples as they represent in timing and
frequency of vaccination the full spectrum of organisational challenges related to childhood vaccination.
Vaccination against pertussis (often administered in
combination with vaccination against diphtheria and
tetanus) and measles is part of almost all programmes, and
reviews of the evidence supporting the efficacy of vaccines
against these diseases have concluded that the respective
vaccines are safe and highly effective. In Europe, the
gradual uptake of the measles vaccine has meant that
measles incidence is around one-tenth of the rate of the
early 1990s.
A vaccination for hepatitis B has been available since 1982
and is considered to be 95% effective in preventing infection and its chronic consequences, such as cirrhosis and
liver cancer. In 2004, it was estimated that over 350 million
people were chronically infected with the hepatitis B virus
worldwide and at risk of serious illness and death (WHO,
2009b). In 2007, more than 170 countries had already begun
to follow the WHO recommendation to incorporate
hepatitis B vaccine as an integral part of their national
infant immunisation programme. In countries with low
levels of hepatitis B (e.g. Australia, New Zealand, northern
and western Europe and North America), WHO indicates
that routine hepatitis B vaccination should still be given
high priority, since a high proportion of chronic infections
are acquired during early childhood (WHO, 2004b).
Figures 5.11.1 and 5.11.2 demonstrate that the overall
vaccination of children against measles and pertussis
(including diphtheria and tetanus) is high in OECD
countries. In most countries, more than 95% of 2-year-old
children receive the recommended measles and pertussis
vaccination, and rates for all countries are above 75%.
124
Figure 5.11.3 shows that the average percentage of children
aged 2 years who are vaccinated for hepatitis B across
countries with national programmes is also over 95%.
However, a number of countries do not currently require
children to be vaccinated by age two, or do not have routine
programmes and consequently the rates for these countries are significantly lower than for the other countries.
For example, in Denmark and Sweden, vaccination against
hepatitis B is not part of the general vaccination programme, and is only recommended to specific risk groups.
While Canada implemented universal hepatitis B vaccination for adolescents, not all provinces and territories offer
programmes in early infancy (Public Health Agency of
Canada, 2009; Mackie et al., 2009). In France, hepatitis B
vaccination remains controversial, given ongoing speculation over possible side effects, but vaccination coverage
among children under 2 has increased in recent years.
Definition and comparability
Vaccination rates reflect the percentage of children at
either age one or two who receive the respective
vaccination in the recommended timeframe. Childhood vaccination policies differ slightly across
countries. Thus, these indicators are based on the
actual policy in a given country. Some countries
administer combination vaccines (e.g. DTP for diphtheria, tetanus and pertussis) while others administer
the vaccinations separately. Some countries ascertain
vaccinations based on surveys and others based on
encounter data, which may influence the results.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
5. QUALITY OF CARE • CARE FOR COMMUNICABLE DISEASES
5.11. Childhood vaccination programmes
5.11.1 Vaccination rates for pertussis, children aged 2,
2009 (or nearest year)
Hungary
Finland
Czech Republic
Slovak Republic
Mexico
South Africa
Poland
Greece
France
Sweden
Russian Federation
Belgium
India
Iceland
China
Germany
Portugal
Luxembourg
Italy
Turkey
Switzerland
Slovenia
Japan
Estonia
Brazil
Spain
OECD
Netherlands
United Kingdom
Israel
Norway
Korea
Ireland
New Zealand
Australia
Denmark
Chile
United States
Austria
Indonesia
5.11.2 Vaccination rates for measles, children aged 2,
2009 (or nearest year)
Hungary
Greece
South Africa
China
Russian Federation
Brazil
Slovak Republic
Finland
Mexico
Czech Republic
Poland
Spain
Turkey
Israel
Sweden
Netherlands
Luxembourg
Germany
Portugal
Estonia
Slovenia
Belgium
India
Australia
OECD
Japan
Norway
Korea
Canada
Iceland
Chile
United States
Switzerland
Ireland
France
Italy
New Zealand
United Kingdom
Denmark
Indonesia
Austria
99.8
99.3
99.3
99.2
99.1
99.0
99.0
99.0
99.0
98.0
98.0
97.9
97.0
97.0
97.0
96.8
96.5
96.5
96.2
96.0
96.0
96.0
96.0
96.0
96.0
95.9
95.3
95.2
95.0
95.0
94.0
94.0
94.0
92.0
91.7
89.0
88.2
83.9
83.0
82.0
0
50
99.8
99.0
99.0
99.0
99.0
99.0
98.9
98.5
98.3
98.3
98.0
97.5
97.0
97.0
96.7
96.2
96.2
95.9
95.4
95.2
95.0
94.5
94.0
94.0
93.6
93.6
93.0
93.0
92.7
92.0
91.8
90.0
90.0
90.0
90.0
89.9
89.0
87.0
84.0
82.0
76.0
0
100
% of children vaccinated
Source: OECD Health Data 2011; WHO (2011f).
1 2 http://dx.doi.org/10.1787/888932525533
50
100
% of children vaccinated
Source: OECD Health Data 2011; WHO (2011f).
1 2 http://dx.doi.org/10.1787/888932525552
5.11.3 Vaccination rates for hepatitis B, children aged 2, 2009 (or nearest year)
Required and/or routine immunisation
%
100
Not required and/or not routinely provided by age 2
80
0.2
22.5
82.0
83.0
92.4
90.5
92.9
94.0
93.0
94.5
94.0
34.0
17.0
20
95.0
95.0
95.3
95.5
95.8
95.8
96.1
97.0
96.3
97.5
98.0
98.0
99.0
99.0
99.0
99.1
99.1
99.2
99.3
40
47.0
60
Cz
Sl
ec
h
R
ov ep
a k ub
Re li c
pu
b
Hu li c
ng
ar
M y
ex
ic
o
Ch
in
a
S o Isr
ut ae
h
l
Af
Ru
ric
ss
a
ia
n Pol a
Fe
de nd
ra
ti
Be on
lg
iu
Sl m
ov
e
Po ni a
r tu
g
Es al
to
Au ni a
st
ra
li a
It a
ly
Sp
a in
OE
CD
Br
az
il
L u Gr e
e
xe
c
m e
bo
ur
g
Ko
re
a
Ne Tur
w ke
y
Z
Ne e ala
n
th
d
Un er l a
i te nd
s
d
St
a
Ge tes
rm
an
Au y
st
r
In
do i a
ne
si
Fr a
an
ce
In
d
Sw ia
ed
e
Ca n
na
d
De
a
nm
ar
k
0
Note: OECD average only includes countries with required or routine immunisation.
Source: OECD Health Data 2011; WHO (2011f).
1 2 http://dx.doi.org/10.1787/888932525571
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
125
5. QUALITY OF CARE • CARE FOR COMMUNICABLE DISEASES
5.12. Influenza vaccination for older people
Influenza is a common infectious disease worldwide and
affects persons of all ages. For example, on average, between
5% and 20% of the population in the United States contracts
influenza each year (CDC, 2009). Most people with the illness
recover quickly, but elderly people and those with chronic
medical conditions are at higher risk for complications and
even death. Between 1979 and 2001, on average, influenza
accounted for more than 200 000 hospitalisations and
36 000 deaths per year in the United States (CDC, 2009). The
impact of influenza on the employed population is substantial, even though most influenza morbidity and mortality
occurs among the elderly and those with chronic conditions
(Keech et al., 1998). In Europe, influenza accounts for around
10% of sickness absence from work, while the cost of lost
productivity in France and Germany has been estimated to
be in the range of USD 9.3 billion to 14.1 billion per year
(Szucs, 2004).
Immunisation against seasonal influenza (or flu) for older
people has become increasingly widespread in many OECD
countries over the past decade. Influenza vaccination for
older people and patients with chronic conditions is
strongly recommended by governments and vaccination
experts in Europe, the United States and other countries
(Nicholson et al., 1995).
Figure 5.12.1 shows that, in 2009, the percentage of the
population aged 65 and over who were vaccinated against
influenza was 56% on average across OECD countries.
However, there is a wide variation in vaccination rates,
ranging from 1% in Estonia, 22 % in Slovenia and the Czech
Republic, up to 75% in Australia, 77% in the Netherlands,
and 88% in Chile and Mexico. The high rate in Chile reflects
the participation in an annual widespread vaccination
campaign. The rate in Mexico likely reflects the intensive
vaccination activities related to the 2009 H1N1 pandemic.
Figure 5.12.2 indicates that while the OECD average increased
markedly between 1999 and 2004, it remained relatively
stable between 2004 and 2009. Since 2004, some countries
marginally increased their coverage whereas others reduced
their coverage, most notably some of the countries which
were already below the OECD average, such as Slovenia and
Hungary.
A number of factors have contributed to the current high
levels in influenza immunisation rates in some OECD countries, including greater acceptance of preventive health
services by patients and practitioners, improved public
health insurance coverage for vaccines and wider delivery
by health care providers other than physicians (Singleton
126
et al., 2000). A number of barriers need to be overcome in
other countries if they wish to further increase their coverage rates. For example, possible reasons put forward for the
relatively low vaccination rates in Austria include poor
public awareness, inadequate insurance coverage of
related costs and lack of consensus within the Austrian
medical profession about the importance of vaccination
(Kunze et al., 2007).
Particularly virulent strains of the virus, similar to the
H5N1 avian influenza sub-type, can cause pandemics with
a much wider impact than seasonal influenza. The potential impact of influenza not just on the health of people but
also on economic activity has been demonstrated again by
the 2009 H1N1 epidemic (also referred to as “swine flu”).
Although assessments of the economic impact of the
H1N1 epidemic differ, the World Bank estimated in 2008
that a severe flu pandemic could cost the global economy
up to 4.8% of world domestic product (Burns et al., 2008).
WHO reports that vaccines are one of the most valuable
ways to protect people during influenza epidemics and
pandemics. Other measures include anti-viral and other
drugs, social distancing and personal hygiene. Established
national infrastructure and processes for seasonal vaccination programmes can signal an enhanced preparedness to
respond to an influenza outbreak. However, scientific
evidence suggests that the seasonal influenza vaccines that
are routinely provided across OECD countries offer little or
no protection against influenza A (H1N1) (WHO, 2009c).
Definition and comparability
Influenza vaccination rate refers to the number of
people aged 65 and older who have received an
annual influenza vaccination, divided by the total
number of people over 65 years of age. The main
limitation in terms of data comparability arises from
the use of different data sources, whether survey or
programme, which are susceptible to different types
of errors and biases. For example, data from population surveys may reflect some variation due to recall
errors and irregularity of administration.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
ec
h
ak
ov
bl
bl
ia
ic
ic
ria
1
22.0
22.1
30
en
pu
pu
st
30.5
36.1
38.9
43.0
48.5
h
ak
ec
ov
Cz
Sl
y
a
ia
ic
ic
ni
en
bl
bl
ria
to
ov
pu
pu
Es
Sl
Re
Re
st
ar
k
d
ar
an
ng
Au
Hu
nl
l
n
ga
nd
pa
nm
Ja
Fi
De
r tu
la
1
1.4
22.0
22.1
30
Sl
Re
Re
y
40
Cz
ov
ar
d
k
50.0
52.2
Po
Ir e
g
nd
ur
la
bo
er
m
it z
xe
CD
30.5
43.0
36.1
38.9
40
Au
ng
an
ar
n
50
Hu
nl
nm
l
Lu
OE
el
y1
ra
an
Is
rm
m
n
en
iu
ai
ed
lg
Sw
Be
d
ly
an
da
es
ce
It a
al
na
Sp
Ze
Ca
Ge
w
Sw
Ne
at
an
St
Fr
a
m
re
do
Ko
ng
d
Ki
i te
d
53.8
54.7
56.0
56.3
50.0
66.3
66.4
66.5
64.0
65.0
77.0
73.3
73.6
74.6
71.0
66.7
65.7
61.1
56.7
52.2
48.5
50
Fi
De
pa
53.8
54.7
56.0
56.3
61.1
2004
Ja
nd
ga
la
r tu
Ir e
g
nd
ur
la
bo
er
m
Po
xe
CD
60
Lu
it z
y1
65.0
65.7
1999
OE
m
n
66.3
66.4
66.5
66.7
i te
Un
Un
li a
s
il e
nd
ra
la
st
er
Au
th
o
60
Sw
iu
ai
an
lg
rm
Be
d
ly
an
da
It a
al
na
Sp
Ze
Ca
71.0
73.3
73.6
74.6
77.0
%
100
Ge
w
es
ce
70
Ne
at
an
a
m
re
li a
do
St
Fr
ng
d
Ki
i te
d
Ko
s
87.9
Ne
ic
Ch
ex
70
Sl
i te
nd
80
ra
la
st
er
88.2
M
80
Au
th
o
il e
ic
90
Ch
ex
87.9
88.2
90
Un
Un
Ne
M
5. QUALITY OF CARE • CARE FOR COMMUNICABLE DISEASES
5.12. Influenza vaccination for older people
%
100
5.12.1 Influenza vaccination coverage, population aged 65 and over, 2009 (or nearest year)
20
10
0
1. Population aged 60 and over.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525590
5.12.2 Vaccination rates against influenza, population aged 65 and over, 1999-2009 (or nearest year)
2009
20
10
0
1. Population aged 60 and over.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525609
127
6. ACCESS TO CARE
6.1. Unmet health care needs
6.2. Coverage for health care
6.3. Burden of out-of-pocket health expenditure
6.4. Geographic distribution of doctors
6.5. Inequalities in doctor consultations
6.6. Inequalities in dentist consultations
6.7. Inequalities in cancer screening
6.8. Waiting times
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
129
6. ACCESS TO CARE
6.1. Unmet health care needs
Most OECD countries aim to provide equal access to health
care for people in equal need. One method of gauging
equity of access to services is through assessing reports of
unmet needs for health care for some reason. The problems that patients report in getting care when they are ill or
injured often reflect significant barriers to care.
Some common reasons that people give for not receiving
care include excessive treatment costs, long waiting times,
not being able to take time off work or needing to look after
children or others, or that they had to travel too far to
receive care. Differences in the reporting of unmet care
needs across countries could be due to differences in survey
questions, because of socio-cultural reasons, or because of
reactions to current national health care debates. However,
these factors play a lesser role in explaining any differences
among population groups within each country. It is also
important to consider self-reported unmet care needs in
conjunction with other indicators of potential barriers to
access, such as the extent of health insurance coverage and
the amount out-of-pocket payments (see Indicators 6.2
“Coverage for health care” and 6.3 “Burden of out-of-pocket
health expenditure”).
In most OECD countries, a majority of the population report
no unmet care needs. However, in a European survey
undertaken in 2009, significant proportions in some
countries reported having unmet needs. Generally, it is
women, and people in low-income groups who report not
getting the care they need.
Three possible reasons that might lead to access problems
are presented in Figure 6.1.1. In Greece, Italy, Poland and
Portugal, the most common reason is treatment cost.
Although fewer than five per cent of survey respondents in
these countries indicated that they were affected, the
burden fell heaviest on low income earners. Waiting times
were an issue for some in Poland, Finland and Estonia.
Travelling distance did not feature as a major problem
except in Norway, where one-third of the small number of
persons indicating that they had an unmet care need said
that it was because of the distance they had to travel to
receive care.
A larger proportion of the population indicates unmet
needs for dental care than for medical care. Portugal
(14.5%) and a group of countries including Iceland, Sweden,
Norway, Italy and Poland (all around 10%) reported the
highest rates in 2009 (Figure 6.1.2). Large inequalities in
unmet dental care needs were evident between high and
low income groups in Portugal and Norway, as well as in
Estonia and Germany, although in the latter two countries,
average levels of unmet dental care were low.
130
Inequalities in self-reported unmet medical care needs are
also evident in non-European countries (Figure 6.1.3).
Again, foregone care due to cost is more prevalent among
lower income groups. There are large differences in the size
of these inequalities across countries, as shown by much
lower levels in the United Kingdom than in the United
States. In the United States, more than one-third of the
adult population with below-average incomes reported
having some type of unmet care need due to cost in 2010
(Commonwealth Fund, 2010). Adults with below-average
incomes who have health insurance report significantly
less access problems than do their uninsured counterparts
(Blendon et al., 2002). The proportion of the population
reporting cost-related access problems declined markedly
between 2007 and 2010 in New Zealand, and to a lesser
extent in the United States and Australia (Commonwealth
Fund, 2008, 2010).
Definition and comparability
Questions on unmet health care needs are a feature of
a number of national and cross-national health interview surveys, including the European Union Statistics
on Income and Living Conditions survey (EU-SILC)
a n d t h e i n t e r n a t i o n a l h e a l t h p o l i cy s u r v ey s
conducted by the Commonwealth Fund. No single
survey or study on unmet care needs has been
conducted across all OECD countries.
To determine unmet medical care, individuals are
typically asked whether there was a time in the
previous 12 months when they felt they needed
health care services but did not receive them,
followed by a question as to why the need for care
was unmet. Common reasons include that care was
too expensive, the waiting time was too long, or the
travelling distance to receive care was too far.
Information on both unmet care and socio-economic
status are derived from the same survey, although
question and answer categories, age groups surveyed
and measures to grade socio-economic status can
vary. Cultural factors and policy debates may also
affect attitudes to unmet care. Caution is needed in
comparing the magnitude of inequalities across
countries.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.1. Unmet health care needs
6.1.1 Unmet need for a medical examination, selected reasons
by income quintile, European countries, 2009
Quintile 1
Higher income
6.1.2 Unmet need for a dental examination,
by income quintile, European countries, 2009
Quintile 5
Lower income
Could not afford to
Waiting time
High
income
Portugal
Austria
Spain
Czech Republic
Iceland
Denmark
Sweden
Estonia
Italy
Finland
Poland
France
Norway
Germany
France
Greece
Greece
Switzerland
Hungary
Iceland
Finland
Ireland
Hungary
Estonia
Italy
Luxembourg
Denmark
Netherlands
United Kingdom
Norway
Czech Republic
Poland
Germany
Austria
Portugal
Slovak Republic
Slovak Republic
Ireland
Slovenia
3
Low
income
Too far to travel
Belgium
6
%
Middle
income
Spain
Luxembourg
Sweden
Netherlands
Switzerland
Belgium
United Kingdom
Slovenia
0
0
3
6
9
12
%
Source: EU-SILC.
0
5
10
15
20
25
%
Source: EU-SILC.
1 2 http://dx.doi.org/10.1787/888932525628
1 2 http://dx.doi.org/10.1787/888932525647
6.1.3 Unmet care need1 due to costs in eleven OECD countries, by income group, 2010
Above average income
%
Below average income
50
39
40
30
27
22
21
20
10
12
8
7
4
8
6
5
4
17
15
14
13
12
20
18
17
4
3
es
St
d
i te
Un
Ge
rm
at
an
y
li a
Au
st
ra
ay
rw
No
da
na
Ca
an
Fr
al
Ne
w
Ze
Sw
ce
d
an
en
ed
s
nd
Ne
th
er
la
la
er
it z
Sw
Un
i te
d
Ki
ng
do
m
nd
0
1. Either did not visit doctor with medical problem, did not get recommended care or did not fill/skipped prescription.
Source: Commonwealth Fund (2010).
1 2 http://dx.doi.org/10.1787/888932525666
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
131
6. ACCESS TO CARE
6.2. Coverage for health care
Health care coverage promotes access to medical goods
and services, as well as providing financial security against
unexpected or serious illness (OECD, 2004a). However, total
health insurance coverage – both public and private – is an
imperfect indicator of accessibility, since the range of
services covered and the degree of cost-sharing applied to
those services can vary across countries.
Most OECD countries have achieved near-universal coverage of health-care costs for a core set of services, which
usually include consultations with doctors and specialists,
tests and examinations, and surgical and therapeutic
procedures (Figure 6.2.1). Generally, services such as dental
care and supply of pharmaceutical drugs are partially
covered, although there are a number of countries where
these services must be purchased separately (see Annex
Table A.5).
Four OECD countries do not have universal health coverage.
Chile has a dual health care system with coverage through
the public National Health Insurance Fund, or through private health insurance companies and other not-for-profit
agencies. A proportion of the population, however, remains
without specific coverage. In Mexico, the “Seguro Popular”
voluntary health insurance scheme was introduced in 2004
to provide coverage for the poor and uninsured, and has
grown rapidly so that by 2009 around three quarters of the
population were covered. Public coverage in Turkey has
increased rapidly in recent years, reaching over 80%
in 2009.
In the United States, coverage is provided mainly through
private health insurance, and 55% of the total population
had this for their basic coverage in 2009. Publicly-financed
coverage insured 26% of the total population (the elderly,
people with low income or with disabilities), leaving 19% of
the population – mostly under 65 years of age – without
health coverage. Most uninsured persons cite the increasing cost of premiums as the reason for their lack of coverage (NCHS, 2009). Employers, particularly smaller ones, are
also less likely to offer coverage to workers (OECD, 2008b).
The recent rise in the proportion of uninsured can be
attributed to the effects of the recession and the loss of
employment, accompanied by the loss of health care coverage (KFF, 2010).The problem of persistent uninsurance is a
major barrier to receiving health care, and more broadly, to
reducing health inequalities among population groups
(AHRQ, 2011b; HHS Office of Health Reform, 2009). The 2010
Patient Protection and Affordable Care Act seeks to
increase insurance coverage in the United States.
Basic primary health coverage, whether provided through
public or private insurance, generally covers a defined
“basket” of benefits, in many cases with cost-sharing. In
132
some countries, additional health coverage can be
purchased through private insurance to cover any costsharing left after basic coverage (complementary insurance), add additional services (supplementary insurance)
or provide faster access or larger choice to providers (duplicate insurance). Among the 34 OECD countries, ten report
private coverage for over half of the population in 2009
(Figure 6.2.2).
Private health insurance offers 94% of the French population complementary insurance to cover cost-sharing in the
social security system. The Netherlands has the largest
supplementary market (90% of the population), followed by
Israel (81%), whereby private insurance pays for prescription drugs and dental care that are not publicly reimbursed.
Duplicate markets, providing faster private-sector access to
medical services where there are waiting times in public
systems, are largest in Ireland (51%) and Australia (45%).
The population covered by private health insurance is
positively correlated to the share of total health spending
accounted for by private health insurance (Figure 6.2.3).
The importance of private health insurance is not linked to
a countries’ economic development. Other factors are more
likely to explain market development, including gaps in
access to publicly financed services, the way private
providers are financed, government interventions directed
at private health insurance markets, and historical development (OECD, 2004b).
Definition and comparability
Coverage for health care is the share of the population
receiving a defined set of health care goods and services under public programmes and through private
health insurance. It includes those covered in their
own name and their dependents. Public coverage
refers both to government programmes, generally
financed by taxation, and social health insurance,
generally financed by payroll taxes. Take-up of private
health insurance is often voluntary, although it may
be mandatory by law or compulsory for employees as
part of their working conditions. Premiums are generally non-income-related, although the purchase of
private cover can be subsidised by the government.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.2. Coverage for health care
6.2.1 Health insurance coverage for a core set of services,
2009
Total public coverage
Chile
Mexico
Turkey
United States
Slovak Republic
Estonia
Poland
Luxembourg
Netherlands
Austria
Spain
Belgium
France
Germany
Iceland
United Kingdom
Switzerland
Sweden
Slovenia
Portugal
Norway
New Zealand
Korea
Japan
Italy
Israel
Ireland
Hungary
Greece
Finland
Denmark
Czech Republic
Canada
Australia
6.2.2 Private health insurance coverage, by type,
2009
Primary private health coverage
Primary
73.5
74.0
80.8
26.4
93.7
90.0
Israel
80.7
Belgium
76.4
Slovenia
74.2
Canada
68.0
United States
99.2
99.5
99.9
89.2
99.9
62.3
Luxembourg
10.8
0.1
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
40
Duplicate
Netherlands
54.9
20
Supplementary
France
95.2
95.2
97.6
97.8
98.8
99.0
0
Complementary
55.8
Australia
51.2
Ireland
50.7
Austria
33.8
New Zealand
32.2
Germany
30.4
Switzerland
29.5
Spain
19.7
Portugal
19.4
Denmark
18.0
Chile
16.3
Mexico
6.0
Turkey
2.5
Iceland
0
60
80
100
Percentage of total population
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525685
0.1
20
40
60
80
100
Percentage of total population
Note: Private health insurance can fulfil several roles. For instance, it
can be both duplicate and supplementary in Australia and Israel; and
both complementary and supplementary in Denmark, Ireland and
New Zealand.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525704
6.2.3 Private health insurance, population covered and share in total health expenditure, 2009
Share of private health insurance in total expenditure on health (%)
40
USA
35
30
25
20
CHL
15
CAN
10
DEU
CHE
5
ESP
PRT
NZL
AUS
AUT
0
10
20
30
ISR
BEL
LUX
DNK
0
40
50
FRA
SVN
60
NLD
70
80
90
100
Share of population covered by private health insurance (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525723
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
133
6. ACCESS TO CARE
6.3. Burden of out-of-pocket health expenditure
Financial protection through public or private health insurance substantially reduces the amount that people pay
directly for medical care, yet in some countries the burden of
out-of-pocket spending can still create barriers to health
care access and use. Households that have difficulties
paying medical bills may delay or forgo needed health care
(Hoffman et al., 2005; May and Cunningham, in Banthin et al.,
2008). On average across OECD countries, 19% of health
spending is paid directly by patients (see Indicator 7.5
“Financing of health care”).
The US Medical Expenditure Panel Survey found that 28% of
Americans living in a poor family (defined as a family
income below the Federal poverty level) were spending more
than 10% of their after-tax family income for health services
and health insurance premiums in 2004, compared with
10% of Americans in a high income family (Banthin et al.,
2008). Among older persons in the United States, lowincome individuals pay the highest out-of-pocket payments
in relation to their income, with prescription drugs comprising the biggest share (Corrieri et al., 2010).
In contrast to publicly-funded care, out-of-pocket payments
rely on the ability to pay. If the financing of health care
becomes more dependent on out-of-pocket payments, its
burden is, in theory, shifted towards those who use services
more, and possibly from high to low income earners, where
health care needs are higher. In practice, many countries
have exemptions and caps to out-of-pocket payments
for lower income groups to protect health care access.
Switzerland, for example, has a high proportion of out-ofpocket expenditure, but it has cost-sharing exemptions for
large families, social-assistance beneficiaries and others.
There is an annual cap on deductibles and co-insurance
payments (Paris et al., 2010).
Households in the lowest income category in the Netherlands
spent 6.5% of their disposable income on out-of-pocket
payments in 2007, whereas in the highest income category
the proportion was 1.5% (Westert et al., 2010). In Turkey,
results from the 2006 Household Budget Survey indicate that
out-of-pocket spending was reasonably progressive, in that
poorer families spent 3.4% of their household consumption
on health, whereas in richer households this was 4.2% (OECD
and World Bank, 2008).
The burden of out-of-pocket health spending can be
measured either by its share of total household income or
its share of total household consumption. The average
share varied considerably across OECD countries in 2010,
representing less than 2% of total household consumption
in countries such as Turkey, the Netherlands, France and
the United Kingdom, but more than 5% in Greece and
Switzerland (Figure 6.3.1). The United States, with 3.1% of
consumption spent on out-of-pocket health services, is
close to the average.
Persons who are older or with lower incomes tend to have
greater levels of illness and are more likely to need health
care, so it is important to determine whether the distribution of out-of-pocket spending varies across the population. A cross-national survey conducted in eleven OECD
countries found that high out-of-pocket spending (defined
as more than USD 1 000 per year) was uncommon for both
low- and high-income earners in the United Kingdom,
Sweden and France (Schoen et al., 2010). In other countries,
adults with above-average incomes were more likely to
report high out-of-pocket spending. Even so, in Switzerland
and the United States, the proportion of poorer adults with
high out-of-pocket expenditure was high, at 20% and 29%
respectively (Figure 6.3.2).
134
A small proportion of households in OECD countries face
very high or “catastrophic” health expenditure each year,
perhaps as a result of severe illness or major injury (WHO,
2010c). Countries that have a greater reliance on out-ofpocket health care expenditure tend also to have a higher
proportion of households with catastrophic expenditures.
In some countries, the imposition of user fees may mean
that lower income households forgo health care altogether,
and thus not use enough services to incur catastrophic
expenditures.
Definition and comparability
Out-of-pocket payments are expenditures borne
directly by a patient where insurance does not cover
the full cost of the health good or service. They
include cost-sharing, self-medication and other
expenditure paid directly by private households. In
some countries, estimations of informal payments to
health care providers are also included.
Information on of out-of-pocket expenditure is
collected through household expenditure surveys in a
number of OECD countries.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.3. Burden of out-of-pocket health expenditure
6.3.1 Out-of-pocket expenditure as a share of final household consumption, 2009 (or nearest year)
%
7
6.2
6
5.4
5
4.7
4.6
4.3
4.2
4.2
4.1
3.9
3.5
4
3.4
3.4
3.4
3.3
3.3
3.2
3.1
3.1
3.1
3.0
2.9
2.9
2.8
2.8
2.7
2.5
2.4
2.4
2.4
3
2.4
2.2
1.6
1.6
1.5
1.5
2
Sw
it z
er
la
Gr n d
ee
c
M e1
ex
ic
o
Ch
il e
Ko
r
Be ea
lg
iu
Po m
r tu
ga
Sl
l
ov
a k Isr
Re ael
pu
b
S w li c
ed
en
Sp
Hu a in
ng
a
No r y
rw
a
Fi y
nl
an
Ic d
el
an
d
OE
De CD
nm
ar
k
Un
i te It a
ly
d
St
at
e
Au s
st
r
Ca ia
n
Au ada
st
ra
li a
Lu E s to
xe ni
m a
bo
ur
Po g
la
n
Ir e d
la
C z Ge nd
ec rm
h
R any
N e epu
w bli
Ze c
al
an
d
Ja
Un S p a n
i te lov
e
d
K i ni a
ng
do
m
Ne Fr a
th nc e
er
la
nd
Tu s
rk
ey
1
1. Private sector total.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525742
6.3.2 Out-of-pocket medical costs of USD 1 000 or more in the past year by income level, eleven OECD countries, 2010
Above average income
Below average income
45
United States
29
34
Switzerland
20
31
Australia
16
17
Canada
12
16
Norway
15
11
Netherlands
7
11
New Zealand
6
10
Germany
5
5
5
France
2
2
Sweden
0
0
United Kingdom
0
10
20
30
40
50
Percentage of adults
Source: Schoen et al. (2010).
1 2 http://dx.doi.org/10.1787/888932525761
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
135
6. ACCESS TO CARE
6.4. Geographic distribution of doctors
Access to medical care requires an adequate number and
proper distribution of physicians. Shortages of physicians
in a geographic region can lead to increased travel times for
patients and higher caseloads for doctors. The maldistribution of physicians is a challenge in a number of OECD
countries, especially in territories with remote and sparsely
populated areas, with long travelling times to the nearest
urban region.
Measuring disparities in the “density” of physicians among
regions within the same country gives some indication of
the accessibility of doctor services. Regions, however, may
have high physician density, but persons living in
geographically remote areas may still face long travel times
to receive medical care. Not only should the density of
physicians match the regions’ population, but the services
that physicians offer should also match need, whether
these are for GPs or specialists. Medical needs may be
higher in remote areas with an older than average population, for example.
OECD countries display very different levels in the number of
practising physicians per 1 000 population, ranging from lows
of less than two in Chile, Turkey and Korea, to highs of four
and more in Norway, Austria and Greece (see Indicator 3.2
“Medical doctors”).
In many countries, there are a greater number of physicians per capita in capital cities (Figure 6.4.1). In the Czech
Republic for example, Prague has a density of physicians
almost twice the country average. Austria, Belgium, Greece,
Portugal, the Slovak Republic and the United States also
have physicians concentrated in capital cities. There are
also disparities in specialists, with a greater concentration
in capital cities in Mexico, the Slovak Republic and Turkey
(OECD, 2009b). In Japan, an urban-biased distribution is
reported for a variety of specialists (Matsumoto, 2010).
The density of physicians is greater in regions with a high
urban population, due to the concentration of services such
as surgery and specialised practitioners (Figure 6.4.2). In
Canada, just under 16% of “family physicians” (mostly
general practitioners) and only 2% of specialists were
located in rural areas and small towns in 2006, whereas
24% of the population resided in these areas (Dumont et al.,
2008). Similarly, in the United States, 17% of the population
lived in non-metropolitan areas in 2004, but only 9% of
practising patient care physicians were located in these
areas, and almost 50% of US counties had no obstetricians
or gynaecologists providing direct patient care (NCHS,
2007). In France, 22% of general practitioners and 4% of
specialists practised in towns of up to 10 000 population
in 2010, whereas 36% of the population resided in these
areas (DREES, 2010).
136
A number of factors affect the distribution of physicians.
These include the population size and economic development of a region (which are related to market size and
income potential), the regions’ professional climate (the
possibility of interaction with colleagues, and access to
hospitals and other medical facilities) and the extent of
social amenities (Huber et al., 2008).
Experience shows that a mix of policies are needed to
address maldistribution issues (Simoens and Hurst, 2006;
Dolea et al., 2010). In Canada, foreign-trained doctors
comprised an average of 30% of the labour force in rural
and remote areas in 2006. Telehealth and nurse practitioners also assist in providing primary care. Incentives have
been developed to train health professionals with rural
background and exposure (Dumont et al., 2008). In Turkey,
new health staff have been assigned to areas with low
physician density, although the challenge remains to
match staff with areas of greatest need (OECD and World
Bank, 2008). In July 2010, WHO issued a set of Global Policy
Recommendations on different retention strategies for
health workers in remote and rural areas (WHO, 2010).
Definition and comparability
For more detail on practicing physicians, see
Indicator 3.2 “Medical doctors”. The geographic distribution of physicians can be examined by calculating
rates of practising physicians per regional population.
Since countries use a variety of geographical classifications, the OECD has classified regions into two
territorial Levels. The higher level (Territorial Level 2)
consists of 362 large regions, which correspond
closely to national administrative regions (OECD,
2011b). However, these regions may contain a mixture
of urban, intermediate and rural populations. Further
sub-regional analysis may be necessary to obtain a
more complete picture of geographic distribution of
physicians. A number of countries have developed
schemes to classify populations into urban-rural
categories, although these are not standard, making
cross-national comparisons difficult.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.4. Geographic distribution of doctors
6.4.1 Physician density, by territorial level 2 regions, 2008 (or nearest year)
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Israel
Italy
Japan
Korea
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Russian Federation
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
Australian Capital Territory
Vienna
Brussels
NW Territories
and Nunavut
Prague
Attiki
Northern District
Liguria
Lisboa
Saint
Petersburg
Bratislava
District
of Columbia
0
2
4
6
8
10
Per 1 000 population
Source: OECD (2011b).
1 2 http://dx.doi.org/10.1787/888932525780
6.4.2 Physician density in rural and urban regions, four OECD countries, latest year available
Urban
Rural/remote
Per 100 000 population
500
453
400
376
300
217
200
210
187
120
100
113
84
0
Australia, 2008
Canada, 2004
France, 2010
United States, 2005
Note: Classifications of rural and urban regions differ between countries.
Source: AIHW (2010b); CIHI (2005); DREES (2010); Fordyce et al. (2007).
1 2 http://dx.doi.org/10.1787/888932525799
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
137
6. ACCESS TO CARE
6.5. Inequalities in doctor consultations
Measuring rates of health care utilisation, such as doctor
consultations, is one way of identifying whether there are
access problems for certain populations. Difficulties in
consulting doctors because of excess cost, long waiting
periods or travelling time, and lack of knowledge or incentive may lead to lower utilisation, and in turn to poorer
health status and increased health inequalities.
The average number of doctor consultations per capita
varies greatly across OECD countries (see Indicator 4.1
“Consultations with doctors”). But there are also significant
differences among socio-economic groups within countries, as determined by income, education, or occupation.
Ongoing OECD work is updating an earlier study by van
Doorslaer et al. (2004) on income-related inequality in visits
to doctors in a number of OECD countries. The figures show
the horizontal inequity index – a measure of inequality in
health care use – for the probability of a doctor, GP and
specialist visit. The probability is unequal if the horizontal
inequity index is significantly different from zero. It favours
low income groups when it is below zero, and high income
groups when it is above zero. The index is adjusted for
differences in need for health care, because health problems
are more frequent and more severe among lower socioeconomic groups.
Doctor visits were more likely among higher income
persons in 12 of 15 countries (Figure 6.5.1), however most
countries have low levels of inequality. Only in the United
States was a higher level of inequality apparent. In three
OECD countries – the United Kingdom, the Czech Republic
and Slovenia – given the same need, high income people
were as likely to see a doctor as those with low income. In
Korea, a similar study found income-related equality for
western doctor visits (Lu et al., 2007).
Regarding the frequency of visits, six countries out of
14 display pro-rich inequalities (Canada, France, Finland,
Spain, the United States, and Poland). In the other eight
countries, low income people saw a doctor as frequently as
high income people (Belgium, Slovenia, New Zealand, the
Czech Republic, Hungary, Germany, the Slovak Republic,
and Estonia).
There is a difference between GP and specialist visits. The
probability of a GP visit was equally distributed in most
countries (Figure 6.5.2). When inequality does exist, it is
often positive, indicating a pro-rich distribution, but the
degree of inequality is small. Lower income people,
however, consult a GP more frequently.
A different story emerges for specialist visits – in nearly all
countries, high income people are more likely to see a
specialist than those with low income (Figure 6.5.3), and
138
also more frequently. In Finland, the relationship is
stronger for visits to private specialists because of the size
of patient co-payments, a high-income distribution of
workplace services which facilitate access to specialist
care, and the large private ambulatory care sector
(NOMESCO, 2004; OECD, 2005b). It Italy, regional variations
in health care access explain most of the pro-rich inequalities in specialist visits (Masseria and Giannoni, 2010).
Consistent with these findings, an earlier study found that
people with higher education levels tend to use specialist
care more, and the same was true for GP use in several
countries (France, Portugal and Hungary) (Or et al., 2008).
The study suggests that, beyond the direct cost of care,
other health system characteristics are important in reducing social inequalities in health care utilisation, such as the
role given to the GP and the organisation of primary care.
Social inequalities in specialist use are less in countries
with a National Health System and where GPs act as
gatekeepers. Countries with established primary care
networks may place greater emphasis on deprived populations, and gatekeeping often provides simpler access and
better guidance for people in lower socio-economic
positions (Or et al., 2008).
Definition and comparability
Consultations with doctors refer to the probability
and frequency of visits with physicians, including
both generalists and specialists (except in the United
States where this distinction is not possible).
OECD estimates come from health interview or
household surveys conducted around 2009, and rely
on self-report. Inequalities in doctor consultations are
assessed in terms of household income. The number
of doctor consultations is adjusted for need, based on
self-reported information about health status.
Differing survey questions and response categories
may affect cross-national comparisons. Surveyed
groups may vary in age range, and the measures used
to grade income can also vary. Caution is therefore
needed when interpreting inequalities in health care
utilisation across countries.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.5. Inequalities in doctor consultations
6.5.1 Horizontal inequity indices for probability of a doctor visit (with 95% confidence interval),
15 OECD countries, 2009 (or nearest year)
0.10
0.08
0.06
0.04
0.02
0
-0.02
es
a
i te
d
Es
St
to
at
ni
d
nl
Fi
Ca
Po
la
na
an
nd
da
y
Hu
Ze
al
ng
an
ar
d
ic
Un
ov
Ne
ak
w
Re
Fr
pu
an
bl
ce
ia
en
Sl
Be
ov
lg
Sp
iu
ai
m
n
y
rm
Ge
Sl
Un
Cz
i te
ec
d
h
Ki
Re
ng
pu
do
bl
an
ic
m
-0.04
Source: OECD estimates (2011).
1 2 http://dx.doi.org/10.1787/888932525818
6.5.2 Horizontal inequity indices for probability of a GP visit (with 95% confidence interval),
14 OECD countries, 2009 (or nearest year)
0.10
0.08
0.06
0.04
0.02
0
-0.02
ov
a
ni
Es
to
da
na
Ca
an
nl
Fi
Po
d
nd
la
an
al
Ze
Ne
w
Re
ak
Sl
Sl
Un
d
ic
pu
en
ov
an
Fr
d
i te
ec
Cz
bl
ia
ce
y
ar
ng
Hu
Ki
Be
ng
lg
do
iu
m
m
ria
st
Au
h
Re
pu
Sp
bl
ai
ic
n
-0.04
Source: OECD estimates (2011).
1 2 http://dx.doi.org/10.1787/888932525837
6.5.3 HorizontaI inequity indices for probability of a specialist visit (with 95% confidence interval),
13 OECD countries, 2009 (or nearest year)
0.10
0.08
0.06
0.04
0.02
0
-0.02
Fr
an
ce
n
ai
Sp
nd
la
Po
m
iu
lg
Be
Ca
na
da
a
ni
to
Es
Fi
nl
an
d
d
Ne
w
Ze
al
ng
Sl
ov
ak
Hu
pu
Re
an
ar
y
ic
bl
ia
en
ov
Sl
h
ec
Cz
Un
i te
d
Ki
Re
ng
pu
do
bl
ic
m
-0.04
Note: The probability of a doctor, GP or specialist visit is inequitable if the horizontal inequity index is significantly different from zero. It
favours low income groups when it is below zero, and high income groups when it is above zero. The index is adjusted for need.
Source: OECD estimates (2011).
1 2 http://dx.doi.org/10.1787/888932525856
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
139
6. ACCESS TO CARE
6.6. Inequalities in dentist consultations
Dental caries, periodontal (gum) disease and tooth loss are
common problems in OECD countries. Despite improvements, problems in access persist, most commonly among
disadvantaged and low income groups. In the United States,
over 40% of low income persons aged 20-64 years had
untreated dental caries in 2005-08, compared with only
16% of high income persons (NCHS, 2011). In Finland, onequarter of adults with lower education had six or more missing teeth, while less than 10% of those with higher education
had the same amount of tooth loss (Kaikkonen, 2007).
Strategies to improve access to dental care for disadvantaged or underserviced populations include reducing
financial and non-financial barriers, and promoting an
adequate dental workforce to respond to demand.
Most public health authorities recommend an annual visit
to a dentist. The average number of per capita consultations varied widely in 2009, from over three in Japan and
over two in Belgium, the Netherlands and Israel, to 0.1 in
Mexico and 0.3 in Turkey, with an OECD average of 1.3
(Figure 6.6.1). Some of this variation can be explained by
the differing availability of dentists. In general, as the
number of dentists increases, so does the number of
consultations per capita (OECD, 2009b).
Recent OECD findings show that high income persons were
more likely to visit a dentist within the last 12 months
(Figure 6.6.2). This is despite differences in public or private
dental coverage and the amount of reimbursement.
Inequalities are larger in countries with a lower probability
of a dental visit such as Hungary, Poland, the United States
and Spain. Denmark and France have different recall
periods and this affects the average probability of a dental
visit, but not the level of inequality. Both countries are
among the most equitable for the probability of a dental
visit.
Inequalities in types of care, whether curative or preventive, are also apparent. A recent study in Canada shows
that access to preventive care is more common among
higher income persons (Grignon et al., 2010). There are
similar income-related inequalities in dental service utilisation among Europeans aged 50 years and over (Listl,
2011), mostly due to inequalities in preventive dental visits.
In the United States, more recent data confirms the wide
differences between income groups in the probability of a
dental visit. Less than half of poor and near-poor persons
visited a dentist in 2009 compared with close to 70% of
middle and high income persons. This gap has remained
largely unchanged over the past decade (Figure 6.6.3). As in
many other countries, access to dental care in the United
140
States is generally more difficult than for medical care, since
a smaller proportion of persons have dental insurance. More
adults report that they did not get needed dental care due to
costs than medical care (see Indicator 6.1, “Unmet health
care needs”).
Oral health care is mostly provided by private dental practitioners. Treatment is costly, averaging 5% of total health
expenditure (and 16% of private health expenditure) across
OECD countries in 2009. In countries such as Australia,
Canada and New Zealand, adult dental care is generally not
part of the basic package of public care insurance, although
some care is provided for people with disabilities, those
with low income and other disadvantaged groups. In other
countries, prevention and treatment are covered, but a
share of costs is borne by patients, and this may create
access problems for low-income groups (Figure 6.6.4).
Some countries, such as the Nordic countries and the
United Kingdom, provide public dental care, particularly to
children and disadvantaged groups.
Definition and comparability
Consultations with dentists refer to the probability
and the number of contacts with dentists. Estimates
usually come from health interview or household
surveys, and rely on self-report, although some
countries provide administrative data. In Germany,
the Social Health Insurance Scheme only counts the
first reimbursement during a three-month period,
and so under-reporting may occur.
Inequalities in dental consultations are here assessed
in terms of household income.
Differing survey questions and response categories may
affect valid cross-national comparisons. Surveyed
groups may vary in age range, and the measures used to
grade income level can also vary. Most countries refer to
dental consultations during the past 12 months, except
for France (past 24 months) and Denmark (past three
months). The difference in recall periods is likely to
have an impact on the average probability of dentist
visits, but not on the level of inequality. Caution is
herefore needed when interpreting inequalities across
countries.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.6. Inequalities in dentist consultations
6.6.1 Average number of dentist consultations per capita,
2009 (or nearest year)
6.6.2 Probability of a dental visit in the past 12 months,
by income group, 2009 (or nearest year)
Low income
Mexico
Turkey
Luxembourg
Chile
United Kingdom
Hungary
Poland
Denmark
Italy
United States
Austria
Switzerland
Finland
OECD
Australia
Estonia
Germany
Slovak Republic
Korea
Spain
France
Czech Republic
Belgium
Netherlands
Israel
Japan
Average
High income
0.1
0.3
0.6
0.7
0.7
0.8
0.8
0.9
0.9
1.0
France 1
Czech Republic
United Kingdom
Slovak Republic
Canada
Austria
1.2
1.2
1.3
1.3
1.4
1.4
1.4
1.5
1.6
1.6
1.7
1.8
Finland
Belgium
Slovenia
New Zealand
Estonia
Spain
United States
Poland
2.1
2.1
Hungary
2.3
3.2
0
0.5
1.0
1.5
Denmark 2
0
2.0
2.5
3.0
3.5
Annual consultations per capita
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525875
20
40
60
80
100
%
1. Visits in past two years.
2. Visits in past three months.
Source: OECD estimates (2011).
1 2 http://dx.doi.org/10.1787/888932525894
6.6.3 Proportion of adults visiting a dentist in the past
year, by income group, United States, 1997-2009
Poor
Japan
Netherlands
France
Germany
Belgium
Slovenia
Luxembourg
Austria
Canada
Czech Republic
Estonia
Slovak Republic
Finland
OECD
Sweden
New Zealand
Australia
Poland
Denmark
Norway
Hungary
Iceland
Korea
Switzerland
Spain
Near-poor
Middle and high income
%
75
70
65
60
55
50
45
09
08
23.6
25.0
25.3
25.9
28.1
28.6
35.0
39.6
44.1
49.7
51.2
51.3
53.9
54.2
59.5
60.4
60.9
63.9
70.5
75.4
76.6
80.6
83.5
91.0
97.2
0
20
20
20
06
05
04
03
07
20
20
20
20
20
01
02
20
20
9
8
00
20
19
9
19
9
19
9
7
40
Source: NCHS (2011).
1 2 http://dx.doi.org/10.1787/888932525913
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6.6.4 Out-of-pocket dental expenditure,
2009 (or nearest year)
40
60
80
100
% of total dental expenditure
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932525932
141
6. ACCESS TO CARE
6.7. Inequalities in cancer screening
Cancer is the second most common cause of death in
OECD countries, responsible for 28% of all deaths in 2009.
Among women, breast cancer is the most common form,
accounting for 30% of new cases each year and 15% of
cancer deaths in 2009. Cervical cancer adds an additional
3% of new cases, and 2% of female cancer deaths (see
Indicator 1.4, “Mortality from cancer”).
The early detection of breast and cervical cancers through
screening programmes has contributed to increased
survival rates, and many countries have opted to make
screening widely available. In most countries, more than
half of women in the target age groups have had a recent
mammogram, and a pelvic exam or Pap smear (see
Indicators 5.8 and 5.9).
Screening rates vary widely among women in different
socio-economic groups in OECD countries (Figures 6.7.1
and 6.7.2). Even in those countries where the practice is
common, women in lowest income groups are generally
less likely to undergo screening. Income-related inequalities in cervical cancer screening are significant in 15 of the
16 countries studied. However, pro-rich inequalities in
breast cancer screening are significant in fewer countries
(Belgium, Canada, Estonia, France, New Zealand, Poland
and the United States).
In the United States, low-income women, women who are
uninsured or receiving Medicaid (health insurance coverage for the poor, disabled or impoverished elderly) or
women with lower educational levels report much lower
use of mammography and Pap smears (NCHS, 2011). There
is additional evidence in European countries for significant
social inequalities in utilisation of early detection and
prevention health care services (von Wagner et al., 2011).
In particular, women with higher level of assets are more
likely to have mammograms (Sirven and Or, 2010).
In Mexico, cervical cancer detection programmes have
been in place for some time, but problems with access and
coverage remain, especially among disadvantaged groups,
so that almost half of women aged 50 years and over have
not had a Pap test in the last two years (Couture et al., 2008).
In most OECD countries, however, income should not be a
barrier to accessing screening mammography or Pap
smears, since the services are provided free of charge, or at
the cost of a doctor consultation.
Participation rates also vary by geographic regions
(Figure 6.7.3). Some areas, such as the Northern Territory
(Australia), and London (the United Kingdom), exhibit
significantly lower rates than do other regions within the
country. The reasons for this are varied. In geographically
isolated regions such as the Northern Territory, travelling
142
distance, the availability of screening services and access
barriers for Indigenous women play a part. In inner urban
areas of London, low levels of awareness of screening
programmes, symptoms and risks are a concern among
women who are poor, or from minority ethnic groups.
A number of socio-economic characteristics – such as
income, ethnicity, younger age, higher level of education,
employment status, residential area, marital status, having
health insurance, good health status, having a usual source
of care and use of other preventative services – are all
important predictors of participation in screening.
Since a wide range of screening practices and different
access barriers exist across OECD countries, no single
strategy will meet all needs in promoting greater and equal
coverage (Gakidou et al., 2008). In countries with sufficient
health system capacity, increased screening can be encouraged by ensuring services are free, and are available where
needed. Policies and interventions may need to be better
targeted in order to overcome inequalities. As a complementary tool, the promise of new cancer preventing
vaccines also has important implications for resource-poor
settings where maintaining screening programmes is
challenging.
Definition and comparability
Breast and cervical screening participation rates
measure the proportion of women of a given age who
have variously received a recent mammogram, breast
exam, pap smear or pelvic exam. Information is
generally derived from health surveys, or from
screening programme administrative data.
Rates by income groups were derived from health
surveys. For cervical, women aged 20-69 years were
asked whether they had been screened in the three
years prior to the survey, and for breast, women
aged 50-69 years in the past two years. The exception
was Denmark (for breast only), where screening was
reported for the past 12 months. Screening estimates
based on self-reported health surveys should be used
cautiously, since respondents tend to overestimate
desirable behaviours.
The data for geographic regions include women in
target age groups who had participated in national
screening programmes. Target age groups and screening periodicity may differ across countries.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.7. Inequalities in cancer screening
6.7.1 Cervical cancer screening in past three years,
by income level, 2009 (or nearest year)
Low income
Average
6.7.2 Breast cancer screening in past two years,
by income level, 2009 (or nearest year)
High income
Low income
United States
Spain
Austria
Austria
Spain
United States
Slovenia
France
Canada
New Zealand
New Zealand
Canada
France
Belgium
Poland
Czech Republic
Denmark
Hungary
Belgium
Poland
Czech Republic
Slovak Republic
Hungary
United Kingdom
Slovak Republic
Slovenia
United Kingdom
Estonia
Estonia
Denmark1
0
20
40
0
60
80
100
% of women aged 20-69
Note: The data source for some countries may be different to that used
for reporting breast and cervical cancer screening in Chapter 5.
Average
20
40
High income
60
80
100
% of women aged 50-69
Note: The data source for some countries may be different to that used
for reporting breast and cervical cancer screening in Chapter 5.
1. Visits in the past 12 months.
Source: OECD estimates (2011).
1 2 http://dx.doi.org/10.1787/888932525951
Source: OECD estimates (2011).
1 2 http://dx.doi.org/10.1787/888932525970
6.7.3 Participation in breast cancer screening programmes, regions in selected OECD countries
Northern Territory
Australia (2007-08)
Limburg
Belgium (2006-07)
Canada (2005)
France (2009)
Calabria
Italy (2008)
Trentino
BreastScreen
South region
New Zealand (2009)
Switzerland (2007)
Valais
Berne
United Kingdom (2008-09)
London
United States (2008)
0
20
40
60
80
100
% of women in target age group
Source: AIHW (2010c); FDCS (2011); IMA-AIM (2010); INVS (2011); NHSBSP (2010); ONS (2010); Page and Taylor (2010); PHAC (2008); CDC (2010b).
1 2 http://dx.doi.org/10.1787/888932525989
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
143
6. ACCESS TO CARE
6.8. Waiting times
Patients may need to wait for health services for a number
of reasons, including a lack of medical equipment or no
available hospital beds, short-staffing, or inefficiencies in
the organisation of services. Excessive waiting times to see
a doctor or for non-emergency surgery can sometimes lead
to adverse health effects such as stress, anxiety or pain
(Sanmartin, 2003). Dissatisfaction and strained patientdoctor relationships also damage public perceptions of the
health system.
Since most countries use their own definitions, collecting
comparable data on waiting times is difficult. Multi-country
patient surveys are useful, although these rely on selfreport, have limited sample size and may not be consistent
with administrative data.
These surveys find that waiting times vary substantially.
While in some countries they are a major health policy
concern, others report no significant waiting times at all.
Waiting times to see a primary care physician or nurse
in 2010 were low in most of the 11 countries covered by the
Commonwealth Fund Survey, and only in Canada, Norway
and Sweden did a significant number of patients have to
wait for six days or more (Davis et al., 2010).
Waiting times for specialist consultations were also higher
in Canada, Norway and Sweden, with 50% or more of
survey respondents waiting at least 4 weeks for an appointment (Figure 6.8.1). In Germany, Switzerland and the
United States, more timely access was provided. Waiting
times for elective surgeries such as cataract removal or hip
replacement also show substantial differences. In 2010, a
considerable proportion of patients in Canada, Sweden,
Norway, the United Kingdom and Australia reported waiting four months or more for elective surgery (Figure 6.8.2)
(Davis et al., 2004, 2006, 2010; Schoen et al., 2010).
Waiting times can vary within countries. Though very
moderate waiting times for a doctor consultation are
reported for Germany, patients in the eastern part of the
country report waiting longer (KBV, 2010). There is evidence
from several countries, including England, Germany and
Austria, that persons in higher socio-economic groups or
with private health insurance have shorter waiting times
(Laudicella et al., 2010; KBV, 2010; Statistik Austria, 2007). In
Canada, women have longer waiting times for specialist
consultations than men, possibly because men consult a
specialist at a more advanced or acute stage of disease,
and have a more urgent need for treatment (Carrière and
Sanmartin, 2010).
144
Initiatives to cut waiting times have been launched in a
number of OECD countries. In England, the government set a
target in 2000 of a maximum 18 weeks from referral to treatment for elective care, and by 2008, 94% of admitted patients
and 98% of non-admitted patients were treated within that
time (Department of Health, 2009). These administrative data
show more positive results than those reported in surveys
(Figure 6.8.2). In New Zealand, waiting times for elective
surgery were also addressed as a major health target and have
decreased since 2005, while the access and level of services
have improved substantially (MoH, 2010).
In Canada, waiting times for a set of priority areas, including
hip and knee replacement and cataract surgery, were
targeted in 2004 as part of the 10-Year Plan to Strengthen
Health Care. The most recent assessment for 2010-11
reported eight out of ten patients receiving priority procedures within benchmarks. For hip replacement, seven out of
ten provinces treated 75% of patients within 26 weeks, while
the benchmark for cataract surgery (75% of patients treated
within 16 weeks) was met in six provinces (CIHI, 2011).
Optimum waiting times are not necessarily zero. It can be
cost-effective to maintain short queues of elective patients
because the adverse health consequences of short delays are
minimal, and there are savings in hospital capacity from
allowing queues to form (Siciliani and Hurst, 2003). They
may also deter patients who stand to gain only small health
benefits from demanding treatment (Laudicella et al., 2010).
Definition and comparability
In the Commonwealth Fund Surveys, waiting times
for doctor or nurse consultations refer to the days or
weeks the patient had to wait to get an appointment
when sick, or in need of medical attention. Waiting
times for specialist and elective surgery was the time
between the patient being advised that they needed
care and the appointment. Only those respondents
who had specialist consultations or elective surgery
in the last year or two were asked to specify waiting
times.
Since there are no universally accepted definitions of
waiting times, data derived from different sources
may not be fully comparable.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
6. ACCESS TO CARE
6.8. Waiting times
6.8.1 Waiting time of four weeks or more for a specialist appointment
2005
%
80
60
2008
2010
60 59
57
60
55
55
58
55
50
45
47
46
46
40
40
39
32
31 30
28
26
23
22
20
20
18
17
Sw
Ge
it z
er
rm
la
an
y
nd
es
at
St
Un
i te
Un
d
i te
Ki
th
Ne
Ne
d
er
ng
la
do
nd
m
s
d
Ze
w
Au
Fr
st
al
ra
an
li a
ce
an
rw
No
Ca
Sw
na
ed
da
en
ay
0
Source: Commonwealth Fund International Health Policy Surveys.
1 2 http://dx.doi.org/10.1787/888932526008
6.8.2 Waiting time of four months or more for elective surgery
2001-02
%
50
2005
2007
2010
41
40
38
33
30
30
27
27
26
25
23
22
21
21
20
19
20
18 18
13
10
8
7
8 8
7
7
7
5
6
5
5
0
y
an
rm
Ge
nd
er
th
Ne
d
i te
Un
la
at
St
la
er
it z
Sw
s
es
nd
ce
an
al
Ze
w
Ne
Fr
an
d
li a
ra
st
do
ng
Ki
d
i te
Un
Au
m
ay
rw
No
en
ed
Sw
Ca
na
da
0
Source: Commonwealth Fund International Health Policy Surveys.
1 2 http://dx.doi.org/10.1787/888932526027
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
145
7. HEALTH EXPENDITURE AND FINANCING
7.1. Health expenditure per capita
7.2. Health expenditure in relation to GDP
7.3. Health expenditure by function
7.4. Pharmaceutical expenditure
7.5. Financing of health care
7.6. Trade in health services (medical tourism)
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
147
7. HEALTH EXPENDITURE AND FINANCING
7.1. Health expenditure per capita
OECD countries vary enormously in how much they spend
on health and the rate at which health spending grows.
This reflects a wide array of market and social factors, as
well as countries’ diverse financing and organisational
structures of their health systems.
The United States continues to outspend all other OECD
countries by a wide margin. In 2009, spending on health
goods and services per person in the United States rose to
USD 7 960 (Figure 7.1.1) – two and a half times the average
of all OECD countries. The next highest spending countries,
Norway and Switzerland, spend only around two-thirds of
the per capita level of the United States, but are still more
than 50% above the OECD average. Most of the northern
and western European countries, together with Canada
and Australia, spend between USD PPP 3 200 and 4 400,
between 100% and 130% of the OECD average. Those
countries spending below the OECD average include
Mexico and Turkey, but also the southern and eastern
European members of the OECD together with Korea. Japan
also spends less on health than the average in OECD
countries, despite its above-average per capita income. By
comparison the fast growing economies, China and India,
spend less than 10% and 5% of the OECD average on health.
Figure 7.1.1 also shows the breakdown of per capita spending on health into public and private components (see also
Indicator 7.5 “Financing of health care”). In general, the
ranking according to per capita public expenditure remains
comparable to that of total spending. Even if the private
sector in the United States continues to play the dominant
role in financing, public spending on health per capita is still
greater than that in most other OECD countries (with the
exception of Norway, Luxembourg and the Netherlands),
because overall spending on health is much higher than in
other countries. In Switzerland also, a large proportion of
health care financing comes from private sources, and its
public spending on health is lower than in certain other
countries, although overall spending is higher. The opposite
is true in Denmark where most health care is mostly
financed through public sources.
Per capita health spending over 2000-09 is estimated to
have grown, in real terms, by 4% annually on average across
the OECD (Figure 7.1.2 and Table A.6). In many countries,
the growth rate reached a peak prior to 2004 and slowed in
more recent years.
In general, the countries that have experienced the highest
growth in health expenditures per capita over this period
are those that had relatively low levels at the beginning of
the period. Health expenditure growth in the Slovak
Republic and Korea, for example, has been more than twice
the OECD average since 2000, resulting in a degree of
convergence between OECD countries over time.
148
In countries such as Italy, Switzerland and Germany, health
spending per capita has increased at a much slower rate
over the period – at an annual average of 2% or less. This
reflects, in part, a period of relatively low economic growth
over the period as a whole and the effect of deliberate costcontainment policies.
Figure 7.1.3 shows the familiar association between GDP
per capita and health expenditure per capita across OECD
countries. While there is an overall tendency for countries
with higher GDP to spend a greater amount on health,
there is wide variation since GDP is not the sole factor
influencing health expenditure levels. The association is
stronger among countries with low GDP per capita than
among OECD countries with a higher GDP per capita. Even
for countries with similar levels of GDP per capita there are
substantial differences in health expenditure at a given
level of GDP. For example, despite Germany and Finland
having similar GDP per capita, their health spending per
capita differs considerably with Germany spending around
25% more than Finland. The United States spends much
more on health than what might be expected based only on
its GDP level.
Definition and comparability
Total expenditure on health measures the final
consumption of health goods and services (i.e. current
health expenditure) plus capital investment in health
care infrastructure. This includes spending by both
public and private sources on medical services and
goods, public health and prevention programmes and
administration.
Differing estimation methodologies for long-term care
spending, in particular the allocation of spending
between health and social care, continue to limit the
overall comparability of total health spending. See
Indicators 7.3 “Health expenditure by function” and 8.8
“Long-term care expenditure” for further details.
Countries’ health expenditures are converted to a
common currency (US dollar) and adjusted to take
account of the different purchasing power of the
national currencies, in order to compare spending
levels. Economy-wide (GDP) PPPs are used as the most
available and reliable conversion rates.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7. HEALTH EXPENDITURE AND FINANCING
7.1. Health expenditure per capita
7.1.1 Total health expenditure per capita, public and private, 2009 (or nearest year)
Public expenditure on health
Private expenditure on health
132
99
862
308
918
902
1 036
943
1 393
1 186
1 511
2 000
1 394
2 084
1 879
2 165
2 108
2 579
2 508
2 878
2 724
3 067
2 983
3 226
3 137
3 233
3 487
3 445
3 722
3 538
3 946
3 781
4 218
4 000
3 978
4 348
42 89
4 808
4 363
5 144
4 914
6 000
5 352
7 960
USD PPP
8 000
Un
i te
d
St
at
e
N
S w or s
w
i
t
Ne ze ay
th r l a
Lu er l nd
xe a n
m ds 1
bo
u
Ca rg 2
n
De ad
nm a
a
Au r k
Ge s tr i
rm a
a
Fr ny
a
n
Be c
lg e
iu
Ir e m 3
l
S w and
ed
Un
i t e Ic en
d ela
Ki n
ng d
Au dom
st
ra
li
OE a
Fi CD
nl
an
d
It a
Ne S ly
w pa
Z e in
al
an
Ja d
pa
Gr n
e
Sl e c e
ov
Po eni a
r tu
Cz
ec I gal
Sl h R sr a
ov e e
a k pu l
Re bli
pu c
bl
Ko i c
Hu r e a
ng
a
Po r y
la
Ru
E s nd
to
ss
ni
ia
a
n
F e Ch
d e il e
ra
tio
Br n
a
M z il
ex
i
So Tu co
ut rk
h ey
Af
ric
Ch a
in
a
In In d
do i a
ne
si
a
0
1. In the Netherlands, it is not possible to clearly distinguish the public and private share related to investments.
2. Health expenditure is for the insured population rather than the resident population.
3. Total expenditure excluding investments.
Source: OECD Health Data 2011; WHO Global Health Expenditure Database.
1 2 http://dx.doi.org/10.1787/888932526046
7.1.2 Annual average growth rate in health expenditure
per capita in real terms, 2000-09 (or nearest year)
Luxembourg
Portugal
Israel
Italy
Iceland
Switzerland
Germany
France
Austria
Norway
Japan
Hungary
Australia
Mexico
United States
Denmark
Sweden
Canada
Slovenia
OECD
Spain
Finland
Belgium
Netherlands
United Kingdom
New Zealand
Chile
Czech Republic
Ireland
Turkey
Greece
Poland
Estonia
Korea
Slovak Republic
7.1.3 Total health expenditure per capita
and GDP per capita, 2009 (or nearest year)
Health spending per capita (USD PPP)
8 000
0.7
1.5
1.5
1.6
1.6
2.0
2.0
2.2
2.2
2.4
2.4
2.8
2.8
3.1
3.3
3.3
3.4
3.7
3.9
4.0
4.0
4.0
4.0
4.4
4.8
4.8
5.2
5.7
6.1
6.3
7 000
6 000
NOR
CHE
NLD
5 000
3 000
KOR
2 000
POL
CHL
BRA
IND
10.9
8
12
Annual average growth rate (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526065
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
HUN
EST
RUS
TUR
ZAF MEX
1 000
8.6
4
LUX
DNK CAN
AUT
DEU
FRA
BEL
IRL
SWE
ISL
GBR
AUS
ITA FIN
ESP
NZL
JPN
GRC
SVN
PRT
CZE
ISR
SVK
4 000
6.9
7.3
7.5
0
USA
0
0
CHN
IDN
15 000
30 000
45 000
60 000
75 000 90 000
GDP per capita (USD PPP)
Source: OECD Health Data 2011; WHO Global Health Expenditure Database.
1 2 http://dx.doi.org/10.1787/888932526084
149
7. HEALTH EXPENDITURE AND FINANCING
7.2. Health expenditure in relation to GDP
Trends in the health spending to GDP ratio are the result of
the combined effect of trends in both GDP and health
expenditure. Apart from Luxembourg, health spending has
grown more quickly than GDP since 2000. This has resulted
in a higher share of GDP allocated to health on average
across OECD countries.
In 2009, OECD countries devoted 9.6% of their GDP to health
spending (Figure 7.2.1 and Table A.8), a sharp increase from
8.8% in 2008, following the recession that started in many
countries in 2008 and became widespread in 2009. The rise
in the health spending share of GDP was particularly
marked in countries hard hit by the global recession. In
Ireland, the percentage of GDP devoted to health increased
from 7.7% in 2007 to 9.5% in 2009. In the United Kingdom, it
rose from 8.4% in 2007 to 9.8% in 2009.
In 2009, the United States spent 17.4% of GDP on health,
5 percentage points more than in the next two countries,
the Netherlands and France (which allocated 12.0% and
11.8% of their GDP on health). Of the OECD countries,
Mexico and Turkey spent less than 6.5% of their GDP on
health. The fast-growing economies of China and India
spent 4.6% and 4.2% respectively in 2009, while South
Africa and Brazil allocated 8.5% and 9.0% of GDP to health.
The share of public expenditure on health to GDP varies
from a high of 9.8% of GDP in Denmark to lows of 4.0% and
3.1% of GDP in Korea and Mexico, respectively. In these two
countries, health spending is more evenly split between
public and private financing compared to other OECD
countries.
For a more comprehensive assessment of health spending,
the health spending to GDP ratio should be considered
together with per capita health spending (see Indicator 7.1
“Health expenditure per capita”). Countries having a relatively high health spending to GDP ratio might have
relatively low health expenditure per capita, while the
converse also holds. For example, Portugal and Sweden both
spent a similar proportion of their GDP on health at around
10% of GDP; however, per capita spending (adjusted to
USD PPP) was close to 50% higher in Sweden (Figure 7.1.1).
Since 2000, after a period of early growth in the health
spending to GDP ratio, there was a period of relative stability until 2009 (Figure 7.2.2). The subsequent reduction in
GDP, due to the economic downturn, has led to a rise in the
150
health spending to GDP ratios. The experience from
previous recessions shows that, in many countries, the
health spending share of GDP has tended to go up strongly
during periods of economic downturns, and then to stabilise or go down only slightly during periods of economic
recovery. Looking back at the experience following the
recession in the early 1990s, some countries such as
Canada and Finland did substantially reduce public
expenditure on health to cut down their budgetary deficits,
leading to a noticeable reduction in the health spending
share of GDP over a few years. But these reductions in
public spending on health proved to be short-lived and,
after a few years of cost-containment, growing demand for
and supply of health services led to a revival of health
expenditure growth exceeding GDP growth again (Scherer
and Devaux, 2010).
Health spending per capita since 2000 has increased more
than two times faster than economic growth on average
across OECD countries (4.0% versus 1.6%), resulting in an
increasing share of the economy devoted to health in most
countries (Figure 7.2.3).
Definition and comparability
See Indicator 7.1 “Health expenditure per capita” for
the definition of total health expenditure.
Gross Domestic Product (GDP) = final consumption +
gross capital formation + net exports. Final consumption of households includes goods and services used
by households or the community to satisfy their
individual needs. It includes final consumption
expenditure of households, general government and
non-profit institutions serving households.
In countries, such as Ireland and Luxembourg, where
a significant proportion of GDP refers to profits
exported and not available for national consumption,
GNI may be a more meaningful measure than GDP.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7. HEALTH EXPENDITURE AND FINANCING
7.2. Health expenditure in relation to GDP
7.2.1 Total health expenditure as a share of GDP, 2009 (or nearest year)
Public
Private
18
17.4
% of GDP
20
4.6
6
4.2
6.1
5.4
6.9
6.4
7.4
7.0
7.8
7.4
8.2
8
7.9
8.5
8.4
8.7
8.5
9.1
9.0
9.2
9.5
9.3
9.5
9.5
9.6
9.6
9.6
9.7
10.0
10
9.8
10.3
10.1
11.0
10.9
11.4
11.4
11.5
11.8
12
11.6
14
12.0
16
2.4
4
2
Un
i te
Ne d S
th t at
er es
la
nd
Fr s 1
a
Ge nc
rm e
De an
nm y
ar
S w C an k
i t z ad
er a
la
Au nd
s
B t
Ne elg r ia
w ium
Ze
2
a
Po land
r tu
Un
i te S w gal
d ed
Ki e
ng n
d
Ic om
el
a
Gr n d
ee
No ce
rw
a
OE y
C
Ir e D
la
nd
It a
l
S y
Sl p a in
ov
Sl
ov F eni a
a k inl
Re and
pu
bl
i
B c
Au r a z
s t il
ra
S o J li a
ut apa
h
Af n
ric
Cz
ec
a
h Ch
Re il
pu e
bl
Lu
ic
xe Isr
m ae
bo l
H u ur g 3
ng
a
Po r y
la
E s nd
to
n
Ko i a
r
Ru
M ea
ex
ss
i
ia
n Tu co
Fe rk
de ey
ra
tio
Ch n
in
a
In In d
do i a
ne
si
a
0
1. In the Netherlands, it is not possible to clearly distinguish the public and private share related to investments.
2. Total expenditure excluding investments.
3. Health expenditure is for the insured population rather than the resident population.
Source: OECD Health Data 2011; WHO Global Health Expenditure Database.
1 2 http://dx.doi.org/10.1787/888932526103
7.2.2 Total health expenditure as a share of GDP,
selected OECD countries, 2000-09
Canada
Korea
Switzerland
United Kingdom
United States
OECD
7.2.3 Annual average growth in real per capita
expenditure on health and GDP, 2000-09 (or nearest year)
Annual average growth rate in real health expenditure per capita (%)
11
SVK
% of GDP
18
9
KOR
16
GRC
14
CZE
GBR
5
8
3
MEX
FRA
6
DEU
ITA
09
20
08
20
07
20
20
20
20
20
20
20
06
-1
05
0
04
0
03
2
02
1
01
4
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526122
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
CHL
NZL
NLD
ESP FIN
BEL
OECD
CAN
DNK
SWE
USA
10
00
TUR
IRL
12
20
EST
POL
7
NOR
JPN
AUT
CHE
PRT
ISR
AUS
SVN
HUN
ISL
LUX
-1
0
1
3
5
Annual average growth rate in real GDP per capita (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526141
151
7. HEALTH EXPENDITURE AND FINANCING
7.3. Health expenditure by function
Spending on the various types of health care services and
goods is influenced by a wide range of factors: health
system constraints, such as access to hospital beds, medical staff and new technology, the financial and institutional
arrangements for health care delivery, as well as national
clinical guidelines and the disease burden within a country.
In 2009, curative and rehabilitative care provided either as
inpatient (including day care) or outpatient care accounted
for more than 60% of current health spending on average
across OECD countries (Figure 7.3.1). The ratio of inpatient to
outpatient spending can vary according to the different
organisational arrangements of health care providers and
clinical practice variation between countries. Austria and
France, for example, report a relatively high proportion of
expenditure on inpatient care (amounting to more than a
third of health spending) which is mirrored by them having
the highest levels of hospital activity (see Indicator 4.4
“Hospital discharges”). Conversely, countries such as
Portugal and Spain, with relatively low levels of hospital
activity, allocate around a quarter of health care resources to
inpatient care.
Large differences remain between countries in their
expenditure on long-term care. Norway, Denmark and the
Netherlands, with established and extensive formal
arrangements for elderly and disabled care, allocate around
a quarter of their total health spending to long-term care.
By contrast, in eastern and southern European countries,
where care tends to be provided in more informal or family
settings, expenditure on long-term care accounts for a
much smaller share of total health spending (see
Indicator 8.8 “Long-term care expenditure”).
The other major category of health expenditure is on
medical goods, mostly accounted for by pharmaceuticals
(see Indicator 7.4 “Pharmaceutical expenditure”). At 19%,
on average, the share of health spending on medical goods
can be as low as 11-12% in New Zealand, Denmark and
Norway, but accounts for more than a third of all health
spending in Hungary and the Slovak Republic.
The growth in the various components of care reflects in
part the relative stage of development of health systems.
With inpatient care highly labour intensive and, therefore,
expensive, certain high income countries with developed
health systems have sought to reduce the share of spending in hospitals by shifting to more day surgery, outpatient
or home-based care. However, this shift can also reflect
regulatory issues. Public spending in the United States is
largely Medicare and Medicaid related for which prices are
tightly controlled. Thus, it can be in the interest of hospitals to shift patients to ambulatory care where there are no
152
controls of the price of interventions (OECD, 2010b). Estimates of spending on ambulatory surgery performed by
independent physicians suggested that this has been the
fastest growing area of health care between 2003 and 2006
in the United States (McKinsey Global Institute, 2008). On
the other hand, lower income OECD countries seeking to
invest in and expand their health systems have generally
seen the growth in hospital inpatient care outpace other
areas of spending such that it has been the main contributor to overall health expenditure growth (Figure 7.3.2).
Figure 7.3.3 shows the share of health expenditure allocated to health care administration. On average, OECD
countries allocated 3% of their spending to the management and regulation of the health system. This also
includes the administration and operation of health insurance funds which goes some way to explaining the wide
variations. Generally those countries operating single payer
tax-based health financing systems (e.g. Denmark and
Sweden) show a lower share of health spending allocated
to administration compared to countries with multi-payer
social insurance models, such as the United States, France
and Germany.
Definition and comparability
The functional approach of the System of Health
Accounts defines the boundaries of the health system.
Total health expenditure consists of current health
spending and investment. Current health expenditure comprises personal health care (curative care,
rehabilitative care, long-term care, ancillary services
and medical goods) and collective services (public
health services and health administration). Curative,
rehabilitative and long-term care can also be classified by mode of production (inpatient, day care,
outpatient and home care).
Factors limiting the comparability across countries
include estimations of long-term care expenditure.
Also, in some cases, expenditure in hospitals is used
as a proxy for inpatient care services, although
hospital expenditure may include spending on
outpatient, ancillary, and in some cases drug
dispensing services (Orosz and Morgan, 2004).
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7. HEALTH EXPENDITURE AND FINANCING
7.3. Health expenditure by function
7.3.1 Current health expenditure by function of health care, 2009
Countries are ranked by curative-rehabilitative care as a share of current expenditure on health
Inpatient care 1
%
100
2
90
16
80
4
6
16
6
14
1
6
8
70
4
11
26
Outpatient care 2
4
8
4
5
Long-term care
26
23
22
27
20
9
4
5
5
7
18
19
6
13
21
14
9
4
8
18
12
12
Medical goods
7
3
12
18
19
18
14
3
12
8
11
14
24
48
42
34
44
30
34
40
20
21
7
8
8
17
25
12
12
7
12
21
38
37
27
9
9
15
23
20
10
15
4
0
27
34
37
51
3
12
9
9
25
60
50
Collective services
33
38
34
34
33
29
27
31
23
26
29
19
25
34
33
25
33
30
20
10
28
28
32
25
35
32
36
30
27
19
29
26
28
28
28
32
32
29
36
32
29
35
30
24
21
26
20
N
HU
N3
D
NL
SV
CA
K
L
R
BE
NO
KO
R
U
A
DE
N
FR
L
E
L
K
SV
DN
IS
CH
N
NZ
FI
CD
T
OE
P
AU
T
ES
LU
ES
X
L
E
PO
N
CZ
JP
T
A3
US
E
PR
SW
IS
R
0
1. Refers to curative-rehabilitative care in inpatient and day-care settings.
2. Includes home-care and ancillary services.
3. Inpatient services provided by independent billing physicians are included in outpatient care for the United States and Canada.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526160
7.3.2 Growth in inpatient and outpatient care expenditure
per capita, in real terms, 2000-09 (or nearest year)
Inpatient care 1
Outpatient care 2
Poland
9.1
5.4
8.1
7.6
Czech Republic
6.4
Korea
Netherlands
6.3
1.5
4.9
Estonia
Slovenia
7.0
4.5
2.6
Denmark
4.1
3.3
Australia
7.9
4.0
2.1
Finland
3.4
Spain
3.3
1.4
5.0
3.2
3.4
OECD
2.7
Canada
4.1
2.7
3.0
Norway
2.4
Sweden
Austria
2.8
2.3
1.5
2.1
2.3
2.1
Hungary
United States
1.8
1.6
1.6
France
Japan
Germany
1.4
Switzerland
1.4
0.4
Luxembourg
-2
1.9
2.5
2.9
-1.9
Iceland
2.9
1.2
-0.2
Portugal
3.8
2.8
0
2
4
6
8
10
Annual average growth rate (%)
1. Including day care.
2. Including home-care and ancillary services.
7.3.3 Expenditure on health care administration
and insurance, 2009 (or nearest year)
United States
France
Germany
Switzerland
Belgium
Slovenia
Netherlands
Canada
Austria
Australia
Korea
Czech Republic
Slovak Republic
Spain
OECD
Estonia
Finland
Iceland
Japan
Portugal
Luxembourg
Sweden
Poland
Hungary
Denmark
Israel
Norway
Italy
7.0
7.0
5.4
4.9
4.9
4.3
4.0
3.7
3.6
3.6
3.6
3.4
3.4
3.1
3.0
2.4
2.1
1.9
1.9
1.7
1.7
1.4
1.4
1.3
1.2
1.2
0.8
0.5
0
2
4
6
8
% of current expenditure on health
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526198
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526179
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
153
7. HEALTH EXPENDITURE AND FINANCING
7.4. Pharmaceutical expenditure
Pharmaceuticals account for almost a fifth of all health
spending on average across OECD countries. The increased
consumption of pharmaceuticals due to the diffusion of
new drugs and the ageing of populations (see Indicator 4.11
“Pharmaceutical consumption”) has been a major factor
contributing to increased pharmaceutical expenditure and
thus overall heath expenditure (OECD, 2008c). However, the
relationship between pharmaceutical spending and total
health spending is a complex one, in that increased expenditure on pharmaceuticals to tackle diseases may reduce
the need for costly hospitalisations and interventions now
or in the future.
The total pharmaceutical bill across OECD countries in 2009 is
estimated to have reached more than USD 700 billion,
accounting for around 19% of current health spending.
Since 2000, average spending on pharmaceuticals has risen
by almost 50% in real terms. However, considerable variation
in pharmaceutical spending can be observed, reflecting
differences in consumption patterns and pharmaceuticals
pricing policies (Figure 7.4.1). In 2009, the United States
remained the highest per capita spender on pharmaceuticals,
with expenditure of USD 947, nearly twice the OECD average
of USD 487. The big pharmaceutical spenders after the United
States were Canada and Greece. At the other end of the scale,
Mexico spent just under USD PPP 250 per capita – little more
than a quarter of the United States. New Zealand and
Denmark also feature among the lowest per capita
spenders at less than USD 300 per capita. Self-medication or
over-the-counter pharmaceutical products typically account
for around 15% of the total spending.
In relation to the overall economy, pharmaceutical spending accounts for 1.5% of GDP on average in OECD countries
(Figure 7.4.1). However, the dispersion around this average
is high: pharmaceutical spending accounts for less than
1% of GDP in Norway, Denmark and New Zealand, while it
reaches close to 2.5% of GDP in Greece, Hungary and the
Slovak Republic.
Expenditures for pharmaceuticals are predominantly
financed through third-party payers in most OECD
countries – either through the public health insurance,
which accounts for around 60% of the total on average, or
through private insurance coverage, leaving a third of the
total on average to the charge of households, much higher
than for physician and hospital services. This is due to
higher co-payments for pharmaceuticals under public
insurance schemes, or a lack of coverage for nonprescribed drugs and for prescribed drugs in some countries. While in some countries, such as the Netherlands,
154
Germany and France, the burden of pharmaceutical
spending falling onto the households is less than 20%, at
the other end of the spectrum, households in Estonia and
Poland pick up around 60% of the total pharmaceutical bill
(Figure 7.4.2).
In the past, pharmaceutical spending has tended to rise at
a faster pace than total health spending in OECD countries
(see Figures 7.4.3 and 7.1.2). This trend has now reversed to
some extent: between 2000 and 2009, real pharmaceutical
expenditure has grown by around 3.5% per year on average
in OECD countries, while total health spending has
increased by 4.0%. In a few countries (Luxembourg, Norway
and Italy), the growth in pharmaceutical spending has
actually been negative over this period. [Note that figures
for Luxembourg refer only to prescribed medicines.]
In Ireland and Greece, where pharmaceutical spending was
growing at a very rapid pace, governments have recently
enforced emergency measures – mainly big price reductions – and announced the implementation of more structural policy reforms. In other countries, such as France,
Germany or the United Kingdom, price reductions or
rebates on pharmaceuticals have often been used as
adjustment variables to contain health spending growth
(France), tackle health insurance funds deficits (Germany)
or cap pharmaceutical companies’ profits on NHS sales
(the United Kingdom) (OECD, 2010b).
Definition and comparability
Pharmaceutical expenditure covers spending on
prescription medicines and self-medication, often
referred to as over-the-counter products. For some
countries, other medical non-durables such as
syringes, bandages, etc. may be included in the total.
It also includes pharmacists’ remuneration when the
latter is separate from the price of medicines.
Pharmaceuticals consumed in hospitals are excluded
(on average they account for around 15% of total
pharmaceutical spending). Final expenditure on
pharmaceuticals includes wholesale and retail
margins and value-added tax.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7. HEALTH EXPENDITURE AND FINANCING
7.4. Pharmaceutical expenditure
7.4.1 Expenditure on pharmaceuticals per capita and as a share of GDP, 2009 (or nearest year)
Over-the-counter medicines
Prescribed medicines
Public
United States
Canada
Greece 1
Ireland1
Belgium 2
Germany
France
Italy1
Japan
Slovak Republic 2
Spain
Switzerland
Austria
Portugal1
Australia
Hungary
OECD
Netherlands
Iceland
Finland
Slovenia
Sweden
Korea
Norway1
Czech Republic
United Kingdom1
Luxembourg 2
Estonia
Israel 3
Poland
Denmark
New Zealand
Mexico 1
947
692
677
662
636
627
626
572
556
554
529
521
518
518
503
493
487
473
460
452
448
437
397
391
389
381
370
319
316
306
289
265
249
1 000
USD PPP
500
0
1. Cannot be separated and includes medical non-durables.
Private
2.1
1.8
2.4
1.7
1.8
1.7
1.9
1.7
1.6
2.4
1.6
1.2
1.3
2.1
1.3
2.4
1.5
1.2
1.3
1.3
1.6
1.2
1.5
0.7
1.5
1.0
0.6
1.6
1.1
1.6
0.8
0.9
1.7
0
1
2
3
% GDP
2. Prescribed medicines only. 3. Total medical goods.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526217
7.4.2 Out-of-pocket expenditure as a share of total
pharmaceutical expenditure, 2009 (or nearest year)
Poland
Estonia
Australia
Norway
Finland
Sweden
Portugal
Iceland
Belgium
Hungary
Korea
Denmark
OECD
Czech Republic
Slovak Republic
Austria
New Zealand
United States
Switzerland
Japan
Canada
Spain
Slovenia
France
Germany
Luxembourg
Netherlands
60.8
58.9
45.4
43.0
42.6
40.6
40.5
40.4
39.3
38.5
36.2
34.9
32.8
31.9
30.2
30.1
29.7
29.3
28.5
27.1
25.8
25.5
17.6
17.0
15.5
13.0
9.8
0
20
40
60
80
% of total pharmaceutical spending
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526236
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7.4.3 Growth in real per capita pharmaceutical
expenditure, 2000-09 (or nearest year)
Greece
Ireland
Korea
Estonia
Slovak Republic
Mexico
Canada
Hungary
United States
OECD
Czech Republic
Poland
Netherlands
Finland
Japan
Germany
Australia
Spain
Iceland
Belgium
Austria
United Kingdom
Israel
Portugal
Slovenia
France
Switzerland
Sweden
Denmark
Italy
Norway
Luxembourg
11.1
8.7
8.1
7.9
7.9
7.0
5.0
4.2
4.1
3.5
3.5
3.4
3.4
3.3
3.0
3.0
2.6
2.6
2.5
2.4
2.4
2.2
2.2
1.9
1.9
1.9
1.2
1.2
1.2
-0.5
-0.6
-0.8
-5
0
5
10
15
Annual average growth rate (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526255
155
7. HEALTH EXPENDITURE AND FINANCING
7.5. Financing of health care
All OECD countries use a mix of public and private sources
to pay for health care, but to varying degrees. Public
financing is confined to government revenues in countries
where central and/or local governments are primarily
responsible for financing health services directly (e.g. Spain
and Norway). It comprises both general government
revenues and social contributions in countries with social
insurance-based funding (e.g. France and Germany). Private
financing, on the other hand, covers households’ out-ofpocket payments (either direct or as co-payments), thirdparty payment arrangements effected through various
forms of private health insurance, health services such as
occupational health care directly provided by employers,
and other direct benefits provided by charities and the like.
Figure 7.5.1 shows the breakdown of how health care services
are paid for across OECD countries in 2009. The public sector
remains the main source of health financing in all OECD
countries, apart from Chile, Mexico and the United States. In
the Netherlands, the Nordic countries (except Finland), the
United Kingdom, the Czech Republic, Luxembourg, Japan and
New Zealand public financing of health care accounted for
more than 80% of all health expenditure. On average, the
public share of total health spending was 72% in 2009, more
or less unchanged over the last 20 years, although the range
has tended to narrow slightly. Many of those countries with a
relatively high public share in the early 1990s, such as the
Czech Republic and the Slovak Republic, have decreased their
share, while other countries which historically had a
relatively low level (e.g. Portugal, Turkey) have increased their
public share, reflecting health system reforms and the expansion of public coverage.
After public financing, the main financing source for health
care are households themselves through so-called out-ofpocket payments. These may be co-payments or costsharing arrangements with public or private schemes, say
for prescription pharmaceuticals, or simply direct payments
borne directly by a patient for services or goods. On average
across OECD countries, the share of health care expenditure
covered by households was around 19% in 2009, ranging
from lows of 6% and 7% in the Netherlands and France, to
more than 30% in Korea, Mexico and Chile. In some central
and eastern European countries, the practice of informal
payments means that the level of out-of-pocket spending is
probably underestimated.
156
Some countries have extended the coverage of their public
health systems in recent years and seen the burden on
households fall. In the case of Korea and Turkey, the share
of health spending borne by households has fallen by
around 10 percentage points since 2000 (Figure 7.5.2). On
the other hand, some eastern European countries with
traditionally high shares of public financing have seen
charges shifted towards households over the same period.
In general, a relationship can be seen between out-ofpocket spending as a share of total health spending and the
overall level of health spending itself (Figure 7.5.3). The
United States, France and the Netherlands, as some of the
highest spenders on of health care, also see households
financing a relatively small share of the health care costs
directly, with the majority of spending made through thirdparty arrangements – both public or private. Switzerland is
notable as having a significant share of its overall high
health spending being paid directly by households.
Definition and comparability
There are three elements of health care financing:
sources of funding (households, employers and the
state), financing schemes (e.g. compulsory or voluntary
insurance), and financing agents (organisations
managing the financing schemes). Here “financing” is
used more in the sense of financing schemes. Public
financing includes general government revenues
and social security funds. Private financing covers
households’ out-of-pocket payments, private health
insurance and other private funds (NGOs and private
corporations).
Out-of-pocket payments are expenditures borne
directly by the patient. They include cost-sharing
and, in certain countries, estimations of informal
payments to health care providers.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7. HEALTH EXPENDITURE AND FINANCING
7.5. Financing of health care
7.5.1 Expenditure on health by type of financing, 2009 (or nearest year)
Private sector
General government
% of total expenditure on health
100
2
90
5
6
14
1
10
15
3
0
12
14
17
17
2
5
16
13
1
13
20
80
9
22
13
7
Out-of-pocket
0
20
5
11
20
12
2
19
5
1
12
27
20
Private insurance
13
3
13
Other
5
4
9
7
8
5
19
28
22
24
15
18
26
27
40
30
70
29
32
33
48
34
60
50
40
12
85
84
84
84
84
84
82
81
81
40
80
78
78
78
77
75
75
75
75
74
73
73
72
72
71
70
68
66
65
30
60
60
58
58
48
48
47
20
10
Un
Ne
th
er
la
De nds 1
i t e nm
d
K i ar k 1
ng
do
No m
Lu
r
w
C z xem a y
ec bo
h
Re ur g
pu
bl
Ic i c
el
a
S w nd
ed
en
Ne Ja
w pa
Ze n
al
an
Fr d
an
ce
It a
Au l y
st
Ge r ia 2
rm
an
Es y
to
B e ni a
lg
iu
m
Ir e 1
la
n
Fi d
nl
an
d
Sp
Sl a in
ov
en
Tu ia
rk
e
Po y 2
la
nd
OE
CD
Ca
na
Hu d a
ng
Sl Au ar y
ov
ak s tr a
Re li a
pu
Po bli c
r tu
g
Gr a l
Sw ee
it z ce 2
er
la
nd
Is
ra
e
Ko l
re
Un M e a
i te x ic
d
St o
at
es
Ch
il e
0
1. Current expenditure.
2. No breakdown of private financing available for latest year.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526274
7.5.2 Change in out-of-pocket spending as a share
of current expenditure on health, 2000-09 (or nearest year)
Korea
Turkey
Poland
Italy
Spain
Ireland
Netherlands
Finland
United Kingdom
Hungary
United States
Iceland
Luxembourg
Switzerland
Mexico
Norway
New Zealand
Australia
Denmark
Chile
OECD
Canada
Austria
Japan
Sweden
Israel
Belgium
France
Estonia
Slovenia
Germany
Portugal
Czech Republic
Slovak Republic
7.5.3 Out-of-pocket and current expenditure on health,
2009 (or nearest year)
Out-of-pocket share in current expenditure on health (%)
50
MEX
-9.7
-9.7
-7.3
-5.3
-3.7
45
-3.5
-3.3
GRC
-3.2
40
-3.1
-3.0
CHL
-2.8
35
-2.8
KOR
-2.6
-2.5
ISR
30
-2.3
CHE
PRT
-2.2
SVK
-2.0
-1.8
HUN
25
POL
-1.7
-1.6
-1.5
20
-1.2
ESP
EST
AUS
SWE
TUR
-0.7
0.1
ISL
JPN
15
0.1
CZE
NZL
SVN
0.1
0.2
AUT
IRL
GBR
10
0.2
ITA
FIN
0.8
BEL
CAN
NOR
USA
DNK
DEU
LUX
FRA
1.1
NLD
1.5
5
1.8
4.7
16.1
-20
-10
0
10
20
Percentage points
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526293
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
0
0
2 000
4 000
6 000
8 000
Current health expenditure per capita (USD PPP)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526312
157
7. HEALTH EXPENDITURE AND FINANCING
7.6. Trade in health services (medical tourism)
Trade in health services and its most high-profile component, medical tourism, has attracted a great deal of media
attention in recent years. The impression often given is
that large numbers of patients are actively seeking health
care abroad or buying their pharmaceuticals over the
Internet from foreign providers. The apparent growth in
“imports” and “exports” has been fuelled by a number of
factors. Technological advances in information communication systems allow patients or third party purchasers of
health care the possibility to seek out quality treatment at
lower cost and/or more immediately from health care
providers in other countries. An increase in the portability
of health coverage, whether as a result of regional arrangements with regard to public health insurance systems, or
developments in the private insurance market, are also
poised to further increase patient mobility. All this is
coupled with a general increase in the temporary movement of populations for business, leisure or specifically for
medical reasons between countries.
While the major part of international trade in health
services does involve the physical movement of patients
across borders to receive treatment, to get a full measure of
imports and exports, there is also a need to consider goods
and services delivered remotely such as pharmaceuticals
ordered from another country or diagnostic services
provided from a doctor in one country to a patient in
another. The magnitude of such trade remains small, but
advances in technology mean that this area also has the
potential to grow rapidly.
The available data for OECD countries show that total
reported exports and imports of health-related travel each
amounted to more than USD 6 billion in 2009. Due to data
gaps and under-reporting, this is likely to be a significant
underestimate. Nevertheless, it is clear that, in comparison
to the size of total health expenditure, spending on healthrelated travel is marginal for most countries, but growing.
For example, while Germany reports the highest level of
imports in absolute terms, this represents only around 0.5%
of Germany’s current health expenditure (Figure 7.6.1).
Smaller countries such as Iceland and Portugal see a higher
level of cross-border movement of patients, but still
this only represents around 1% of health spending.
Luxembourg is a particular case with a large part of its
insured population living and consuming health services in
neighbouring countries.
Although the United States is by far the largest exporter,
reporting some USD 2.3 billion of exports in 2009, in relation
to overall spending on health, this remains largely insignifi-
158
cant (Figure 7.6.2). On the other hand, some central and
eastern European countries have become popular destinations for patients from other European countries, particularly for services such as dental surgery. Health-related
exports in the Czech Republic and Hungary were equivalent
to 3.6% and 2.1% of total health spending respectively.
Annual growth over the past five years has been significantly high in both the Czech Republic and Poland at 28%
and 42% per year.
Patient mobility in Europe could, however, receive a further
boost as the European Commission has sought to clarify
patients’ rights for treatment coverage in other member
states. Many of the proposed changes in European regulations try to strike a balance between the rights of patients
to seek health care and the responsibilities of states to
organise the delivery of health services. The European
Parliament approved the amended cross-border health
care bill in January 2011 with the law due to become
effective in 2013.
Definition and comparability
According to the Manual on Statistics of International
Trade in Services, “Health-related travel” is defined as
“goods and services acquired by travellers going
abroad for medical reasons”. In the balance of payments, trade refers to goods and services transactions
between residents and non-residents of an economy.
The System of Health Accounts includes imports within
current health expenditure, defined as imports of
medical goods and services for final consumption. Of
these, the purchase of medical services and goods by
resident patients while abroad, is currently the most
important in value terms. This trade is not well reported
by many of the countries reporting health accounts
according to the SHA. Exports are not currently recorded
under the System of Health Accounts and there remain
limits regarding comparability.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
7. HEALTH EXPENDITURE AND FINANCING
7.6. Trade in health services (medical tourism)
7.6.1 Imports of health care services as share of total health expenditure, 2009 and annual growth rate in real terms,
2004-09 (or nearest year)
2009
Change 2004-09
Luxembourg
Iceland
Portugal
Netherlands
Belgium1
Germany
Turkey1
Hungary
Canada1
Czech Republic
Slovak Republic
Austria
Korea
Sweden
Norway
Estonia
France 1
Italy1
Slovenia
Mexico 1
Denmark
Ireland1
Poland
Greece 1
United Kingdom1
United States1
9.49
1.11
1.02
0.89
0.59
0.47
0.44
0.30
0.24
0.21
0.20
0.20
0.18
0.16
0.14
0.14
0.14
0.14
0.13
0.10
0.08
0.07
0.06
0.06
0.05
0.04
2.0
1.5
% of total health expenditure
1.0
0.5
0
-6.8
12.2
5.5
1.7
-3.9
7.3
23.5
40.0
1.0
48.6
6.2
13.2
4.6
19.7
-6.4
58.1
2.0
23.6
-4.4
-10.0
-5.4
3.0
-4.0
-14.0
8.4
13.0
-20
0
20
40
60
80
Annual growth rate (%)
1. Refers to balance-of-payments concept of health-related travel.
Source: OECD Health Data 2011 and OECD-Eurostat Trade in Services Database.
1 2 http://dx.doi.org/10.1787/888932526331
7.6.2 Exports of health-related travel as share of total health expenditure, 2009 and annual growth rate in real terms,
2004-09 (or nearest year)
2009
Change 2004-09
Czech Republic
Hungary
Poland
Luxembourg
Turkey
Belgium
Estonia
Mexico
Slovenia
Greece
France
Korea
Israel
United States
Italy
Canada
United Kingdom
New Zealand
Austria
Iceland
3.58
2.08
1.62
1.15
0.98
0.84
0.67
0.48
0.20
0.19
0.15
0.15
0.13
0.11
0.08
0.08
0.06
0.06
0.03
0.02
4
3
% of total health expenditure
2
1
0
27.8
-3.6
41.9
35.7
3.5
-2.0
9.9
-1.3
-13.5
-7.7
0.6
8.9
-5.2
6.9
0.7
5.2
2.4
-1.7
5.7
-6.0
-20
0
20
40
60
Annual growth rate (%)
Note: Health-related travel exports occur when domestic providers supply medical services to non-residents travelling for medical reasons.
Source: OECD-Eurostat Trade in Services Database.
1 2 http://dx.doi.org/10.1787/888932526350
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
159
8. LONG-TERM CARE
8.1. Life expectancy and healthy life expectancy at age 65
8.2. Self-reported health and disability at age 65
8.3. Prevalence and economic burden of dementia
8.4. Recipients of long-term care
8.5. Informal carers
8.6. Long-term care workers
8.7. Long-term care beds in institutions and hospitals
8.8. Long-term care expenditure
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
161
8. LONG-TERM CARE
8.1. Life expectancy and healthy life expectancy at age 65
In OECD countries, life expectancy at age 65 has increased
significantly for both men and women during the past
50 years. Some of the factors explaining the gains in life
expectancy at age 65 include advances in medical care
combined with greater access to health care, healthier
lifestyles and improved living conditions before and after
people reach age 65.
cant gender gap in healthy life years means that women
are more likely to live with some type of activity limitation
after age 65 than men. Sweden and Norway had the highest
number of healthy life years at age 65 in 2009, with 14 years
or more for women and 13.5 years for men. The Slovak
Republic had the lowest number of healthy life years at less
than five for both women and men (Figure 8.1.2).
A growing share of the population is now age 65 and older.
Whether longer life expectancy is accompanied by good
health among ageing populations has important implications for health and long-term care systems.
Other OECD countries also calculate similar indicators of
disability-free life expectancy, although the survey instruments to measure disability may vary slightly. In Japan,
disability-free life expectancy at aged 65 was estimated to
be 15.6 years for women and 12.6 years for men in 2004
(Cabinet Office, Government of Japan, 2006). In the United
States, females born in 2001-02 can expect to live 66.9 years
free from activity limitation, and males 63.6 years (US
Department of Health and Human Services, 2006).
In 2009, people at age 65 in OECD countries could expect to
live for another 20.5 years on average for women and
17.2 years for men (Figure 8.1.1). Life expectancy at age 65 in
the OECD was the highest in Japan for women (24.0 years)
and Switzerland for men (19.0 years). Life expectancy at
age 65 is lower in Turkey as well as in some of the
major emerging economies such as South Africa and the
Russian Federation.
On average across OECD countries, life expectancy at age
65 has increased by 5.6 years for women and 4.4 years for
men since 1960. While the gender gap in life expectancy at
age 65 widened in many countries in the 1960s and the 1970s,
it has slightly narrowed over the past 30 years. In some
countries such as the United States, New Zealand and the
United Kingdom, the overall gains in life expectancy at age 65
since 1960 have been greater for men than for women.
Japan has achieved the highest gains in life expectancy at
age 65 since 1960, with an increase of almost ten years for
women and over seven years for men. The gains in life
expectancy have been more modest in some central and
eastern European countries, such as the Slovak Republic
and Hungary, particularly for men.
Increased life expectancy at age 65 does not necessarily
mean that the extra years lived are in good health. In Europe,
an indicator of disability-free life expectancy known as
healthy life years has recently been developed and is calculated regularly, based on a general question about disability
in the European Survey of Income and Living Conditions
(EU-SILC). Given that this indicator has only recently been
developed, long time series are not yet available.
In 2009, among European countries participating in the
survey, the average number of healthy life years at age 65
was almost the same for women and men, at 9.0 years for
women and 8.8 years for men. The absence of any signifi-
162
Definition and comparability
Life expectancy measures how long on average a
person of a given age can expect to live, if current
death rates do not change. However, the actual agespecific death rate of any particular birth cohort
cannot be known in advance. If rates are falling, as
has been the case over the past decades in OECD
countries, actual life spans will be higher than life
expectancy calculated using current death rates. The
methodology used to calculate life expectancy can
vary slightly between countries. This can change a
country’s estimates by a fraction of a year.
Disability-free life expectancy, or healthy life years,
are the number of years spent free of activity limitation. In Europe, Healthy Life Years are calculated
annually by Eurostat for EU countries and some EFTA
countries using the Sullivan method (Sullivan, 1971).
The disability measure is the Global Activity Limitation Indicator (GALI) which comes from the European
Union Statistics on Income and Living Conditions
(EU-SILC) survey. The GALI measures limitation in
usual activities due to health problems.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.1. Life expectancy and healthy life expectancy at age 65
8.1.1 Life expectancy at age 65, 2009 and years gained since 1960 (or nearest year)
Life expectancy at 65, 2009
Females
Males
24.0
22.5
22.4
22.2
22.0
21.8
21.5
21.5
21.4
21.3
21.2
21.2
21.1
21.1
21.1
21.0
20.8
20.8
20.8
20.6
20.6
20.5
20.5
20.2
20.1
20.0
20.0
19.5
19.1
19.1
18.8
18.3
18.0
17.6
17.6
16.5
15.9
15.8
25
Years
20
Years gained, 1960-2009
Females
Japan
France
Spain
Switzerland
Italy
Australia
Finland
Korea
Luxembourg
Canada
Israel
Austria
New Zealand
Norway
Belgium
Sweden
United Kingdom
Germany
Netherlands
Iceland
Ireland
Portugal
OECD
Greece
Slovenia
United States
Chile
Denmark
Brazil
Poland
Czech Republic
Estonia
Mexico
Slovak Republic
Hungary
Russian Federation
Turkey
South Africa
18.9
18.2
18.3
19.0
18.2
18.7
17.3
17.1
17.6
18.1
18.9
17.7
18.6
18.0
17.5
18.0
18.1
17.6
17.4
18.3
17.2
17.1
17.2
18.1
16.3
17.3
17.0
16.8
16.3
14.7
15.2
14.4
17.0
13.9
13.7
12.0
14.0
11.9
15
10
5
0
Males
9.9
7.3
6.9
7.1
7.1
6.7
5.7
5.2
6.1
4.8
6.2
5.8
6.2
7.8
n.a.
6.9
5.1
4.6
5.2
n.a.
6.5
5.7
5.8
5.6
5.0
3.5
6.4
5.3
5.7
5.7
4.3
6.2
6.6
5.4
5.5
3.5
3.3
3.8
6.2
6.0
4.6
4.7
4.4
5.6
3.9
3.2
n.a.
4.2
4.5
n.a
4.2
3.1
n.a.
4.2
4.2
2.0
2.8
n.a.
3.4
2.8
3.0
0.7
3.8
1.4
n.a.
3.8
2.8
n.a.
0
2
4
6
8
10
Years
Source: OECD Health Data 2011 and national sources for the Russian Federation, South Africa and Brazil.
1 2 http://dx.doi.org/10.1787/888932526369
8.1.2 Healthy life years at age 65, European countries, 2009
3.4
2.8
5.5
5.3
6.6
5.4
6
5.7
5.6
6.4
6.5
7.2
6.6
8
7.3
6.8
6.8
7.4
8.1
8.0
8.0
8.4
9.2
8.4
8.9
8.1
8.8
9.0
Females
8.8
9.2
9.3
9.9
10
10.5
10.1
9.4
10.3
10.2
10.5
11.8
10.8
11.4
10.7
12
11.2
12.0
12.7
13.6
13.5
14.0
14
13.6
14.6
Males
Years
16
4
2
K
SV
T
ES
T
PR
N
HU
U
DE
C
GR
IT
A
PO
L
T
AU
E
CZ
P
ES
N
FI
A
CD
OE
FR
N
SV
L
BE
D
NL
L
IR
X
LU
R
GB
K
DN
L
IS
R
NO
SW
E
0
Source: European Health and Life Expectancy Information System (EHLEIS); Eurostat Statistics Database.
1 2 http://dx.doi.org/10.1787/888932526388
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
163
8. LONG-TERM CARE
8.2. Self-reported health and disability at age 65
Most OECD countries conduct regular health surveys which
allow respondents to report on different aspects of their
health. A question that is often found among such surveys
relates to self-perceived health status, and is usually
similar to: “How is your health in general?”. Although these
questions are subjective, indicators of perceived general
health have been found to be a good predictor of people’s
future health care use and mortality (see Miilunpalo et al.,
1997). However, cross-country differences in perceived
health status may be difficult to interpret. This is because
survey questions may differ slightly, and cultural factors
can affect responses.
close to the European average. The highest rate of selfreported disability rates are in the Slovak Republic,
followed by Portugal and Estonia.
Keeping these limitations in mind, more than half of the
population aged 65 years and over rate their health to be
good or better in 12 of the 31 OECD countries for which data
are available (Figure 8.2.1). New Zealand, the United States,
Canada have the highest percentage of older people assessing their health to be good or better, with at least three out
of four people reporting to be in good health. But the
response categories offered to survey respondents in these
three countries are different from those used in most other
OECD countries, introducing an upward bias in the results
(see box on “Definition and comparability”).
Self-reported health reflects people’s overall perception of their own health, including both physical and
psychological dimensions. Typically, survey respondents are asked a question such as: “How is your
health in general? Very good, good, fair, poor, very
poor”. OECD Health Data provides figures related to the
proportion of people rating their health to be “good/
very good” combined.
In Israel and Spain, around 40% of persons aged 65 years
and over rate their health as good. In Poland, Portugal and
Estonia, the figure was less than 15%. In almost all
countries, men over 65 were more likely than women to
rate their health as good or better, the exceptions being
Australia and Chile. On average across OECD countries,
49% of men aged over 65 rate their health to be good or
better, while 42% of women do so.
The percentage of the population aged 65 years and over
who rate their health as being good or better has remained
fairly stable over the past 30 years in most countries where
long time series are available. Some improvement is
evident in the United States, where the share has increased
from 70% in 1980 to 76% in 2009.
Measures of disability are not yet standardised across
countries. In Europe, based on the EU Survey of Income and
Living Conditions, 43% of people aged between 65 and
74 years reported that they were limited in their usual daily
activities because of a health problem in 2009, this being
one common definition of disability. The proportion rises
to 60% for people aged 75 and over (Figure 8.2.2). While a
large proportion of the population reported only moderate
activity limitation, over 14% aged 65-74 years, and 25%
aged 75 years and over reported being severely limited, on
average among a group of 24 European OECD countries.
Severe activity limitations are more likely to create needs
for long-term care, whether formal or informal.
People in Nordic countries reported the lowest level of
moderate or severe disability, with the exception of
Finland, where self-reported disability rates are higher and
164
Definition and comparability
Caution is required in making cross-country comparisons of perceived health status, for at least two
reasons. First, people’s assessment of their health is
subjective and can be affected by cultural factors.
Second, there are variations in the question and
answer categories used to measure perceived health
across surveys/countries. In particular, the response
scale used in Australia, Canada, New Zealand and the
United States is asymmetric (skewed on the positive
side), including the following response categories:
“excellent, very good, good, fair, poor”. The data
reported in OECD Health Data refer to respondents
answering one of the three positive responses (“excellent, very good or good”). By contrast, in most other
OECD countries, the response scale is symmetric,
with response categories being: “very good, good, fair,
poor, very poor”. The data reported from these
countries refer only to the first two categories (“very
good, good”). Such difference in response categories
biases upward the results from those countries that
are using an asymmetric scale.
Perceived general disability is measured in the
EU-SILC survey through the question: “For at least the
past six months, have you been hampered because of
a health problem in activities people usually do? Yes,
strongly limited/Yes, limited/No, not limited”. Persons
in institutions are not surveyed, resulting in an underestimation of disability prevalence. Again, the
measure is subjective, and cultural factors may affect
survey responses.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.2. Self-reported health and disability at age 65
8.2.1 Population aged 65 years and over reporting to be in good health, 2009 (or nearest year)
Females
New Zealand1
United States1
Canada1
Denmark
Switzerland
Australia1
Norway
Ireland
Sweden
Netherlands
Belgium
Iceland
Austria
OECD
Luxembourg
France
Mexico
Israel
Spain
Chile
Greece
Germany
Czech Republic
Korea
Slovenia
Italy
Turkey
Japan
Hungary
Estonia
Portugal
Poland
83.2
75.8
75.5
74.8
71.8
68.4
68.0
63.2
62.3
60.0
56.5
54.6
47.4
45.2
44.7
43.2
42.7
41.8
40.5
37.9
37.3
36.8
35.4
32.7
26.2
22.8
20.2
20.0
18.1
14.0
13.8
10.3
90
60
% of population aged 65 years and over
30
0
83.2
75.8
75.9
78.4
75.2
66.6
72.0
63.0
64.9
67.1
61.4
58.2
55.2
49.0
46.1
45.4
44.2
48.8
48.6
37.1
43.0
38.5
45.6
39.6
37.0
27.8
27.6
22.1
21.6
17.6
18.2
13.4
Males
83.2
75.9
75.1
71.9
69.2
69.9
64.0
63.4
60.1
54.3
52.8
51.4
44.1
42.4
43.7
41.5
41.3
36.4
34.4
38.4
32.6
35.5
29.2
28.0
19.3
19.0
14.6
18.4
15.5
12.3
10.6
8.4
0
30
60
90
% of population aged 65 years and over
1. Results for these countries are not directly comparable with those for other countries, due to methodological differences in the survey
questionnaire resulting in an upward bias.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526407
8.2.2 Limitations in daily activities, population aged 65-74 years and 75 years and over, 2009
Limited to some extent
Limited strongly
7.7
9.7
8.2
20.8
16.5
8.1
9.6
13.3
12.3
8.7
10.5
19.4
15.4
11.8
14.3
15.8
9.8
16.5
14.0
20.2
16.1
16.8
15.8
19.8
26.6
80
60
% of population aged 65-74 years
40
20
Limited to some extent
Sweden
Norway
Denmark
Iceland
United Kingdom
Switzerland
Ireland
Luxembourg
Belgium
Netherlands
Czech Republic
Slovenia
France
Finland
OECD
Austria
Spain
Poland
Italy
Greece
Germany
Hungary
Estonia
Portugal
Slovak Republic
14.5
14.2
19.1
11.4
18.9
27.5
27.5
24.1
25.2
30.2
29.7
21.3
26.9
30.8
29.1
30.5
36.9
33.8
37.3
31.4
37.5
39.5
42.1
39.1
48.2
0
16.9
19.1
28.5
8.6
23.0
32.2
34.8
33.9
34.3
41.9
40.4
26.5
33.8
39.2
34.0
34.0
42.6
37.0
44.1
35.5
44.5
42.3
46.6
38.9
37.7
0
Limited strongly
17.1
14.0
16.0
24.2
23.9
13.2
18.2
15.1
20.0
14.9
22.1
29.2
32.2
27.6
26.1
33.6
21.6
29.2
29.8
39.0
30.8
33.2
32.5
37.9
49.9
20
40
60
80
% of population aged 75 years and over
Source: European Union Statistics on Income and Living Conditions 2009.
1 2 http://dx.doi.org/10.1787/888932526426
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
165
8. LONG-TERM CARE
8.3. Prevalence and economic burden of dementia
Dementia describes a variety of brain disorders which
progressively lead to brain damage, and cause a gradual
deterioration of the individual’s functional capacity and
social relations. Alzheimer’s disease is the most common
form of dementia, representing about 60% to 80% of cases.
Currently, there is no treatment that can halt dementia, but
pharmaceutical drugs and other interventions can slow the
progression of the disease.
In 2009, there were an estimated 14 million people aged
60 years and over suffering from dementia in OECD countries, accounting for more than 5% of the population in that
age group, according to estimates by Wimo et al. (2010)
(Figure 8.3.1). France, Italy, Switzerland, Spain and Sweden
had the highest prevalence, with 6.3% to 6.5% of the population aged 60 years or older estimated as having dementia.
The prevalence rate was only about half these rates in some
emerging economies including South Africa, Indonesia and
India, although this in part reflects fewer detected cases.
Clinical symptoms of dementia usually begin after the age
of 60, and the prevalence increases markedly with age
(Figure 8.3.2). The disease affects more women than men.
In Europe, 14% of men and 16% of women aged 80-84 years
were estimated as having dementia in 2009, compared to
less than 4% among those under 75 years of age (Alzheimer
Europe, 2009). For the very elderly aged 90 years and over,
the figures rise to 31% of men and 47% of women. A similar
pattern is observed in Australia (Alzheimer’s Australia,
2009). Early-onset dementia among people aged younger
than 65 years is rare; they comprise less than 2% of the
total number of people with dementia.
People with Alzheimer’s disease and other dementias are
high users of long-term care services. Wimo and colleagues
(2010) used cost-of-illness studies from different countries
and an imputation method for countries lacking specific cost
data to estimate the direct costs of dementia, including only
the resources used to care for people with dementia. For those
countries where an imputation was necessary, it was
assumed that the expenditures per person with dementia as
a share of GDP were similar to those found in countries with
available data. In 2009, the direct costs of dementia were
estimated at 0.5% of GDP on average among OECD countries.
Direct costs were highest in Italy and Japan, reaching close to
166
0.8% of GDP (Figure 8.3.3). As expected, countries that have a
higher prevalence of dementia tend to spend more than those
with a lower prevalence (Maslow, 2010).
As the number of older persons suffering from dementia is
already large, and is expected to grow in the future, dementia
has become a health policy priority in many countries.
National policies in Australia, Austria, Canada, France, the
United States and other countries typically involve measures
to improve early diagnosis, promote quality of care for people
with dementia, and support informal care givers (Wortmann,
2009; Juva, 2009; Ersek et al., 2009; Kenigsberg, 2009).
Definition and comparability
Dementia prevalence rates are based on estimates of
the total number of persons aged 60 years and over
living with dementia divided by the size of the corresponding population. Estimates by Wimo et al. (2010)
are based on previous national epidemiological
studies and meta-analyses.
Wimo et al. (2010) used cost-of-illness studies from
different countries and an imputation method for
countries lacking specific cost data to estimate the
direct costs of dementia, including only the resources
used to care for people with dementia. For countries
where an imputation was necessary, it was assumed
that the expenditures per person with dementia as a
share of GDP were similar to those found in countries
with available data. All cost figures are expressed as
constant USD in 2009, adjusted for purchasing power
parities (PPPs). Cost studies are inherently difficult,
especially when there are co-morbidities.
Given the divergence in scale and accuracy of the
sources used across countries, the estimates should
be used with caution.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.3. Prevalence and economic burden of dementia
8.3.1 Prevalence of dementia among the population aged 60 years and over, 2009
3.4
3.2
3.5
4
3.5
4.2
4.0
4.7
4.7
4.8
4.7
5.0
5
4.9
5.1
5.0
5.2
5.1
5.3
5.3
5.4
5.3
5.5
5.4
5.6
5.5
5.6
5.6
5.7
5.7
5.8
5.8
6.1
6
5.9
6.1
6.1
6.2
6.2
6.3
6.3
6.4
6.3
6.5
% of population aged 60 years and over
7
3
2
1
FI
N
NL
D
ES
T
IS
L
SV
N
IR
L
PO
L
GR
C
HU
N
CH
L
RU
S
SV
K
CZ
E
M
EX
BR
A
KO
R
CH
N
TU
R
IN
D
ID
N
ZA
F
FR
A
IT
A
CH
E
ES
P
SW
E
NO
R
US
A
GB
R
JP
N
BE
L
AU
T
DE
U
AU
S
CA
N
NZ
L
PR
T
LU
X
DN
OE K
CD
IS
R
0
Source: Wimo et al. (2010).
1 2 http://dx.doi.org/10.1787/888932526445
8.3.2 Age- and gender-specific prevalence of dementia in Europe and Australia, 2009
Europe – males
%
Europe – females
Australia – males
Australia – females
45
40
35
30
25
20
15
10
5
0
65-69
70-74
75-79
80-84
85-89
90+
Age
Source: Alzheimer Europe (2009); Alzheimer’s Australia (2009).
1 2 http://dx.doi.org/10.1787/888932526464
8.3.3 Direct cost of dementia for population aged 60 years and over, as a share of GDP, 2009
0.17
0.13
0.18
0.17
0.21
0.20
0.28
0.25
0.31
0.42
0.43
0.44
0.44
0.47
0.45
0.48
0.50
0.54
0.54
0.51
0.47
0.42
0.36
0.33
0.29
0.3
0.2
0.39
0.4
0.49
0.5
0.54
0.57
0.56
0.58
0.57
0.59
0.58
0.60
0.6
0.60
0.63
0.62
0.64
0.7
0.77
0.8
0.79
% of GDP
0.9
0.1
IT
A
JP
N
DE
U
SW
E
FR
A
DN
K
BE
L
ES
P
GB
R
FI
N
ES
T
PR
T
AU
T
IS
L
CH
E
HU
N
NO
R
US
OE A
CD
CA
N
NZ
L
AU
S
LU
X
GR
C
SV
N
NL
D
RU
S
IR
L
CZ
E
PO
L
IS
R
SV
K
CH
L
CH
N
KO
R
BR
A
ID
N
IN
D
M
EX
ZA
F
TU
R
0
Source: Wimo et al. (2010).
1 2 http://dx.doi.org/10.1787/888932526483
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
167
8. LONG-TERM CARE
8.4. Recipients of long-term care
The number of people receiving long-term care (LTC) in
OECD countries is rising, mainly due to population ageing
and the growing number of elderly dependent persons, as
well as the development of new programmes and services
in several countries. In response to most people’s preference to receive LTC services at home, an important trend
in many OECD countries over the past decade has been
the implementation of different types of programmes to
support home-based care.
Although the receipt of long-term care is not limited to
elderly people, the vast majority of LTC recipients are over
65 years of age. Most of them are also women, because of
their higher life expectancy combined with a higher prevalence of disabilities and functional limitations in old age.
On average across OECD countries, about 12% of the population aged 65 and over were receiving some long-term care
services at home or in institutions in 2009 (Figure 8.4.1).
The use of long-term care services increases sharply with
age, with people aged 80 and older being more than six
times more likely to receive long-term care than people
aged 65-79 in many countries.
The number of LTC recipients as a share of the population
65 years and over was the highest in Austria in 2009, with
almost one-fourth of the senior population receiving longterm care benefits either in institutions or at home. On the
other hand, only about 1% of the senior population in
Poland and Portugal receive formal LTC services, with most
of them receiving care in institutions, although many more
may receive informal care from family members at home.
Over the past decade, many OECD countries have introduced programmes to promote the delivery of long-term
care at home. Several countries have expanded community-based services and home care coverage and support
(e.g. Canada, Ireland and Sweden). Some countries have
introduced financial support for users, for instance in the
form of cash benefits for LTC recipients at home in Austria
and the Netherlands.
In most countries for which trend data are available, the
number of people receiving long-term care at home as a
share of the total number of LTC recipients has increased
over the past ten years (Figure 8.4.2). The proportion of LTC
recipients at home is the highest in Japan and Norway. In
both countries, the proportion has gone up over the past
decade, so that now more than three-quarters of LTC recipients receive care at home. The share of home-based care
recipients has also increased in Sweden, Luxembourg and
Hungary. In Hungary, LTC in institutions has been restricted
by budgetary constraints and stricter admission criteria. In
Finland, there has been a significant reduction in the share
of home-based care recipients over the past decade. The
number of people receiving LTC at home has not declined,
but it has grown at a much slower rate than the number of
168
people receiving care in institutions. This may be due to the
fact that a larger number of people have more severe conditions or that they live in remote areas where home-based
care options may be limited.
In the United States, only around half of LTC recipients
receive care at home. This may partly reflect a traditional
bias towards supporting institutional-based care. Financial
support to promote home-based care has only been implemented by certain states. Additional support may be
needed in the United States and in other countries to
further encourage home-based care (Colombo et al., 2011).
Definition and comparability
LTC recipients are defined as persons receiving
long-term care by paid providers, including nonprofessionals receiving cash payments under a social
programme. They also include recipients of cash
benefits such as consumer-choice programmes, care
allowances or other social benefits which are granted
with the primary goal of supporting people with longterm care needs. Long-term care institutions refer to
nursing and residential care facilities which provide
accommodation and long-term care as a package.
Long-term care at home is defined as people with
functional restrictions who receive most of their care
at home. Home care also includes specially designed
or adapted living arrangements.
Data for Japan underestimate the number of recipients in institutions because many elderly people
receive long-term care in hospitals. In the Czech
Republic, LTC recipients refer to recipients of the care
allowance (i.e. cash allowance paid to eligible dependent persons). In Poland and Spain, the data underestimate the total number of LTC recipients due to
partial coverage of facilities or services. In Australia,
the data do not include recipients who access the
Veterans’ Home Care Program and those who access
services under the National Disability Agreement.
With regard to the age threshold, data for Austria,
Belgium, France and Poland refer to people aged
over 60, while they refer to people over 62 in the
Slovak Republic (this is resulting in a slight underestimation of the share in these countries, given that
a much smaller proportion of people aged 60-65
or 62-65 receive LTC compared with older age groups).
LTC recipients refer to people aged over 67 in Norway.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.4. Recipients of long-term care
8.4.1 Population aged 65 years and over receiving long-term care, 2009 (or nearest year)
Institutions
Home
Institutions + home
% of population aged 65 years and over
25 23.9
22.2
19.4
20
18.2
18.2
17.6
17.5
16.1
15
13.9
13.1
12.8
12.6
12.2
12.0
11.3
11.1
10.0
10
7.8
6.7
6.6
6.5
5.9
5.1
5
4.0
3.7
3.6
3.2
3.2
1.1
0.9
er
la
n
Sw d
ed
De en
N e nm
ar
w
Ze k
al
an
d
C z Aus
t
ec
h r a li a
Re
L u pub
li
xe
m c
bo
ur
g
Ja
pa
OE n
CD
21
Fi
nl
a
Ge nd
rm
an
y
Fr
an
c
Hu e
ng
ar
Es y
to
n
Be ia
lg
iu
m
S
Un lov
e
i te
ni
a
d
St
at
es 1
Ic
el
an
d
Sp
ai
n
Ir e
la
nd
It a
ly
Sl
ov C an
ak
ad
Re a
pu
bl
ic
Ko
re
Po a
r tu
ga
Po l
la
nd
s
ay
rw
Sw
it z
No
nd
Ne
th
er
la
ra
Is
Au
st
ria
el
2
0
1. In the United States, data for home care recipients refer to 2007 and data for recipients in institutions refer to 2004.
2. In Austria, it is not possible to distinguish LTC recipients at home or in institutions. The data refer to people receiving an allowance for LTC,
regardless of whether the care is provided at home or in institutions. Because of this, Austria is not included in the OECD average.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526502
8.4.2 Share of long-term care recipients receiving care at home, 1999 and 2009 (or nearest year)
1999
2009
% of total LTC users
80
77.0
76.7
72.3
71.7
70.4
71.3
70.5
70.1
70
68.7
67.7
66.9
66.6
64.5
61.5
60
59.4
59.2
58.7
58.0
56.8
53.8
55.4
54.1 54.4
52.8
50.6
50
47.8
es
at
li a
d
i te
Un
Au
st
St
ra
m
Be
lg
iu
d
an
Fi
nl
ly
It a
CD
OE
y
ng
Hu
bo
m
xe
Lu
ar
g
ur
en
ed
Sw
an
rm
Ge
la
er
it z
Sw
y
nd
ay
rw
No
Ja
pa
n
40
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526521
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
169
8. LONG-TERM CARE
8.5. Informal carers
Informal carers are the backbone of long-term care systems
in all OECD countries, although there are substantial variations across countries on the relative importance of informal care giving by family members compared with the use
of more formal long-term care providers. Because of the
informal nature of care provided by family members, it is
not easy to get comparable data on the number of informal
carers across countries, nor on the amount of time that
they devote to care giving. The data presented in this
section come from national or international health
surveys, and refer to people aged 50 years and over who
report providing care and assistance to a family member
for activities of daily living (ADL).
Intensive care giving is associated with a reduction in labour
force attachment for care givers of working age, higher
poverty rates, and a higher prevalence of mental health
problems. Many OECD countries have implemented policies
to support informal carers with a view to mitigate these negative impacts. These include paid care leave (e.g. Belgium),
allowing flexible work schedules (e.g. Australia and the
United States), providing respite care (e.g. Austria, Denmark
and Germany) as well as counselling/training services
(e.g. Sweden). Moreover, a number of OECD countries
provide cash benefits to informal care givers or cash-for-care
allowances for recipients which can be used to pay informal
care givers (Colombo et al., 2011).
On average across OECD countries, one-in-nine people
aged 50 and over reported providing care and ADL assistance for a dependent relative around 2007. The percentage
ranges from a low of 8% in Sweden, where formal care
provision is more developed, to a rate about two-times
greater in Italy and Spain (Figure 8.5.1). In Italy, the high
proportion of people reporting to provide care to a family
member is associated with relatively few formal (paid) LTC
workers (see Indicator 8.6 “Long-term care workers”).
Recent OECD work has estimated that the potential pool of
working-age and older informal carers is likely to shrink in
the coming decades as a result of declining family size,
changes in residential patterns of people with disabilities,
and rising participation rates of women in the labour
market. Across OECD countries, the share of people aged
over 80 years, compared with the population share aged 15
to 80, will almost triple in coming decades, rising from 5%
in 2010 to close to 13% in 2050. Therefore, it is likely that a
greater share of people providing informal care may be
required to provide high-intensity care. Without adequate
support, informal care giving might exacerbate employment and health inequalities (Colombo et al., 2011).
Most informal carers are women. On average across
countries, about 66% of carers between the age of 50 and 64
are women. Among the population aged 75 and over, this
percentage drops slightly to about 60% (Figure 8.5.2).
Many informal carers provide a limited number of hours of
care per week, although there is wide variation across
countries (Figure 8.5.3). On average across countries,
slightly more than 50% of carers provide less than
ten hours of care per week. This proportion is particularly
high in some Nordic countries (Denmark and Sweden),
where a greater share of LTC services is provided by paid
workers. By contrast, in Korea as well as in some southern
European countries (Spain, Greece and Italy) and in the
Czech Republic and Poland, most informal care givers
spend more time providing care to a family member. In the
United States also, a high proportion of informal care givers
provide over ten hours of care per week, with many of them
providing more than 20 hours.
170
Definition and comparability
Informal carers are defined as people providing assistance with basic activities of daily living (ADL) for at
least one hour per week. The data relate only to the
population aged 50 and over, and are based on
national or international health surveys. Data for the
United States include care provided for parents only.
Survey results may be affected by reporting biases or
recall problems.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.5. Informal carers
8.5.1 Population aged 50 and over reporting to be informal carers, around 2007
15.3
15.2
14.6
12.1
11.7
11.4
11.2
11.0
10.8
10.7
10.3
9.8
9.3
8.7
8.0
10
12.0
15
16.2
%
20
5
IT
A
P
GB
IR
ES
R
L
L
CZ
BE
E
CD
OE
NL
DE
AU
D
S
U
E
CH
A
FR
PO
L
T
AU
K
DN
GR
SW
C
E
0
Source: OECD estimates based on the 2005-07 HILDA survey for Australia, the 2007 BHPS survey for the United Kingdom and the 2004-06 SHARE survey
for other European countries.
1 2 http://dx.doi.org/10.1787/888932526540
8.5.2 Share of women among all informal carers aged 50 and over, around 2007
50-64
75 and over
60.7
66.2
50.8
59.6
60.7
65.9
61.6
61.1
65.1
61.9
61.1
65.6
62.2
61.7
70.0
65.0
62.9
63.5
48.8
54.2
53.6
64.5
68.0
69.7
70.6
48.8
46.3
50
64.9
65.4
65.8
64.6
60.0
65.5
64.4
69.5
76.0
66.3
66.8
67.7
59.3
60
55.0
58.9
54.7
70
68.0
66.0
67.3
69.3
66.7
75.1
75.6
77.6
68.1
80
65-74
82.9
%
90
33.7
40
PO
L
T
AU
L
KO
BE
R
U
NL
DE
D
R
GB
IT
A
S
AU
CH
E
E
CZ
OE
FR
CD
A
E
SW
P
ES
L
IR
DN
GR
C
K
30
Source: OECD estimates based on the 2005-07 HILDA survey for Australia, the 2007 BHPS survey for the United Kingdom, the 2004-06 SHARE survey for
other European countries and the 2005 KLoSA survey for Korea.
1 2 http://dx.doi.org/10.1787/888932526559
8.5.3 Weekly hours of care provided by informal carers, around 2007
20+ hours
52.2
20.4
17.6
31.7
8.9
15.2
16.1
35.4
34.2
30.5
39.9
44.9
47.9
43.4
38.9
15.4
37.8
32.4
14.2
15.9
16.4
29.9
17.6
26.7
18.3
17.5
27.3
30.3
14.2
27.1
13.2
24.7
13.8
22.6
14.0
15.4
13.2
9.5
15.3
8.6
20
10
18.5
30
33.4
50
40
45.6
48.0
51.2
52.1
52.6
55.0
55.1
60
55.5
59.6
61.5
63.4
71.5
71.7
76.1
70
10-19 hours
62.0
0-9 hours
% of carers
80
R
KO
P
ES
A
US
C
GR
L
PO
IT
A
E
CZ
L
BE
CD
OE
T
AU
R
GB
S
AU
DE
U
A
FR
D
NL
L
IR
E
SW
E
CH
DN
K
0
Source: OECD estimates based on the 2005-07 HILDA survey for Australia, the 2007 BHPS survey for the United Kingdom, the 2004-06 SHARE survey for
other European countries, the 2005 KLoSA survey for Korea and the 2006 HRS survey for the United States.
1 2 http://dx.doi.org/10.1787/888932526578
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
171
8. LONG-TERM CARE
8.6. Long-term care workers
The provision of long-term care (LTC) is a labour-intensive
activity. The data on formal LTC workers presented in this
section refer to nurses as well as personal carers (i.e. other
LTC workers who do not qualify as nurses) who are paid to
provide care and/or assistance with activities of daily living
to people requiring long-term care at home or in institutions other than hospitals.
In proportion to the population aged 65 and over, the
number of formal LTC workers is highest in Sweden and
Norway. Portugal and Italy have the lowest number
(Figure 8.6.1). In some countries such as Norway, Denmark,
the Netherlands, Switzerland and New Zealand, a majority
of LTC workers provide care in institutions, even though
most LTC recipients may receive care at home (see
Indicator 8.4 “Recipients of long-term care”). This can be
explained at least partly by the fact that people receiving
LTC in institutions often have more severe diseases and
limitations and require more intensive care. In other
countries such as Estonia, Israel, Korea and Japan, there are
relatively few LTC workers in institutions, and most formal
care givers provide care in the patient’s home.
Most LTC workers are women and work part-time. For
example, in Canada, Denmark, Korea, New Zealand and
Norway, over 90% of LTC workers are women. Foreign-born
workers also play an important role in LTC, although their
presence is uneven across OECD countries. While Germany
has very few foreign-born LTC workers, in the United States
nearly one in every four care workers is foreign-born
(Colombo et al., 2011). In other countries, foreign-born
workers represent an important share of people providing
home-based services, including LTC services. This is the
case, for instance, in Italy where about 70% of people providing services at home are foreign-born (Colombo et al.,
2011). The recruitment of foreign-born workers to provide
LTC at home or in institutions can help respond to growing
demand, often at a relatively low cost. But the growing
inflows of LTC workers from other countries have raised
some issues in certain countries, such as the management
of irregular migration inflows and paid work which is
undeclared for tax and social security purposes.
The mix between nurses and lower-skilled personal care
workers providing LTC services vary significantly across
OECD countries (Figure 8.6.2). On average, about 25% of
formal LTC providers are nurses, while the other 75% are
personal care workers (who may be called under different
names in different countries, such as nursing aides, health
assistants in institutions, home-based care assistants, etc.).
In some countries (e.g. the United States and Switzerland),
qualified nurses represent the bulk of formal LTC providers,
while in others (Estonia and Korea), they represent only a
very small proportion of LTC workers. This wide variation
may be partly explained by institutional factors, such as
public health insurance coverage in certain countries that
includes some LTC services (Switzerland) or a relatively
high share of LTC services provided in institutions where
higher-skilled LTC workers are more likely to work (the
United States). Many countries are looking at possibilities
to delegate some of the tasks currently provided by nurses
to lower-skilled providers to increase the supply of services
and reduce costs, while ensuring that minimum standards
of quality of care are maintained.
172
The LTC workforce still represents only a small share of
total employment, but this share has increased over the
past decade in many countries, along with the broadening
of public protections against LTC risks and increased
demand stemming from population ageing. In Japan, the
number of LTC workers has grown by 9% per year since the
implementation of the universal LTC insurance programme
in 2000, while there was a slight decrease in total employment in the economy during that period (Figure 8.6.3). In
contrast, in Sweden, the average growth rate of LTC
workers between 2000 and 2009 was much more modest, at
only 0.3% per year.
Given population ageing and the expected decline in the
availability of family care givers, the demand for LTC
workers as a share of the working population is expected to
at least double by 2050. A combination of policies is needed
to respond to this growing demand for formal LTC workers,
including policies to improve recruitment (e.g. encouraging
more unemployed people to consider training and working
in the LTC sector); improve retention (e.g. enhancing pay and
work conditions); and increase productivity (e.g. through
reorganisation of work processes and more effective use of
new technologies) (Colombo et al., 2011).
Definition and comparability
Long-term care workers are defined as paid workers
who provide care at home or in institutions (outside
hospitals). They include qualified nurses (see definition under Indicator 3.7 “Nurses”) and personal care
workers providing assistance with ADL and other
personal support. Personal care workers include
different categories of workers who may be called
under different names in different countries. They
may have some recognised qualification or not.
Because personal care workers may not be part of
recognised occupations, it is more difficult to collect
comparable data for this category of LTC workers. LTC
workers also include family members or friends who
are employed under a formal contract either by the
care recipient, an agency, or public and private care
service companies. The numbers are expressed as
head counts, not full-time equivalent.
The data for Germany exclude elderly care nurses,
formal workers working predominantly in administration, and persons declared to social security
systems as care givers, resulting in a substantial
under-estimation. The data for Italy exclude workers
in semi-residential long-term care facilities. The data
for Japan involve double-counting as some workers
may work in more than one home. The data for
Ireland refer only to the public sector.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.6. Long-term care workers
8.6.1 Long-term care workers as share of population aged 65 and over, 2009 (or nearest year)
Institutions
Home
Institutions + home
% of population aged 65 years and over
14
12
10
5.9
8
2.7
3.1
1.6
0.4
T
PR
A
1.1
FR
K1
1.7
IT
A
0.8
1.4
N
T
N
AU
U
N
FI
SV
R
L
IR
0.8
1.6
SV
2.8
E
3.0
HU
3.1
CZ
2.6
0.6
N
N
15
S
CD
L
1.2
3.6
4.4
2.6
DE
3.2
OE
AU
E
D
CH
T
1.9
3.9
1.5
NL
ES
K
R
DN
IS
A1
R
US
NO
4.5
0.6
1.1
0
5.0
KO
5.4
1.4
3.9
P1
6.3
CA
6.4
2
E1
2.5
7.4
7.0
SW
2.3
NZ
4
1.9
9.5
JP
11.9
ES
1.4
13.0
6
1. In Sweden, the United States, Spain and the Slovak Republic, it is not possible to distinguish LTC workers in institutions and at home.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526597
8.6.2 Share of nurses in relation to all long-term care workers (nurses and personal care workers), 2009 (or nearest year)
%
60
62.6
53.6
50
38.0
40
32.6
31.8
30
27.1
26.3
25.0
23.7
23.4
22.6
20
15.3
12.4
10
5.6
R
KO
IS
0.1
T
R
E
SW
L
NZ
N
JP
SV
K
L
IR
CD
OE
S
U
AU
NL
DE
D
R
NO
E
K
CZ
US
DN
A
E
CH
0.6
ES
1.6
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526616
8.6.3 Trends in long-term care employment and total employment, 2000-09 (or nearest year)
LTC workers
Total employment
Average annual growth rate (%)
10
9.0
8
6
5.0
4.0
4
3.2
3.2
2
1.1
0.6
n.a.
0
1.5
1.4
1.2
0.4
1.1
0.9
0.3
-0.1
-0.2
-0.3
E
SW
D
NL
K
DN
N
HU
R
NO
CD
OE
U
DE
R
IS
JP
N
-2
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526635
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
173
8. LONG-TERM CARE
8.7. Long-term care beds in institutions and hospitals
The number of beds in long-term care (LTC) institutions
and in LTC departments in hospitals provides a measure of
the resources available for delivering LTC services to individuals outside of their home. Long-term care institutions
refer to nursing and residential care facilities which
provide accommodation and long-term care as a package.
They include specially designed institutions or hospitallike settings where the predominant service component
is long-term care for people with moderate to severe
functional restrictions.
On average across OECD countries, there were 44 beds in
LTC institutions and 6 beds in LTC departments in hospitals
per 1 000 people aged 65 and over in 2009 (Figure 8.7.1).
Sweden had the highest number of LTC beds in 2009, with
80 beds per 1 000 people aged 65 and over in LTC institutions, but only a small number of beds allocated for LTC in
hospitals. In Italy and Poland, there were relatively few
beds in LTC institutions or in hospitals per 1 000 people
aged 65 years and over in 2009. Most LTC services in these
two countries are provided at home by informal care givers
(see Indicator 8.5 “Informal carers”).
While most countries report very few beds allocated for LTC
in hospitals, some countries continue to use hospital beds
quite extensively for LTC purposes. In Korea, there are
nearly as many LTC beds in hospitals as there are in dedicated LTC institutions. However, the number of beds in
LTC institutions has increased in recent years, especially
following the introduction of Korea’s public long-term care
insurance programme in 2008. In Japan, there is also a
fairly large number of hospital beds that have traditionally
been used for long-term care, but there have also been
recent increases in the number of beds in LTC institutions.
Among European countries, Finland and Ireland maintain a
fairly large number of LTC beds in hospitals. In Finland,
local governments are responsible for managing both
health and long-term care services, and have traditionally
used hospitals to provide at least some long-term care. In
both Finland and Ireland, there has been however a recent
rise in the number of beds in LTC institutions which has
been accompanied by a reduction in LTC beds in hospitals.
Many other OECD countries have developed the capacity of
LTC institutions to receive LTC patients once they no longer
need acute care in hospitals, in order to free up costly
hospital beds. The number of LTC beds in institutions has
increased more rapidly than the number of LTC beds in
174
hospitals in most countries (Figure 8.7.2). It has grown
particularly quickly in Korea and Spain, although it started
from a relatively low level and still remains well below the
OECD average. In Australia also, the number of beds in
institutions has increased rapidly over the past ten years.
In Sweden, both the number of LTC beds in hospitals and in
LTC institutions has declined slightly over the past decade,
although the capacity still remains the highest of all
countries. Sweden has implemented various measures in
recent years to promote home-based care, including the
use of cash benefits to promote home living and the
expansion of community-based LTC (Colombo et al., 2011).
Providing LTC in institutions is generally more expensive
than home-based care, if only because of the additional
cost of board and lodging. However, depending on individual circumstances, a move to LTC institutions may be the
most appropriate and cost-effective option, for example for
people living alone and requiring round the clock care and
supervision (Wiener et al., 2009) or people living in remote
areas with limited home-care support.
Definition and comparability
Long-term care institutions refer to nursing and
residential care facilities which provide accommodation and long-term care as a package. Beds in adapted
living arrangements for persons who require help
while guaranteeing a high degree of autonomy and
self control are not included. For international
comparisons, beds in rehabilitation centers are also
not included.
However, there are variations in data coverage across
countries. Several countries only include beds in
publicly-funded LTC institutions, while others also
include private institutions (both profit and non-forprofit). Some countries also include beds in treatment
centers for addicted people, psychiatric units of
general or specialised hospitals, and rehabilitation
centers.
Information on data for Israel: http://dx.doi.org/10.1787/
888932315602.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.7. Long-term care beds in institutions and hospitals
8.7.1 Long-term care beds in institutions and hospitals, per 1 000 population aged 65 and over, 2009 (or nearest year)
Institutions
Hospitals
Per 1 000 population aged 65 and over
90
81.7
80
74.8
72.5
71.9
69.3
70
68.5
67.8
62.9
61.7
60.9
60
57.7
56.7
55.1
54.2
51.2
50.3
50
49.5
48.8
47.8
42.6
42.3
40.5
40
37.4
34.7
32.1
31.1
30
19.8
20
17.5
10
Cz
ly
nd
It a
Po
la
el
Is
Sp
a in
a
ra
re
n
pa
Ko
Ja
a
ni
Es
Au
st
ria
es
to
at
St
d
i te
Un
ec
h
xe
Re
pu
bl
ur
ic
g
19
bo
m
CD
rm
Ge
Sl
Un
ov
i te
Lu
d
ak
OE
ar
an
y
k
ic
nm
De
Re
pu
bl
m
y
do
ar
ng
Ki
Hu
ng
ra
an
st
Au
w
Ne
Sw
li a
d
nd
Ze
al
la
ay
Ir e
rw
nd
it z
No
er
la
s
d
nd
an
Ne
th
er
Ic
el
la
m
ce
Be
lg
iu
d
an
an
Fr
nl
Fi
Sw
ed
en
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526654
8.7.2 Trends in long-term care beds in institutions and in hospitals, 2000-09 (or nearest year)
Institutions
Hospitals
Average annual growth rate (%)
30 28.3
25
20.2
20
15
10
7.8
6.6
5.6
5.3
5
0.9
5.1
0.9
4.6
4.3
3.8
3.6 3.3
5.6
4.4
3.4
2.9
2.7 2.9
2.5
0.9
0.4
0.8
0.7
0.5
0.0
0
0.3
-0.4
-1.3
-1.9
-2.0
-5
-4.2
-4.6
-6.1
en
Sw
ed
ce
an
pu
Re
Cz
ec
h
Fr
bl
ic
m
iu
lg
nd
la
er
it z
Be
es
Sw
Un
i te
d
St
ng
at
ar
y
el
ra
Hu
rm
Ge
Is
an
y
a
ni
n
pa
to
Es
d
an
el
Ja
m
xe
Lu
Ic
bo
ur
g
nd
la
Ir e
CD
OE
ly
It a
d
an
nl
Fi
li a
ra
Au
st
a in
Sp
Ko
re
a
-10
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526673
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
175
8. LONG-TERM CARE
8.8. Long-term care expenditure
Long-term care (LTC) expenditure has risen over the past
few decades in most OECD countries and is expected to rise
further in the coming years due mainly to population
ageing and a growing number of people requiring health
and social services on an ongoing basis. LTC cuts across the
domains of both health and social care. The component of
LTC that is considered under the health boundary for international comparisons comprises continuous episodes of
care with a dominant characteristic related to medical or
personal care (i.e. support for basic activities of daily living
such as eating, dressing and washing). In contrast, spending on LTC services or programmes associated with helping
people with disabilities to live as independently as possible
(i.e. support for residential services or help with instrumental activities of dailing living, such as preparing meals
or managing personal finances) are considered outside the
scope of medical or personal care and represent the social
component of LTC spending.
A significant share of LTC services is funded from public
sources. In addition, publicly-funded LTC expenditure is
more suitable for international comparisons as there is
significant variation in the reporting of privately-funded LTC
expenditure across OECD countries. Total public spending
on LTC (health and social) accounted for 1.4% of GDP on
average across OECD countries in 2009 (Figure 8.8.1). The
Netherlands and Sweden allocated more than 3.5% of GDP
to public spending on long-term care, while the Czech
Republic, Estonia, Hungary, Korea, Mexico, Poland, Portugal
and the Slovak Republic allocated less than 0.5% of their
GDP. This significant variation reflects both differences in
population structure and in the development of formal
long-term care systems, as opposed to more informal
arrangements based mainly on care giving provided by
unpaid family members.
Keeping in mind the underreporting of privately-funded
LTC expenditure, it plays a relatively larger role in
Switzerland (about 1.3% of GDP) and in the United States
(about 0.4% of GDP).
The international boundaries between health and social
LTC spending are still not fully applied across all countries,
with some countries reporting particular components of
LTC as part of health care, while others view it as a social
spending. As a result, there are important variations in the
level of the health and social-related public LTC spending
among certain OECD countries. The Netherlands, Denmark
and Norway have a public spending on health LTC of over
2% of GDP, with the average being close to 1% of GDP across
OECD countries. Portugal, Mexico and the Slovak Republic
spend less than 0.1% of GDP on the health part of public
LTC. Regarding the social part of public LTC expenditure,
Sweden has the highest share, reaching 3% of GDP, much
greater than the OECD average of 0.6%. In contrast, Poland,
Luxembourg, Spain, New Zealand and Korea report less
than 0.1% of GDP on social public LTC spending.
176
Resources allocated by government to LTC have been
growing rapidly in recent years in several countries and are
a significant factor in the overall growth of health expenditure (Figure 8.8.2). Korea and Spain recently implemented
measures to expand the comprehensiveness of their
LTC systems, showing the highest public spending growth
rate in this area since 2000. For more than half of OECD
countries, the health component of public LTC expenditure
has grown faster than overall public health expenditure
(they fall above the 45° line in Figure 8.8.3). In other
countries however, such as Australia, Canada, Finland,
Sweden and the United States, the health part of public LTC
spending has grown slower than public health expenditure.
Projection scenarios suggest that public resources allocated
to LTC as a share of GDP will at least double by 2050. As a
result, the challenge will be to strike the right balance
between providing appropriate LTC protection, while
ensuring that this protection is fiscally sustainable in the
long run (Colombo et al., 2011).
Definition and comparability
LTC spending comprises both health and social
support services to people with chronic conditions
and disabilities needing care on an ongoing basis.
Based on the agreed-upon definitions in the System
of Health Accounts (SHA), the health component of
LTC spending relates to health care provided to
patients with chronic impairments and assistance
with activities of daily living (ADL, such as eating,
washing and dressing). It includes palliative care and
health care provided in LTC institutions, and health
and personal care services (for ADL) received at home.
LTC social expenditure includes support for residential services in assisted living arrangements and
other kinds of protected housing for persons with
functional limitations; assistance with instrumental
activities of daily living (IADL, such as doing groceries,
preparing meals, managing personal finances and
other services of housekeeping), social services of day
care such as social activities for dependent persons;
transport to and from day-care facilities or similar
social services. Countries’ reporting practices in the
allocation of LTC spending between the health and
social components may differ from the agreed-upon
SHA definition. According to the SHA, only the health
part of LTC expenditure is included in the overall
health expenditure as reported under Chapter 7.
In Figures 8.8.2 and 8.8.3, public LTC expenditure
refers only to the health component of LTC.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
8. LONG-TERM CARE
8.8. Long-term care expenditure
8.8.1 Long-term care public expenditure (health and social components), as share of GDP, 2009 (or nearest year)
Health LTC
% of GDP
4 3.80
Social LTC
3.70
3
2.50
2.20
2.20
2
1.90
1.80
1.70
1.39
1.30
1.30
1.20
1.00
1
1.00
0.91
0.90
0.84
0.84
0.65
0.60
0.43
0.41
0.30
0.30
0.21
0.20
0.09
o
l
M
ex
ic
ga
a
r tu
Po
ic
ni
to
bl
Re
ak
Es
pu
bl
pu
Re
ov
h
0.01
Sl
ec
Cz
Un
ic
y
a
ar
re
ng
nd
Hu
Ko
es
la
at
Po
i te
xe
d
St
g
ur
m
Sp
a in
li a
bo
nd
ra
st
Lu
Au
it z
er
la
en
Sl
ov
Sw
Ne
ia
y
n
an
ria
pa
rm
Ge
Ja
da
st
Au
d
na
Ca
13
w
OE
Ze
al
an
d
an
CD
ce
Ic
el
m
an
iu
Be
lg
rw
No
Fr
d
ay
k
an
ar
nl
Fi
nm
De
ed
la
er
th
Ne
Sw
nd
s
en
0
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526692
8.8.2 Growth in public expenditure
on long-term care (health), 2000-09 (or nearest year)
Korea
Spain
Estonia
Poland
Netherlands
Iceland
Belgium
Japan
France
Czech Republic
Luxembourg
Switzerland
Norway
Slovenia
Denmark
New Zealand
United States
Australia1
Finland
Canada
Austria
Sweden
Portugal
Germany
Hungary
58.6
21.9
18.0
8.8.3 Growth in public expenditure on health
and long-term care (health), 2000-09 (or nearest year)
Average annual growth rate in public
expenditure on LTC (health) (%)
25
7.4
7.3
ESP
7.1
6.4
20
6.0
EST
6.0
5.6
5.3
15
5.2
5.1
4.7
4.5
4.3
10
4.0
3.9
3.5
3.3
5
3.2
3.0
2.9
POL
ISL
NOR
BEL
FRA
CZE
LUX
JPN
CHE
AUS
SVN
USA
DNK
AUT
FIN
PRT
CAN
SWE
NLD
NZL
1.0
DEU
0.2
0
0
10
20
30
40
50
60
Average annual growth rate,
in real terms (%)
1. LTC in hospitals only.
Source: OECD Health Data 2011.
0
5
10
15
20
25
Average annual growth rate in current public
health expenditure, in real terms (%)
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526730
1 2 http://dx.doi.org/10.1787/888932526711
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
177
Health at a Glance 2011
OECD Indicators
© OECD 2011
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HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
189
ANNEX A
ANNEX A
Additional Information on Demographic
and Economic Context, Health System Characteristics,
and Health Expenditure and Financing
Table A.1. Total population, mid-year, thousands, 1960 to 2009
1960
1970
1980
Australia
Austria
Belgium
Canada
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany1
Greece
Hungary
Iceland
Ireland
Israel2
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
10 275
7 048
9 154
18 180
7 643
9 660
4 580
1 216
4 430
45 684
55 585
8 327
9 984
176
2 832
2 150
50 200
93 419
25 012
314
37 877
11 487
2 382
3 581
29 561
8 858
3 994
1 580
30 455
7 485
5 328
27 438
52 371
180 671
12 507
7 467
9 656
21 747
9 570
9 805
4 929
1 365
4 606
50 772
60 651
8 793
10 338
204
2 950
2 958
53 822
103 721
32 241
340
50 785
13 039
2 828
3 876
32 526
8 680
4 529
1 670
33 753
8 043
6 181
35 294
55 633
205 052
14 695
7 549
9 859
24 516
11 174
10 327
5 123
1 473
4 780
53 880
61 566
9 643
10 711
228
3 401
3 878
56 434
117 061
38 124
364
67 384
14 150
3 170
4 086
35 578
9 766
4 984
1 832
37 527
8 311
6 319
44 522
56 331
227 225
OECD (total)
768 937
870 331
965 971
1990
2000
2009
17 065
7 678
9 967
27 698
13 179
10 363
5 141
1 568
4 986
56 709
63 254 
10 161
10 374
255
3 506
4 660
56 719
123 613
42 869
382
83 971
14 952
3 390
4 242
38 031
9 983
5 298
1 927
38 851
8 559
6 712
56 104
57 238
249 623
19 153
8 012
10 251
30 689
15 398
10 273
5 337
1 370
5 176
59 062
82 212
10 918
10 211
281
3 790
6 289
56 942
126 927
47 008
436
98 439
15 926
3 858
4 491
38 256
10 226
5 401
1 985
40 264
8 872
7 184
67 393
58 888
282 166
21 955
8 363
10 797
33 368
16 929
10 492
5 519
1 340
5 339
62 636
81 902
11 283
10 023
319
4 459
7 485
58 947
127 509
48 747
494
107 551
16 418
4 317
4 829
38 153
10 630
5 418
2 020
45 930
9 301
7 744
72 484
60 931
306 656
1 153 084
1 220 287
1 049 028
 Break in series.
1. Note that population figures for Germany prior to 1991 refer to West Germany.
2. Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526749
190
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
ANNEX A
Table A.2. Share of the population aged 65 and over, 1960 to 2009
1960
Australia
1970
1980
1990
2000
2009
8.5
8.3
9.6
11.1
12.4
13.3
Austria
12.2
14.1
15.4
14.9
15.4
17.5
Belgium
12.0
13.4
14.3
14.9
16.8
17.1
Canada
7.5
7.9
9.4
11.3
12.6
13.9
Chile
4.8
5.0
5.5
6.1
7.2
8.8
Czech Republic
9.6
12.1
13.5
12.5
13.8
15.0
Denmark
10.6
12.3
14.4
15.6
14.8
16.1
Estonia
10.5
11.7
12.5
11.6
15.1
17.0
Finland
7.3
9.2
12.0
13.4
14.9
16.9
France
11.6
12.9
13.9
14.0
16.1
16.7
Germany
10.8
13.2
15.5
15.3
16.4
20.5
Greece
8.1
11.1
13.1
13.8
16.6
18.8
Hungary
9.0
11.6
13.4
13.3
15.1
16.5
Iceland
8.1
8.8
9.9
10.6
11.6
11.8
Ireland
11.1
11.1
10.7
11.4
11.2
11.1
Israel1
5.0
6.7
8.6
9.1
9.8
9.8
Italy
9.3
10.9
13.1
14.9
18.3
20.4
Japan
5.7
7.1
9.1
12.1
17.4
22.7
Korea
2.9
3.1
3.8
5.1
7.2
10.7
10.8
12.5
13.6
13.4
14.1
14.0
Mexico
3.4
4.6
4.3
4.1
4.7
5.8
Netherlands
9.0
10.2
11.5
12.8
13.6
15.2
Luxembourg
New Zealand
8.7
8.4
9.7
11.2
11.8
12.8
Norway
11.0
12.9
14.8
16.3
15.2
14.8
Poland
5.8
8.2
10.1
10.1
12.2
13.5
Portugal
7.9
9.4
11.3
13.4
16.2
17.8
Slovak Republic
6.9
9.2
10.5
10.3
11.4
12.2
Slovenia
7.8
9.9
11.4
11.1
14.0
16.2
Spain
8.2
9.6
11.2
13.6
16.8
16.7
Sweden
11.8
13.7
16.3
17.8
17.3
17.9
Switzerland
10.2
11.4
13.8
14.6
15.3
17.2
3.6
4.4
4.7
4.4
5.4
7.6
11.7
13.0
15.0
15.7
15.8
15.8
United States
9.2
9.8
11.3
12.5
12.4
13.0
OECD
8.5
9.9
11.4
12.1
13.5
14.9
Turkey
United Kingdom
1. Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526768
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
191
ANNEX A
Table A.3. GDP per capita in 2009 and average annual growth rates, 1970 to 2009
GDP per capita
in USD PPP
Average annual growth rate (in real terms)
2009
1970-80
1980-90
1990-2000
2000-09
Australia1
39 409
1.3
1.4
2.4
1.7
Austria
38 823
3.5
2.0
2.1
1.0
Belgium
36 287
3.2
1.9
1.9
0.7
Canada
38 230
2.8
1.6
1.9
0.8
Chile
14 131
..
..
4.8
2.5
Czech Republic
25 568
..
..
0.3
3.0
Denmark
37 706
1.9
2.0
2.2
0.1
Estonia
19 882
..
..
..
4.2
Finland
35 237
3.4
2.6
1.7
1.3
France
33 763
3.0
1.9
1.6
0.5
Germany
36 328
2.7
2.1
0.3
0.6
Greece2
28 251
3.6
0.2
1.6
3.9
Hungary
20 280
..
..
..
2.2
Iceland
36 655
5.2
1.6
1.5
1.4
Ireland
39 652
3.3
3.3
6.3
1.1
Israel3
27 495
2.4
1.9
2.8
1.0
Italy
33 105
3.3
2.4
1.5
–0.2
Japan1
33 854
3.2
4.1
0.9
1.1
Korea
27 150
7.2
8.4
5.6
3.5
Luxembourg
85 521
1.9
4.5
3.6
1.6
Mexico
14 322
3.6
–0.4
1.8
0.4
Netherlands
41 085
2.3
1.7
2.5
1.64
New Zealand
28 985
0.6
1.3
1.7
1.4
Norway
55 730
4.1
2.1
3.1
0.9
Poland
18 929
..
..
3.7
3.9
Portugal1
24 953
3.5
3.0
2.7
0.5
Slovak Republic
22 868
..
..
..
4.8
Slovenia
27 829
..
..
1.6
2.7
Spain
32 254
2.5
2.6
2.4
0.8
Sweden
37 155
1.6
1.9
1.7
1.1
Switzerland
45 150
1.0
1.6
0.4
0.7
Turkey1
14 848
1.7
2.8
1.8
3.6
United Kingdom
35 656
1.8
2.6
2.2
1.0
United States
45 797
2.2
2.3
2.2
0.6
OECD
33 320
2.8
2.3
2.3
1.6
1. Most recent year available is 2008.
2. Most recent year available is 2007.
3. Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
4. Most recent year used is 2008.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526787
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HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
ANNEX A
Table A.4. Basic primary health insurance coverage of selected functions of care,
and share of typical costs covered, 2008-09
Australia
Acute inpatient care
Outpatient primary care
and specialist contacts
Pharmaceuticals
Dental care
Covered, 100%
Covered, 76-99%
Covered, 76-99%
Not covered
Austria
Covered, 76-99%
Covered, 100%
Covered, 76-99%
Covered, 100%
Belgium
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Canada
Covered, 100%
Covered, 100%
Covered, 51-75%
Not covered
Covered, 76-99%
Covered, 76-99%
Covered, 51-75%
Covered, 1-50%
Czech Republic
Denmark
Covered, 100%
Covered, 100%
Covered, 51-75%
Covered, 1-50%
Finland
Covered, 76-99%
Covered, 76-99%
Covered, 51-75%
Covered, 76-99%
France
Covered, 76-99%
Covered, 51-75%
Covered, 51-75%
Covered, 1-50%
Covered, 100%
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Covered, 1-50%
Germany
Greece
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Hungary
Covered, 100%
Covered, 100%
Covered, 76-99%
Covered, 1-50%
Iceland
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Ireland
Covered, 100%
Covered, 100%
..
Not covered
Italy
Covered, 100%
Covered, 76-99%
Covered, 100%
Covered, 1-50%
Japan
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Korea
Covered, 76-99%
Covered, 51-75%
Covered, 51-75%
Covered, 51-75%
Luxembourg
Covered, 76-99%
Covered, 76-99%
Covered, 76-99%
Covered, 51-75%
Mexico
Covered, 100%
Covered, 100%
Covered, 100%
Covered, 100%
Netherlands
Covered, 100%
Covered, 100%
Covered, 100%
Covered, 1-50%
New Zealand
Covered, 100%
Covered, 51-75%
Covered, 76-99%
Not covered
Norway
Covered, 100%
Covered, 76-99%
Covered, 76-99%
Not covered
Poland
Covered, 100%
Covered, 100%
Covered, 51-75%
Covered, 100%
Portugal
Covered, 100%
Covered, 100%
Covered, 1-50%
Covered, 1-50%
Slovak Republic
Covered, 100%
Covered, 100%
Covered, 76-99%
Covered, 51-75%
Spain
Covered, 100%
Covered, 100%
Covered, 76-99%
Covered, 100%
Covered, 76-99%
Covered, 76-99%
Covered, 51-75%
Covered, 1-50%
Switzerland
Covered, 100%
Covered, 76-99%
Covered, 76-99%
Not covered
Turkey
Covered, 100%
Covered, 76-99%
Covered, 76-99%
Covered, 100%
United Kingdom
Covered, 100%
Covered, 100%
Covered, 100%
Covered, 76-99%
Sweden
Source: OECD Survey on Health System Characteristics 2008-2009 and OECD estimates.
1 2 http://dx.doi.org/10.1787/888932526806
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
193
ANNEX A
Table A.5. Predominant mode of payment for physicians in OECD countries
Australia
Primary care physicians
Outpatient specialists
Inpatient specialists
Fee-for-service
Fee-for-service
Salary
Austria
Fee-for-service/capitation
Fee-for-service
Salary
Belgium
Fee-for-service
Fee-for-service
..
Canada
Fee-for-service
Fee-for-service
Fee-for-service
Czech Republic
Fee-for-service/capitation
Fee-for-service/salary
Salary
Denmark
Fee-for-service/capitation
Salary
Salary
Finland
Salary
Salary
Salary
France
Fee-for-service
Fee-for-service
Salary
Germany
Fee-for-service
Fee-for-service
Salary
Salary
Fee-for-service/salary
Salary
Hungary
Capitation
Salary
..
Iceland
Salary
Fee-for-service
Salary
Ireland
Capitation/fee-for-service
Fee-for-service
Salary
Capitation
Salary
Salary
Japan
Fee-for-service
Fee-for-service
Fee-for-service
Korea
Fee-for-service
Fee-for-service
..
Luxembourg
Fee-for-service
Fee-for-service
..
Salary
Salary
Salary
Greece
Italy
Mexico
Netherlands
Capitation
Fee-for-service
Fee-for-service
New Zealand
Fee-for-service/salary
Fee-for-service/salary
Fee-for-service/salary
Norway
Fee-for-service/capitation
Fee-for-service/salary
Salary
Poland
Capitation
Fee-for-service
..
Salary
Salary
..
Capitation
..
Salary
Salary/Capitation
Salary
Salary
Salary
Salary
..
Fee-for-service
Fee-for-service
..
Fee-for-service/salary
Fee-for-service/salary
Fee-for-service/salary
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Turkey
United Kingdom
Salary/capitation/fee-for-service
Salary
Salary
United States
Salary/capitation/fee-for-service
Fee-for-service
..
Source: OECD Survey of Health System Characteristics 2008-2009.
1 2 http://dx.doi.org/10.1787/888932526825
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HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
ANNEX A
Table A.6. Total expenditure on health per capita in 2009
and average annual growth rates, 2000 to 2009
Total health expenditure
per capita in USD PPP
2009
Annual growth rate (in real terms)1
2005/06
2006/07
2007/08
2008/09
Average over
period 2000-09
or most recent year
Australia2
3 445
2.6
2.8
1.5
..
2.8
Austria
4 289
1.8
3.3
2.7
2.2
2.2
Belgium3
3 946
–2.6
2.8
4.5
4.2
4.0
Canada
4 363
3.2
1.9
2.5
7.4
3.7
Chile
1 186
–0.8
7.9
11.6
9.0
5.2
Czech Republic
2 108
2.4
2.4
6.8
10.4
5.7
Denmark
4 348
4.7
1.8
0.9
6.0
3.3
Estonia
1 393
10.6
11.8
10.8
–1.1
7.5
Finland
3 226
3.0
1.1
4.3
0.1
4.0
France
3 978
0.9
1.5
0.4
2.7
2.2
Germany
4 218
2.1
1.6
3.2
4.0
2.0
Greece4
2 724
5.3
4.0
..
..
6.9
Hungary
1 511
1.0
–7.0
–2.3
–3.6
2.8
Iceland
3 538
–1.6
3.1
–0.9
–1.4
1.6
Ireland
3 781
1.6
5.1
9.0
–1.0
6.1
Israel5
2 165
0.9
3.0
4.7
0.1
1.5
Italy
3 137
2.3
–2.9
3.6
–0.8
1.6
Japan2
2 878
1.7
2.4
2.6
..
2.4
Korea
1 879
11.9
9.2
4.5
7.2
8.6
Luxembourg
4 808
–0.3
–4.9
–6.9
8.0
0.7
918
0.8
4.2
1.7
2.4
3.1
Netherlands
4 914
2.1
3.3
3.7
..
4.46
New Zealand
2 983
5.9
–1.5
6.2
7.4
4.8
Norway
5 352
–3.5
4.4
–3.4
8.4
2.4
Poland
1 394
6.1
10.8
14.5
6.8
7.3
Portugal2
2 508
–2.0
1.4
0.4
..
1.5
Slovak Republic
2 084
12.9
16.5
9.2
8.2
10.9
Slovenia
2 579
4.0
0.3
11.0
1.7
3.9
Spain
3 067
3.3
3.2
4.9
1.5
4.0
Sweden
3 722
2.4
2.2
2.1
1.8
3.4
Switzerland
5 144
–1.3
1.1
2.0
2.8
2.0
902
12.6
7.4
4.5
..
6.3
United Kingdom
3 487
5.1
1.4
3.6
5.2
4.8
United States
7 960
2.2
2.2
1.6
2.2
3.3
OECD
3 233
3.0
3.2
3.8
3.6
4.0
Mexico
Turkey2
1. Using national currency units at 2000 GDP price level.
2. Most recent year available is 2008.
3. Excluding investments.
4. Most recent year available is 2007.
5. Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
6. Most recent year used is 2008.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526844
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
195
ANNEX A
Table A.7. Public expenditure on health per capita in 2009
and average annual growth rates, 2000 to 2009
Public expenditure
on health per capita
in USD PPP
2009
Annual growth rate (in real terms)1
2005/06
2006/07
2007/08
2008/09
Average over
period 2000-09
or most recent year
Australia2
2 342
2.1
4.2
2.3
..
3.0
Austria
3 331
1.6
3.9
3.7
2.8
2.3
Belgium3
2 964
–5.3
2.3
6.6
4.4
4.1
Canada
3 081
2.6
2.5
2.9
7.6
3.7
562
4.4
10.6
13.6
17.4
4.1
Czech Republic
1 769
1.7
0.6
3.4
12.3
4.9
Denmark
3 698
4.9
1.5
1.3
6.5
3.5
Estonia
1 049
5.6
15.3
14.1
–4.3
7.2
Finland
2 410
2.2
0.5
4.4
0.4
4.6
France
3 100
0.8
1.0
–0.4
3.1
2.0
Germany
3 242
1.8
1.6
3.4
4.5
1.5
Greece4
1 644
8.7
1.2
..
..
7.0
Hungary
1 053
1.3
–9.9
–1.4
–5.4
2.7
Iceland
2 901
–0.9
3.8
–0.8
–2.1
1.7
Ireland
2 836
1.4
5.2
8.8
–3.2
6.1
Israel5
1 266
0.5
1.8
4.9
0.2
0.8
Italy
2 443
2.8
–3.0
4.9
–0.4
2.4
Japan2
2 325
–1.0
3.6
3.2
..
2.4
Korea
1 093
17.0
10.2
4.7
11.5
10.8
Luxembourg
4 040
0.0
–6.0
–7.0
8.0
0.6
443
1.2
4.6
5.1
5.3
3.5
Netherlands
3 884
27.7
2.7
3.8
..
6.76
New Zealand
2 400
6.5
1.4
6.8
7.7
5.2
Norway
4 501
–3.2
4.8
–3.1
8.1
2.6
Poland
1 006
7.0
12.3
16.7
6.7
7.7
Portugal2
1 633
–3.4
0.8
–0.6
..
1.3
Slovak Republic
1 369
3.7
14.0
10.7
4.9
7.2
Slovenia
1 893
4.2
0.3
12.9
1.6
3.9
Spain
2 259
4.4
3.5
6.5
2.9
4.3
Sweden
3 033
2.4
2.5
2.3
1.8
2.9
Switzerland
3 072
–1.8
1.1
2.7
3.1
2.8
659
13.4
6.6
12.4
..
8.3
United Kingdom
2 935
4.3
1.4
4.9
7.5
5.6
United States
3 795
4.1
2.7
3.6
5.8
4.5
OECD
2 354
3.6
3.2
4.8
4.2
4.2
Chile
Mexico
Turkey2
1. Using national currency units at 2000 GDP price level.
2. Most recent year available is 2008.
3. Excluding investments.
4. Most recent year available is 2007.
5. Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
6. Most recent year used is 2008.
Source: OECD Health Data 2011.
1 2 http://dx.doi.org/10.1787/888932526863
196
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
ANNEX A
Table A.8. Total expenditure on health, percentage of GDP, 1980 to 2009
1980
1990
1995
2000
2005
2007
2008
2009
Australia
6.1
6.7
7.2 
8.0
8.4
8.5
8.7
..
Austria
7.4 
8.3
9.5
9.9
10.4
10.3
10.4
11.0
Belgium1
6.3
7.2
7.6
8.1 
10.1
9.7e
10.1
10.9
..
..
6.7
7.2
8.2
8.4
8.4
9.0
7.0
8.9 
9.0
8.8
9.8
10.0
10.3
11.4
Chile
..
..
5.3
6.6
6.9
6.9
7.5
8.4e
China
..
..
3.5
4.6
4.7
4.2
4.3
4.6
4.7 
7.0 
6.5 
7.2
6.8
7.1
8.2
8.3
8.1
8.7 
9.8
10.0
10.3
11.5
7.0
Brazil
Canada
Czech Republic
Denmark
8.9
Estonia
..
..
..
5.3
5.0
5.2
6.1
Finland
6.3
7.7 
7.9
7.2
8.4
8.1
8.4
9.2
France
7.0
8.4 
10.4
10.1
11.1
11.0
11.1
11.8
Germany
8.4
8.3 
10.1
10.3
10.7
10.5
10.7
11.6
Greece
5.9
6.6
8.6 
7.9
9.6
9.6
..
..
7.0 1991
7.3 
7.0 
8.3
7.5
7.2
7.4
Hungary
..
Iceland
6.3
7.8
8.2
9.5 
9.4
9.1
9.1
9.7
India
..
..
4.3
4.6
4.0
4.1
4.2
4.2
Indonesia
..
..
1.8
2.0
2.1
2.5
2.3
2.4
Ireland
8.2 
6.1
6.6
6.1
7.6
7.7
8.8
9.5
Israel2
7.7
7.1
7.6
7.5
7.8
7.6
7.7
7.9
..
7.7
7.3
8.1
8.9
8.7
9.0
9.5
Italy
Japan
6.4
5.9 
6.9
7.7
8.2
8.2
8.5
..
Korea
3.7
4.0
3.8
4.5
5.7
6.3
6.5
6.9
Luxembourg
5.2
7.8
5.4 
5.6 
7.5 
7.9
7.1
6.8
..
4.4
5.1 
5.1
5.9
5.8
5.8
Netherlands
7.4
8.0
8.3
8.0 
9.8
9.7
9.9 
12.0e
New Zealand
5.8
6.8
7.1
7.6 
8.7
8.8
9.6
10.3
Norway
7.0
7.6
7.9 
8.4
9.1
8.9
8.6e
9.6e
Poland
..
4.8
5.5
5.5 
6.2
6.4
7.0
7.4
5.1
5.7 
7.5 
9.3
10.4
10.0
10.1
..
Russian Federation
..
..
5.3
5.4
5.2
5.4
4.8
5.4
Slovak Republic
..
..
5.8 1997
5.5 
7.0
7.7
8.0
9.1
Slovenia
..
..
7.5
8.3
8.4
7.8
8.4
9.3
South Africa
..
..
7.5
8.5
8.8
8.4
8.2
8.5
Spain
5.3
6.5
7.4 
7.2
8.3
8.5
9.0
9.5
Sweden
8.9
8.2 
8.0
8.2 
9.1
8.9
9.2
10.0
Switzerland
7.4
8.2 
9.6
10.2
11.2
10.6e
10.7
11.4
Turkey
2.4
2.7
2.5 
4.9
5.4
6.0
6.1
..
United Kingdom
5.6
5.9
6.8
7.0
8.2
8.4
8.8
9.8
United States
9.0
12.4
13.7
13.7
15.7
16.0
16.4
17.4
OECD
6.6
6.9
7.5
7.8
8.7
8.6
8.8
Mexico
Portugal
6.4
9.63
 Break in series.
e: Preliminary estimate.
1. Excluding investments.
2. Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
3. OECD average calculated on the most recent data available.
Source: OECD Health Data 2011; WHO Global Health Expenditure Database.
1 2 http://dx.doi.org/10.1787/888932526882
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
197
ANNEX B
ANNEX B
Data Sources for Non-OECD Countries
Brazil
Indicators 1.1 and 1.7
World Bank, World Development Indicators and Global Development Finance, online,
www.databank.worldbank.org.
Indicator 1.8
World Bank, Health Nutrition and Population Statistics, online, www.databank.worldbank.org.
Indicators 1.12, 4.4 and 4.9
Ministry of Health /SE/Datasus, Outcare Information System of SUS (SIA/SUS), www.datasus.gov.br.
Indicators 2.1 and 2.3
Ministry of Health (2010), VIGITEL: Vigilância de fatores de riesco e proteção para doenças crônicas
por inquérito telefônico 2009, Brasilia, DF.
Indicator 2.2
WHO, Global Information System on Alcohol and Health, online, www.apps.who.int/ghodata.
Indicators 3.2 and 3.7
Ministry of Health/SGTES/DEGERTS/CONPROF, Professional Councils, www.datasus.gov.br.
Indicator 4.3
Ministry of Health/SAS, National Register of Health Facilities (CNES), www.datasus.gov.br.
Indicator 5.11
WHO, Vaccine-Preventable Diseases Monitoring System, www.who.int/immunization_monitoring/routine/en/.
Indicators 7.1 and 7.2
WHO, Global Health Expenditure Database, www.who.int/nha/database.
China
Indicator 1.1
World Bank, World Development Indicators and Global Development Finance, online,
www.databank.worldbank.org.
Indicators 1.7 and 1.12
Ministry of Health (2011), China Health Statistics Yearbook 2011, Peking Union Medical College Press,
Beijing.
Indicator 1.8
World Bank, Health Nutrition and Population Statistics, online, www.databank.worldbank.org.
Indicator 2.1
WHO, Global Adult Tobacco Survey (GATS), www.who.int/tobacco/surveillance/gats/en/index.html.
Indicator 2.2
WHO, Global Information System on Alcohol and Health, online, www.apps.who.int/ghodata.
Indicator 2.3
Ministry of Health, Ministry of Science and Technology and National Bureau of Statistics (2004),
The Nutrition and Health Status of the Chinese People 2002.
Indicators 3.2, 3.7, 4.3 and 4.4
Ministry of Health (2010), China Health Statistics Yearbook 2010, Peking Union Medical College Press,
Beijing.
Indicator 4.5
Ministry of Health (2010), China Health Statistics Digest 2010, Peking Union Medical College Press, Beijing.
Indicator 4.9
Lumbiganon, P. et al. (2010), “Method of Delivery and Pregnancy Outcomes in Asia: The WHO Global
Survey on Maternal and Perinatal Health 2007-08”, The Lancet, Vol. 375, pp. 490-499.
Indicator 5.11
WHO, Vaccine-Preventable Diseases Monitoring System, www.who.int/immunization_monitoring/routine/en/.
Indicators 7.1 and 7.2
WHO, Global Health Expenditure Database, www.who.int/nha/database.
India
198
Indicators 1.1 and 1.7
World Bank, World Development Indicators and Global Development Finance, online,
www.databank.worldbank.org.
Indicator 1.8
World Bank, Health Nutrition and Population Statistics, online, www.databank.worldbank.org.
Indicator 1.12
UNAIDS (2004), HIV/AIDS Profile, Joint United Nations Programme on HIV/AIDS (UNAIDS), Geneva.
Indicator 2.1
WHO, Global Adult Tobacco Survey (GATS), www.who.int/tobacco/surveillance/gats/en/index.html.
Indicator 2.2
WHO, Global Information System on Alcohol and Health, online, www.apps.who.int/ghodata.
Indicator 2.3
International Institute for Population Science (IIPS), ORC Macro.
National Family Health Survey (NFHS-3), 2005-06.
Indicators 3.2, 3.7 and 4.3
Ministry of Health and Family Welfare, National Health Profile 2010.
Indicator 4.9
Lumbiganon, P. et al. (2010), “Method of Delivery and Pregnancy Outcomes in Asia: The WHO Global
Survey on Maternal and Perinatal Health 2007-08”, The Lancet, Vol. 375, pp. 490-499.
Indicator 5.11
WHO, Vaccine-Preventable Diseases Monitoring System, www.who.int/immunization_monitoring/routine/en/.
Indicators 7.1 and 7.2
WHO, Global Health Expenditure Database, www.who.int/nha/database.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
ANNEX B
Indonesia
Indicators 1.1 and 1.7
World Bank, World Development Indicators and Global Development Finance, online,
www.databank.worldbank.org.
Indicator 1.8
World Bank, Health Nutrition and Population Statistics, online, www.databank.worldbank.org.
Indicators 1.12, 3.2, 3.7, 4.3
and 4.5
Ministry of Health (2010), Indonesia Health Profile 2009.
Indicator 2.1
WHO, Global Infobase, www.infobase.who.int.
Indicator 2.2
WHO, Global Information System on Alcohol and Health, online, www.apps.who.int/ghodata.
Indicator 2.3
Soemantri, S., J. Pradono and D. Hapsari (2001), National Health Survey (Surkesnas) 2001.
National Household Health Survey Morbidity Study, NCD risk factors in Indonesia.
www.who.int/chp/steps/STEPS_Report_Indonesia_National_2001.pdf.
Indicator 5.11
WHO, Vaccine-Preventable Diseases Monitoring System, www.who.int/immunization_monitoring/routine/en/.
Indicators 7.1 and 7.2
WHO, Global Health Expenditure Database, www.who.int/nha/database.
Russian Federation
Indicator 1.1
Federal States Statistical Services (ROSSTAT), Central Statistics Database,
www.gks.ru/dbscripts/Cbsd/DBInet.cgi; and Human Mortality Database (2011)
www.mortality.org or www.humanmortality.de.
Indicators 1.7 and 4.3
Federal States Statistical Services (ROSSTAT), Central Statistics Database,
www.gks.ru/dbscripts/Cbsd/DBInet.cgi.
Indicators 1.8, 1.12, 3.2, 3.7, 4.4,
4.5 and 4.9
WHO-Europe, European Health for All Database (HFA-DB).
Indicator 2.1
WHO, Global Adult Tobacco Survey (GATS), www.who.int/tobacco/surveillance/gats/en/index.html.
Indicator 2.2
WHO, Global Information System on Alcohol and Health, online, www.apps.who.int/ghodata.
Indicator 2.3
Institute of Sociology, Paragon Research International Russian Center for Preventive Medicine, Russian
Institute of Nutrition and State Statistical Bureau, Russian Longitudinal Monitoring Survey (RLMS) 2005.
Indicator 5.11
WHO, Vaccine-Preventable Diseases Monitoring System, www.who.int/immunization_monitoring/routine/en/.
Indicators 7.1 and 7.2
WHO, Global Health Expenditure Database, www.who.int/nha/database.
South Africa
Indicators 1.1 and 1.7
World Bank, World Development Indicators and Global Development Finance, online,
www.databank.worldbank.org.
Indicators 1.8, 4.5 and 4.9
National Department of Health, District Health Information System (DHIS), online.
Indicator 1.12
Actuarial Society of South Africa, ASSA Model 2008.
Indicator 2.1
Health System Trust, www.hst.org.za.
Indicator 2.2
WHO, Global Information System on Alcohol and Health, online, www.apps.who.int/ghodata.
Indicator 2.3
Department of Health, Medical Research Council (2007), ORC Macro, South Africa Demographic and Health
Survey 2003, National Department of Health, Pretoria.
Indicators 3.2 and 3.7
Health Professions Council of South Africa (HPCSA), www.hpcsa.co.za.
Indicator 4.3
Private sector: Wilbury and Claymore, Hospitals Direct Database.
Public sector: National Department of Health, District Health Information System (DHIS), online.
Indicator 5.11
WHO, Vaccine-Preventable Diseases Monitoring System, www.who.int/immunization_monitoring/routine/en/.
Indicators 7.1 and 7.2
WHO, Global Health Expenditure Database, www.who.int/nha/database.
HEALTH AT A GLANCE 2011: OECD INDICATORS © OECD 2011
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(81 2011 10 1 P) ISBN 978-92-64-11153-0 – No. 59039 2011
Health at a Glance 2011
OECD INDICATORS
Contents
OECD 50th Anniversary: Measuring progress in health in OECD countries over the past fifty years
Chapter 1. Health status
Health at a Glance 2011
Chapter 2. Non-medical determinants of health
Chapter 3. Health workforce
OECD INDICATORS
Chapter 4. Health care activities
Chapter 5. Quality of care
Chapter 6. Access to care
Chapter 7. Health expenditure and financing
Chapter 8. Long-term care
Health at a Glance 2011
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