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The economic costs of
heart attack and chest pain
(Acute Coronary Syndrome)
Acknowledgements
Access Economics would like to acknowledge with appreciation the insightful comments and
guidance received from various people in the development of this report, including Professor
Derek Chew, Associate Professor David Brieger, Dr Ren Tan, Jenny Coutts, Margaret Flaherty,
Ineke Bleeker, Dr Alex Brown, Graham Neville, Tony Arvidsson, Rohan Greenland, Dr Andrew
Boyden, Kim Goodman, Debbie White, Associate Professor Paul Middleton, Linda Soars,
members of the Cardiology Advisory Board (Eli Lilly), Dr Deon Gouws, Paul Dale, Stuart Englund
and Fiona Bailey. We would especially like to thank Emeritus Professor Michael Hobbs for
providing access to unpublished research information and advice on the epidemiology of ACS
and its treatment in Perth.
This report aims to enhance the understanding of, and reiterate, the growing impact of Acute
Coronary Syndrome on Australia and the need for every effort to be made to resolve the
treatment gaps.
Copyright
Data relating to the WA linked database supplied by Emeritus Professor Michael Hobbs and
presented in this report are unpublished from research in progress. They may not be provided
to, or published by, third parties without the permission of Professor Michael Hobbs.
To obtain a copy
A copy of ‘The economics costs of heart attack and chest pain (Acute Coronary Syndrome)’ can
be downloaded from www.accesseconomics.com.au/publicationsreports.php
The economic costs of
heart attack and chest pain
(Acute Coronary Syndrome)
June 2009
While every effort has been made to ensure the accuracy of this document, the uncertain nature of
economic data, forecasting and analysis means that Access Economics Pty Limited is unable to make any
warranties in relation to the information contained herein. Access Economics Pty Limited, its employees
and agents disclaim liability for any loss or damage which may arise as a consequence of any person
relying on the information contained in this document.
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Executive Summary
Access Economics was commissioned by Eli Lilly to estimate the economic costs of Heart
Attack and Chest Pain (Acute Coronary Syndrome-ACS) in Australia for 2009. In addition, an
objective was to investigate current gaps in ACS treatment and clinical need, and highlight
areas of treatment where further investment may result in significant benefits through a
reduction in the burden of disease and improvements in efficiency and quality of care.
To estimate the economic costs of ACS, this study has used the comprehensive cost of illness
framework used throughout the world. In brief, the study consists of the following sections:
■
■
■
■
■
epidemiology of ACS in Australia;
direct health care system costs associated with treatment;
indirect financial and economic costs;
value of the loss in health associated with morbidity and mortality; and
the future of ACS management in Australia.
Unless ACS leads to immediate death, patients experiencing an ACS event are hospitalised.
Data on hospitalisations and death were used to estimate the number of ACS events in
Australia. As the Australian Institute of Health and Welfare (AIHW) data does not account for
readmission and transfers, 28 day age standardised separation rates were sourced from the
Western Australian linked dataset with the assistance of Emeritus Professor Michael Hobbs.
These were extrapolated to the Australian setting using projected Australian population data.
It is projected that in 2009 there will be around 79,990 hospitalisation associated with ACS, of
which 59% is expected to be due to heart attack (AMI), and the remaining associated with
chest pain (unstable angina). Table i shows the projected number of hospitalisations by gender
and condition for 2009.
Table i: Projected number of ACS hospitalisations in Australia 2009
Unstable angina
AMI
ACS
20,224
12,228
32,452
28,596
18,943
47,539
48,820
31,170
79,990
Male
Female
Total
Source: Access Economics calculations
Some hospitalisations due to heart attacks are likely to be followed by death. However, deaths
following a hospitalisation are expected to account for only 24% of all deaths associated with
heart attacks. Most deaths will occur before a person can be admitted to hospital. In total, it is
expected that 9,959 people will die from a heart attack in 2009, of which 2,423 are expected to
occur within 28 days of an admission. Projected deaths following a heart attack by gender and
age for 2009 are shown in Table ii.
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table ii: Projected number of deaths following a heart attack in Australia 2009
35–44 years
45–54 years
55–64 years
65–74 years
75–84 years
85 years and over
Total
Males
Females
Total
81
239
478
892
1,905
1,427
5,022
18
44
137
428
1,570
2,741
4,937
99
283
615
1,320
3,475
4,167
9,959
Source: ABS (2003, 2004, 2005, 2006 and 2007) and Access Economics calculations
The projected number of hospitalisations and deaths associated with ACS means the direct
health care system costs, indirect costs, and burden of disease imposed on society will be
significant. Table iii presents a summary of projected hospitalisations, deaths and economic
costs associated with ACS, split into various cost components, for 2009.
It is projected that the number of ACS hospitalisations and deaths will be 87,526 in 2009 with
an associated total economic cost of $17.9 billion. Of this, direct health care system costs
(primarily hospital stays and pharmaceuticals) are expected to account for around $1.8 billion.
Indirect costs are expected to account for $3.8 billion, primarily due to lost productivity. The
largest cost is expected to be the loss in the value of health, otherwise known as the burden of
disease due to morbidity and mortality. It is expected that due to disability imposed on
individuals, and the loss of life associated with premature mortality, the value in the loss of
health will be approximately $12.3 billion in 2009.
In total, heart attacks are expected to cost around $15.5 billion in 2009. The majority of these
costs are associated with the loss in the value of health, accounting for around 78%, which is
representative of the large amount of premature deaths associated with heart attacks. Total
direct health care system costs and indirect costs are expected to total around $3.5 billion in
2009. The total cost per heart attack is expected to average $281,000.
Unstable angina (chest pain at rest) is expected to cost around $2.4 billion in 2009. However
the burden of disease only comprises $311 million, or around 13%. The majority of costs are
associated with direct and indirect costs, totalling around $2.1 billion. The total cost per
unstable angina event is expected to average $74,000.
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table iii: Summary of estimated separations, deaths and costs 2009
Heart attack
Chest pain
ACS
7,536
0
7,536
Hospitalisations without death
Hospitalisations with death occurring later
Total hospitalisations
45,115
2,423
47,538
32,452
0
32,452
77,567
2,423
79,990
Total Events
55,074
32,452
87,526
$ (million)
1,191
1,254
287
411
328
719
11,307
15,497
$ (million)
577
1,073
0
280
159
311
0
2,400
$ (million)
1,767
2,327
287
691
486
1,030
11,307
17,895
$
25,000
$
18,000
$
22,000
281,000
74,000
204,000
Deaths before reaching a hospital
a
Direct health care system costs
Productivity loss (reduced participation)
Productivity loss (premature mortality)
Informal care
Deadweight loss
Burden of disease (YLD)
Burden of disease (YLL)
Total costs
Cost per separation (direct costs only)
Cost per event (all costs)
b
b
Note: (a) Within 28 days of being admitted to hospital (b) Cost per hospitalisation and cost per event have been
rounded to the nearest $1,000. Source: Access Economics
This study has also highlighted gaps in the treatment and monitoring of ACS throughout
Australia. These include:
a national ACS registry managed by an independent body that includes comprehensive
and consistent data on patients, treatment, and rehabilitation services Australia-wide;
which can be used to develop a common set of performance indicators and ACS
treatment outcome measures;
a national approach to cardiac rehabilitation, including inpatient, outpatient and
maintenance care, specific strategies to increase the uptake of women into
rehabilitation, further investment to ensure rehabilitation programs are accessible to
all regardless of income and geographical location;
an increase in the compliance and adherence with medication via the Quality Use of
Medicines program;
a standardised national program to support employees and employers and the
extension of rehabilitation practices. Workplaces can provide an excellent
environment to facilitate the ongoing rehabilitation and lifestyle changes to prevent
the re-occurrence of ACS events; and
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
further research into the optimal use of existing therapies and identification and
promotion of cost effective treatments currently being used within other health
systems throughout the world.
The focus on ACS at this point in time is particularly important in the context of demographic
ageing in Australia, given the increasing age standardisation rates among the older population
and the link between health, health care resource utilisation, and quality of life. In 2010, the
first of the baby boomers will reach the age of 65 years, where the risk of ACS significantly
increases. It is expected that the proportion of the Australian population that is 65 years and
older (and therefore at higher risk of an ACS event) will increase from around 14% in 2009 to
around 23% in 2050. This, coupled with the expected increase in risk factors associated with
ACS such as obesity and diabetes, means public and private health care resources to prevent
and treat ACS are expected to come under significant pressure in the near future.
To mitigate these pressures, investment in cost effective programs should be undertaken now
to improve effectiveness and efficiency of ACS treatment in the future. The first step should be
to invest in the collection and dissemination of information and data associated with
treatment across Australia at a local level. Informed analysis should then be undertaken to
identify differences in treatment paths, to determine optimal therapies, and to inform best
practice.
The goal of ACS management should be to shift resources to cost effective technologies,
thereby improving the efficiency of ACS treatment and generating greater health benefits for
the Australian community. To ensure any gains made in the hospital are not undone once the
patient steps out the hospital door, monitoring of health outcomes, individual behaviours, and
the effectiveness of rehabilitation also needs to be measured, continually monitored and
supported.
Access Economics
June 2009
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Contents
Executive Summary.......................................................................................................................4
1
2
3
4
The epidemiology of ACS in Australia ............................................................................... 12
1.1
Definition of ACS .................................................................................................................. 12
1.2
Development of ACS ............................................................................................................ 14
1.3
Risk factors and comorbidity associated with ACS .............................................................. 15
1.4
Projected number of ACS events in Australia ...................................................................... 23
1.5
Impact of demographic ageing ............................................................................................ 36
Direct health care system costs ........................................................................................ 39
2.1
Methodology........................................................................................................................ 39
2.2
Direct health care system costs ........................................................................................... 40
2.3
Trends in direct health care system costs ............................................................................ 44
2.4
Direct health care system cost per separation .................................................................... 45
Indirect costs associated with ACS.................................................................................... 47
3.1
Productivity losses ............................................................................................................... 47
3.2
Cost of informal care ............................................................................................................ 50
3.3
Private costs associated with rehabilitation ........................................................................ 52
3.4
Deadweight loss associated with public funding of health care .......................................... 52
Burden of disease ............................................................................................................. 54
4.1
Methodology used for measuring and valuing the burden of disease ................................ 54
4.2
Burden of disease from ACS ................................................................................................. 55
4.3
Burden of disease comparisons ........................................................................................... 57
5
Summary of costs .............................................................................................................. 58
6
The future of ACS management........................................................................................ 59
6.1
A multidisciplinary approach to ACS care ............................................................................ 59
6.2
A national ACS registry ......................................................................................................... 60
6.3
Rehabilitation ....................................................................................................................... 62
6.4
Next generation antiplatelet agents .................................................................................... 65
Appendix A: Epidemiology estimates and projections................................................................ 69
References................................................................................................................................... 76
Charts
Chart 1.1 : Share of CHD deaths by risk factors 2003 ................................................................ 17
Chart 1.2 : Share of CHD DALYs by risk factors 2003 ................................................................. 17
Chart 1.3 : Risk of AMI associated with exposure to multiple risk factors................................. 18
Chart 1.4 : Reduced risk of AMI associated with healthy behaviour ......................................... 18
Chart 1.5 : Trends in daily smoking for those aged 14 years and over ...................................... 19
Chart 1.6 : Prevalence of overweight and obese people in Australia ........................................ 20
Chart 1.7 : Trend in blood pressure amongst Australians aged 25 to 64 ................................... 21
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.8 : Trends in diabetes within Australia .......................................................................... 22
Chart 1.9 : Actual and projected age standardised separation rates for AMI ........................... 26
Chart 1.10 : Actual and projected age standardised separation rates for unstable angina ...... 26
Chart 1.11 : Actual and projected age standardised separation rates for ACS .......................... 27
Chart 1.12 : Projected age standardised separation rates by condition 2009 ........................... 28
Chart 1.13 : Projected age standardised separation rates for ACS 2009 ................................... 28
Chart 1.14 : Comparison of projected ACS separations in Australia 2009 ................................. 30
Chart 1.15 : Projected male separations in Australia 2009 ........................................................ 31
Chart 1.16 : Projected female separations in Australia 2009..................................................... 32
Chart 1.17 : Projected total separations in Australia by condition 2009 ................................... 32
Chart 1.18 : Projected total separations in Australia by gender 2009 ....................................... 33
Chart 1.19 : Share of AMI and angina pectoris across states and territories 2006-07 .............. 34
Chart 1.20 : 28 day case fatality following AMI.......................................................................... 35
Chart 1.21 : Actual and projected deaths following AMI Australia ............................................ 36
Chart 1.22 : Projected Australian population age structure ....................................................... 37
Chart 1.23 : Projected ACS separations in Australia .................................................................. 38
Chart 2.1 : Distribution of direct health care system costs of ACS 2009 ................................... 42
Chart 2.2 : Direct health care system costs of ACS by expenditure type 2009 .......................... 43
Chart 2.3 : Direct health care system costs of AMI by expenditure type 2009 ......................... 43
Chart 2.4 : Direct health care system costs of unstable angina by expenditure type 2009....... 44
Chart A.1: Male AMI separation rates and trends ...................................................................... 71
Chart A.2: Female AMI separation rates and trends................................................................... 72
Chart A.3: Male unstable angina separation rates and trends ................................................... 72
Chart A.4: Female unstable angina separation rates and trends ................................................ 73
Tables
Table 1.1 : Definition of ACS used in this study.......................................................................... 14
Table 1.2 : Prevalence distributions for seven lifestyle risk factors by age and sex 2003 ......... 16
Table 1.3 : ACS age standardised separations per 100,000 in the Perth Statistical Division ..... 24
Table 1.4 : Projected deaths following AMI by age bracket Australia 2009 .............................. 36
Table 2.1 : Projected direct health care system costs by age and gender 2009 ........................ 41
Table 2.2 : Projected direct health care system costs, by expenditure type 2009 .................... 42
Table 2.3 : Patient days associated with unstable angina and AMI ........................................... 45
Table 2.4 : Trend in direct health care system costs associated with ACS.................................. 45
Table 2.5 : Direct health care system costs per separation 2009 ............................................... 46
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 3.1 : Productivity loss due to premature death 2009....................................................... 49
Table 3.2 : Productivity loss due to working days lost 2009 ...................................................... 50
Table 4.1 : Value of YLDs associated with ACS 2009 .................................................................. 56
Table 4.2 : YLLs from ACS 2009 .................................................................................................. 56
Table 4.3 : Burden of disease in Australia 2009 ......................................................................... 57
Table 5.1 : Summary of separations, deaths and costs 2009 ..................................................... 58
Table 6.1 : Factors that impact on health and health outcomes ................................................ 61
Table 6.2 : Recommended medications for ACS treatment........................................................ 64
Table 6.3 : Status of new antiplatelet agents ............................................................................. 67
Table A.1: Male AMI age standardised separations per 100,000 ............................................... 69
Table A.2: Female AMI age standardised separations per 100,000............................................ 69
Table A.3: Male unstable angina age standardised separations per 100,000 ............................ 70
Table A.4: Female unstable angina age standardised separations per 100,000......................... 70
Table A.5: Male ACS age standardised separations per 100,000 ................................................ 70
Table A.6: Female ACS age standardised separations per 100,000 ............................................ 71
Table A.7: Actual and projected ACS separation rates for males ............................................... 74
Table A.8: Actual and projected ACS separation rates for females ............................................ 75
Figures
Figure 1.1 : Defining ACS over time ............................................................................................ 13
Figure 6.1 : A model of care for rehabilitation ............................................................................ 63
Figure 6.2 : Signalling pathways that activate platelets ............................................................. 67
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Glossary
ABS
Australian Bureau of Statistics
ACE
Angiotensin-converting enzyme
ACS
Acute coronary syndrome
AIHW
Australian Institute of Health and Welfare
AMI
Acute myocardial infarction
BMI
Body Mass Index
CHD
Coronary heart disease
CRA
Comparative risk assessment
CVD
Cardiovascular disease
DALY
Disability adjusted life year
DBP
Diastolic blood pressure
DoFD
Department of Finance and Deregulation
DoHWA
Department of Health Western Australia
DWL
Deadweight loss
ECG
Electrocardiogram
ESC-ACC
European Society of Cardiology and the American College of
Cardiology
EMS
Emergency medical services
GBD
Global Burden of Disease
IHD
Ischemic heart disease
LLA
Lipid-lowering agents
NHMRC
National Health and Medical Research Council
NSTEACS
Non-ST-segment elevation acute coronary syndrome
NSTEMI
Non-ST-segment elevation myocardial infarction
PBAC
Pharmaceutical Benefits Advisory Committee
PCI
Percutaneous coronary intervention
QALY
Quality-adjusted life year
SBP
Systolic blood pressure
STEMI
ST-segment elevation infarction
TRA
Thrombin receptor antagonist
VSLY
Value of a statistical life year
YLD
Years of health life lost due to disability
YLL
Years of healthy life lost due to premature death
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Definitions
Acute coronary syndrome
An umbrella term for conditions resulting from sudden
insufficient blood supply to the heart. These include chest
pain (unstable angina) and heart attack (AMI).
Acute myocardial infarction
A sudden insufficient blood supply to the heart muscle
(myocardium) occurring because of blocked or narrowed
arteries. Shown on an ECG as a Non-ST-segment elevation
myocardial infarction (NSTEMI) or a ST-segment elevation
myocardial infarction. A heart attack.
Angina pectoris
The medical term for chest pain that is due to coronary
heart disease. It is a symptom of acute myocardial
infarction. Described as uncomfortable pressure in the
centre of the chest. Manifested as stable angina or unstable
angina.
Burden of disease
The impact of a disease or condition on the health and
mobility of an individual.
Deadweight loss
Inefficiencies created in the economy through distortions
created by increased taxes to fund public health care.
Direct health care system costs
Public and private costs directly associated with the
provision of health care.
Event
The occurrence of unstable angina or AMI. It can include a
separation, death, or separation and death.
Health capital
The stock of human capital that produces health. This can
depreciate with age and ill health, or increase with
investment (such as exercise).
Indirect costs
Costs to the economy associated with flow on effects from
reduced health and mobility, such as productivity loss and
informal care costs.
Myocardial infarction
Reduced blood flow causing damage to the heart muscle.
Heart attack.
Separation
An admitted patient episode of care. A period of
hospitalization.
Separation rate
The number of separations compared to the number of
individuals within the relevant population.
Stable angina
Chest pain and discomfort that is instigated by stress or
exercise, most commonly caused when the heart is working
hard, but not getting enough blood and oxygen.
A blood clot that forms inside a blood vessel or cavity of the
heart.
Reduced blood flow to the heart muscle causing severe
chest pain but without damage to the heart muscle. It is
usually unexpected and usually occurs at rest.
Thrombus
Unstable angina
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
1
The epidemiology of ACS in Australia
Coronary heart disease (CHD) (also known as ischemic heart disease) is one of the major
causes of morbidity in Australia and the largest single cause of death, accounting for around
23,570 deaths in 2005 (AIHW 2007; 2008). It is associated with significant cost to the health
care system, individuals, and society in general (Access Economics 2005).
Acute coronary syndrome (ACS) is a sub-group of CHD and is associated with unstable angina
and acute myocardial infarction (AMI). It includes clinical presentations that span ST-segmentelevation1 myocardial infarction to an accelerated pattern of angina without evidence of
necrotic damage to the heart muscle (myonecrosis) (Chew et al 2005).
The common underlying cause of ACS is a build up of cholesterol plaque on the inside of the
arteries of the heart muscle (known as atherosclerosis), causing the muscle cells to enlarge and
form a hard cover over the area. This narrows the artery, reducing blood supply (and hence
oxygen) to the heart. Under normal conditions blood flow may still be adequate but may be
insufficient when an elevated blood flow is required (for example, through exercise). This is
known as stable angina and is not considered part of ACS.
However, if the plaque ruptures from the artery wall it can cause a blood clot within the artery,
significantly reducing blood flow or completely blocking blood flow to the heart muscle. This
can cause the sudden onset of angina (unstable angina) leading to severe chest pain and
potential damage to the heart muscle (acute myocardial infarction). Death can occur if blood
flow is not quickly restored to the heart muscle through the use of drugs or catheter
procedures.
1.1 Definition of ACS
ACS is defined across a range of acute myocardial ischemic states. It encompasses unstable
angina, non-ST-segment elevation myocardial infarction (NSTEMI), and ST-segment elevation
myocardial infarction (STEMI) (Grech and Ramsdale 2003a).
Figure 1.1 shows the definition of ACS components over time. An initial electrocardiogram
(ECG) is conducted to determine whether ST-segment-elevation is present. If at a hospital,
myocardial biomarker levels will also be tested. The ECG results and the myocardial biomarker
levels will determine the diagnosis and the treatment path. If STEMI is present on the ECG,
patients are diagnosed as having an AMI (heart attack) requiring urgent reperfusion. If ST
elevation is not present, then patients may be diagnosed as having a NSTEMI (if biomarkers are
elevated) or unstable angina (if biomarkers are not elevated).
1
Recording of electrical activity of the heart over time using an electrocardiograph
12
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Figure 1.1: Defining ACS over time
Source: Aroney et al (2006)
For the purposes of this study, ACS is defined as patients that are diagnosed with unstable
angina and AMI. Referring to the World Health Organisation (WHO) ICD-10 codes, ACS
incorporates I20.0 for unstable angina (a sub-set of angina pectoris) and all sub-sets within I21
(WHO 2007). These are outlined in more detail in Table 1.1.
13
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 1.1: Definition of ACS used in this study
ICD-10
Group
Sub-group
I20.0
Unstable angina
Angina:
Crescendo
De novo effort
Worsening effort
Intermediate coronary syndrome
Preinfarction syndrome
I21.0
Acute transmural myocardial
infarction of anterior wall
Transmural infarction (acute) (of):
Anterior (wall) NOS
Anteroapical
Anterolateral
Anteroseptal
I21.1
Acute transmural myocardial
infarction of inferior wall
Transmural infarction (acute) (of):
Diaphragmatic wall
Inferior (wall) NOS
Inferolateral
I21.2
Acute transmural myocardial
infarction of other sites
Transmural infarction (acute) (of):
Apical-lateral
Basal-lateral
High lateral
Lateral (wall) NOS
Posterior (true)
Posterobasal
Posterolateral
Posteroseptal
Septal NOS
I21.3
Acute transmural myocardial
infarction of unspecified site
Transmural myocardial infarction NOS
I21.4
Acute subendocardial myocardial
infarction
Nontransmural myocardial infarction NOS
I21.9
Acute myocardial infarction,
unspecified
Myocardial infarction (acute) NOS
Notes: (a) Includes: myocardial infarction specified as acute or with a stated duration of 28 days or less from onset.
Excludes: certain complications following AMI: I25.2, I25.8, I22-I24.1.
Source: WHO (2007)
1.2 Development of ACS
ACS begins with a fracture in the protective fibrous cap of an atheromatous plaque (Libby
2001). When these plaques fissure or rupture and core constituents such as lipid, smooth
muscle and foam cells are exposed, it leads to the local generation of thrombin and deposition
of fibrin (Grech and Ramsdale 2003a). This promotes platelet aggregation and adhesion and
the formation of intracoronary thrombus (Grech and Ramsdale 2003b). Downstream
14
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
embolisation from friable coronary thrombus may occur, leading to focal cell necrosis and the
release of cardiac troponins (Heeschen et al 1999).
STEMI usually occurs when thrombus forms on a ruptured atheromatous plaque and blocks an
epicardial coronary artery. Patient survival depends on several factors, the most important
being restoration of blood flow, the time taken to achieve this, and the sustained patency of
the affected artery (Grech and Ramsdale 2003b). NSTEMI is a form of myocardial infarction
and these types of patients differ from STEMI only through the absence of ST elevation on the
presenting ECG.
Although there is no universally accepted definition of unstable angina, it has been described
as a clinical syndrome between stable angina and AMI (Grech and Ramsdale 2003a). Unstable
angina can be recognised by ischemic-type chest pain that is more frequent, severe or
prolonged than the patient’s usual angina symptoms, occurs at rest or minimal exertion, or is
difficult to control with drugs. Recent onset angina is also classified as unstable (Maynard et al
2000).
1.3 Risk factors and co-morbidity associated with ACS
Most known risk factors of ACS can be reduced by specific preventative methods such as
pharmacotherapy and lifestyle changes (Patel and Adams 2008). These include smoking, high
blood cholesterol, physical inactivity, diabetes, high blood pressure, being overweight or
obese, and depression and social isolation (Heart Foundation 2009). However, there are also
some risk factors of ACS that cannot be reduced, namely age, gender (being male) and a family
history of coronary heart disease (Heart Foundation 2009).
As part of the Global Burden of Disease (GBD) Study, the World Health Organization (WHO)
developed a method for ‘risk quantification’ to assess the health implications of certain risk
exposures and provide a degree of conceptual and methodological consistency and
comparability across risk factors (Ezzati et al 2004). Using this methodology, which was
established as part of the Comparative Risk Assessment (CRA) study, Vos and Begg (2007)
determined that seven risk factors explain 81.5% of CHD deaths and 85.2% of CHD disability
adjusted life years (DALYs).2 Although their study did not specifically focus on ACS, unstable
angina and AMI make up around 57% of Australian separations associated with CHD.3 As such,
risk factors associated with CHD outlined by Vos and Begg (2007) can be used as a good proxy
for ACS.
Table 1.2 provides the prevalence distributions of the seven modifiable risk factors recognised
by the WHO’s CRA study as having an impact on the prevalence of CHD. Blood pressure,
cholesterol, Body Mass Index (BMI) and fruit and vegetable intake are reported at their mean
levels (and standard deviations) in the Australian population. Physical inactivity, tobacco and
alcohol are provided as the percentage of the Australian population that falls into each
category.
2
A DALY is a summary measure of health developed as the measurement unit to quantify fatal and non-fatal health
outcomes, labelled the burden of disease and injury, on populations around the world for the Global Burden of
Disease Study (Murray and Lopez, 1996). DALY weights are measured on a scale of zero to one, where a zero
represented a year of perfect health and one represented death. Other health states associated with specific
conditions are attributed values between zero and one. For example, a DALY weight of 0.238 for unstable angina
means a patient who has unstable angina has lost 23.8% of their total health.
3
Derived from http://d01.aihw.gov.au/cognos/cgi-bin/ppdscgi.exe?DC=Q&E=/ahs/pdx0607, accessed 03 April 2009
15
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 1.2: Prevalence distributions for seven lifestyle risk factors by age and sex 2003
15-29
Blood
Pressure
(mmHg)
Cholesterol
(mmol/L)
BMI
2
(kg/m )
Fruit and
vegetable
intake
(g/day)
Physical
inactivity
(%
population)
Tobacco (%
population)
Alcohol (%
population)
30-44
45-59
60-69
70-79
80+
M
F
M
F
M
F
M
F
M
F
M
F
Mean
-
-
124
115
131
126
140
138
148
146
154
150
SD
-
-
11
12
16
17
17
19
19
22
19
21
Mean
-
-
5.5
5.2
5.8
5.8
5.6
6.0
5.6
6.1
5.3
5.9
SD
-
-
1.0
1.0
1.1
1.1
0.9
0.9
0.9
1.0
1.0
1.0
Mean
-
-
26.8
25.4
27.5
27.2
27.2
28.5
27.1
27.0
25.8
24.9
SD
-
-
4.1
5.4
4.0
5.7
3.7
5.8
3.8
5.2
3.5
4.5
Mean
445
484
452
506
496
569
538
602
538
577
538
577
SD
241
237
235
228
245
240
230
234
219
217
219
217
Vig
10
4
3
2
3
1
1
1
1
0
0
0
Mod
47
37
37
32
37
35
41
38
44
27
30
17
Insuff
23
35
29
38
29
33
26
28
22
28
21
24
Inact
20
25
31
28
32
30
33
33
33
45
49
59
Smoker
-
-
31
25
23
18
16
12
9
9
7
2
Nonsmoker
-
-
69
75
77
82
84
88
91
91
93
98
Abstain
38
59
36
59
33
59
47
68
52
76
61
73
Low
50
34
50
31
53
32
41
24
41
19
37
21
Hazard
6
5
6
6
7
7
7
7
4
4
1
1
Harmful
6
2
7
3
7
2
5
1
3
1
1
4
Note: Vig = Vigorous, Mod = Moderate, Insuff = Insufficient, Inact = Inactive, Hazard = Hazardous Source: Vos and
Begg (2007)
The relative impact of each of the seven risk factors on CHD deaths and DALYs are illustrated in
Chart 1.1 and Chart 1.2 respectively.4 Blood pressure and cholesterol levels have the greatest
influence on the number of deaths attributable to CHD, and alcohol and tobacco have the
lowest. In contrast, cholesterol levels and blood pressure also have the most significant impact
on DALYs, but tobacco and low fruit and vegetable intake have the smallest effect.
4
The actual percentages are reported in the sections below.
16
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.1: Share of CHD deaths by risk factors 2003
Blood Pressure
Cholesterol
BMI
Low fruit and vegetable
Physical inactivity
Tobacco
Alcohol
Source: Vos and Begg (2007) and Access Economics calculations
Chart 1.2: Share of CHD DALYs by risk factors 2003
Blood Pressure
Cholesterol
BMI
Low fruit and vegetable
Physical inactivity
Tobacco
Alcohol
Source: Vos and Begg (2007) and Access Economics calculations
Similar findings on the contribution of risk factors to CHD morbidity and mortality presented in
Vos and Begg (2007) have been found throughout the world. In a study on potentially
modifiable risk factors associated with AMI in 52 countries (including developed and less
developed countries), Yusuf et al (2004) found that tobacco consumption and high cholesterol
were the two strongest risk factors, followed by psychosocial factors, abdominal obesity,
history of hypertension, and history of diabetes. Daily consumption of fruit and vegetables,
moderate to strenuous exercise and consumption of alcohol more than three times per week
reduced the risk of AMI. The odds ratio associated with exposure to multiple risk factors and
17
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
the reduction in risk associated with healthy activities from the study are shown in Chart 1.3
and Chart 1.4 respectively.
Chart 1.3: Risk of AMI associated with exposure to multiple risk factors
Note: Smk = Smoking, DM = diabetes mellitus, HTN = hypertension, Obes = Abdominal obesity, PS = Psychosocial,
RF = Risk factors. The odds ratios are based on current vs never smoking, top vs lowest tertile for abdominal obesity,
and top vs lowest quintile for ApoB/ApoA1.
Source: Yousef et al (2004)
Chart 1.4: Reduced risk of AMI associated with healthy behaviour
Note: Smk = Smoking, Fr/vg = fruits and vegetables, Exer = Exercise, Alc = Alcohol. Odds ratios are adjusted for all
risk factors
Source: Yousef et al (2004)
18
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
1.3.2
Tobacco consumption
Tobacco consumption, particularly the human carcinogens and other toxic properties inhaled
through cigarette smoking, is causally related to an increased risk in mortality from many
medical conditions, including CHD (Ezzati and Lopez 2004). This link has also been established
in reverse, with the risk of AMI and death from CHD decreasing by half one year after quitting,
and, after several years, approaching that of non-smokers (Patel and Adams 2008). Vos and
Begg (2007) estimated that tobacco consumption accounts for 1.5% of CHD deaths and 1.2% of
CHD DALYs in Australia.
The smoking rate for the Australian population has been steadily declining within the last 50
years. More recently, between 1985 and 2007 the prevalence of daily smoking declined by
around 15% and 11% for males and females respectively (AIHW 2008b). Trends in daily
smoking for those aged 14 years and over are shown in Chart 1.5. In 2006, Australia had the
second lowest prevalence rate of smoking amongst OECD (Organisation for Economic
Cooperation and Development) countries at 16.8%, the lowest being Sweden (AIHW 2008b).
Chart 1.5: Trends in daily smoking for those aged 14 years and over
Source: AIHW (2008b)
1.3.3
High cholesterol
Cholesterol is a fat-like substance produced by the body which is found in the blood stream
and all other parts of the bodies including organs and nerve fibres. Most cholesterol in the
body is made by the liver from a variety of foods, but especially from saturated fats. The main
factors that can influence an individual’s level of cholesterol include a diet high in saturated fat
content, heredity, and various metabolic conditions such as type II diabetes (Lawes et al
20024b).
Cholesterol is thought to accelerate atherosclerosis, and thus influence CHD. However, the
exact process remains uncertain. Clear and consistent positive associations between CHD and
cholesterol level have been observed in cohort studies, and clinical trials of cholesterol
lowering treatments have provided evidence of reversibility (Lawes et al 2004b).
19
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Cholesterol is defined as total serum cholesterol expressed in millimoles per litre of blood
(mmol/L). Vos and Begg (2007) estimate that high cholesterol accounts for 10.1% of CHD
deaths and 5.3% of CHD DALYs in Australia. Average blood cholesterol levels of adults aged
between 25 and 64 years were relatively unchanged between 1980 and 2000 (AIHW 2008b).
1.3.4
Body mass index
The body mass index (BMI) provides a general relationship between weight and health (James
et al 2004). Excessive body-weight gain results in abnormalities in blood lipids, leading to an
increased risk of developing CHD. In particular, the distribution of body fat appears to be an
important determinant of the risk of coronary disease and death as patients with abdominal
obesity experience the greatest risk (Krauss and Winston 1998). Vos and Begg (2007)
estimated that elevated BMI accounted for 3.7% of CHD deaths and 2.5% of CHD DALYs in
2003.
The prevalence of overweight and obese people in Australia continues to increase. In 2004-05
around 2.5 million adults were obese and a further 4.9 million were estimated to be
overweight but not obese (AIHW 2008a). This means around 7.4 million people were
estimated to have been above the BMI associated with healthy weight.
Trends in overweight and obesity prevalence between 1995 and 2004-05 are shown in Chart
1.6. In nearly every age bracket there has been a steady increase in the prevalence of
overweight and obese people in Australia.5 A recent study on adults attending general practice
shows that the prevalence of overweight and obese people in Australia has increased from
51% in 1998-99 to 58.5% in 2006-07 (AIHW 2008b).
Chart 1.6: Prevalence of overweight and obese people in Australia
Source: AIHW (2008a)
5
Prevalence of overweight and obese people aged between 65 and 74 years decreased slightly between 2001 and
2004-05.
20
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
1.3.5
Hypertension
It is generally accepted that blood pressure plays a significant role in accelerating
atherosclerosis of the blood vessels and thereby increasing the risk of cardiovascular disease
(Lawes et al 2004a). A variety of prospective cohort studies and overviews have demonstrated
a strong, continuous temporal association between blood pressure and CHD (APCSC 2003;
MacMahon and Rodgers 1993).
The standard unit for measuring blood pressure is mmHg and each 10mmHg below-usual SBP
is associated with a 26% (95% confidence interval of 24-29%) lower risk of CHD (Lawes et al
2004a). According to Vos and Begg (2007), high blood pressure accounts for 10.7% of CHD
deaths and 4.8% of CHD DALYs in Australia when analysed independently from the other risk
factors.
In recent years blood pressure amongst Australians has been trending down. AIHW (2008b)
notes that the prevalence of high blood pressure in males and females aged between 25 and
64 years has more than halved. This is shown in Chart 1.7.
Chart 1.7: Trend in blood pressure amongst Australians aged 25 to 64
Source: AIHW (2008b)
1.3.6
Diabetes
Diabetes mellitus is a chronic metabolic disease resulting from reduced levels of insulin in the
blood, or through ineffective insulin. The consequence is a high level of glucose in the blood
that can lead to a number of conditions, including CHD.
People with diabetes are much more likely to have disability from cardiovascular disease than
those without diabetes (Franklin et al 2004). According to Vos and Begg (2007), diabetes
accounts for around 0.6% of the disability associated with CHD and 3.6% of the years of
healthy life lost. Furthermore, around 2.1% of the total burden of disease associated with CHD
was attributed to diabetes.
21
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
The prevalence of diabetes in Australia has increased significantly in the last 20 years. Based on
National Health Survey, prevalence has increased from around 1.3% of the population in 198990 to 3.4% in 2004-05 (AIHW 2008b). This equates to around 700,000 Australians with diabetes
in 2004-05. Given the trends in the number of people with diabetes and the growth in the
highest risk age bracket (65-74 years) due to demographic ageing, prevalence of diabetes
could increase significantly in the future, with subsequent impacts on the incidence of ACS.
Trends in the prevalence of diabetes are shown in Chart 1.8.
Chart 1.8: Trends in diabetes within Australia
Source: AIHW (2008b)
1.3.7
Alcohol
Alcohol consumption is linked to long-term biological and social consequences through three
outcomes: intoxication, dependence and direct biochemical effects. The direct biochemical
effects can influence IHD in both a beneficial and harmful way. Moderate alcohol consumption
reduces plaque deposits in arteries, promotes blood clot dissolution and protects against blood
clot formation (Zakhari 1997). On the other hand, alcohol increases the risk of high blood
pressure (Apte et al 1997) and hormonal disturbances (Emanuele and Emanuele 1997).
Consequently, when estimating the burden of alcohol consumption, the overall deaths
attributable to alcohol is an underestimation of the true relationship between alcohol
consumption and IHD (Rehm et al 2004). Vos and Begg estimated that the net impact of
alcohol consumption accounts for 0.8% of CHD deaths and 2.3% of CHD DALYs.
1.3.8
Fruit and vegetable intake
Studies have found that fruit and vegetables provide a protective effect against ischemic heart
disease (IHD) (Law and Morris 1998; Ness and Powles 1997). In particular, numerous studies
have consistently shown that individuals who eat more fruits and vegetables have a reduced
risk of AMI (Rimm et al 1996).
The mean dietary intake of fruit and vegetables (excluding potatoes) is estimated to be
600g/day in adults, 480g/day in children aged 5 to 14 years, and 330g/day in children aged 0 to
22
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
4 years (Lock et al 2004). Vos and Begg (2007) estimated that low fruit and vegetable
consumption accounts for 2.4% of CHD deaths and 1.4% of CHD DALYs in Australia.
1.3.9
Physical activity
The apparent protective effect of being more active has been extensively documented with a
significant amount of literature quantifying and qualifying the role of physical inactivity as a
risk factor of CHD (Bull et al 2004). There is evidence of a strong inverse correlation of leisure
time activity and energy expenditure, habitual exercise and fitness with risk of coronary
disease and death (Patel and Adams 2008). The effect appears to be proportional to energy
expenditure; the greater the degree of physical activity the lower the risk of coronary events.
Vos and Begg (2007) estimated that physical inactivity accounts for 6.6% of CHD deaths and
3.4% of CHD DALYs in Australia.
Data from the National Health Surveys for 1995, 2001, and 2004-05 show there has been little
change in the level of physical activity in the Australian population. The proportion of adults
(18 years and over) that undertook less than 100 minutes of exercise in the two weeks prior to
the surveys has fluctuated between 30% and 35% (AIHW 2008b).
1.3.10
Depression
Depression has been recognised as a common co-morbidity among cardiac patients and an
independent predictor of adverse outcomes (Amin et al 2008; Reddy et al 2008).
Approximately 20% of patients with a recent ACS have major depression, and almost 20% have
minor depression (Carney and Freedland 2008). Numerous studies have documented that
depression in patients with ACS is associated with a higher incidence of mortality, recurrent
cardiovascular events, and healthcare utilisation (Rozanski et al 2005). Parker et al (2008)
determined that only depressive episodes that commenced after an ACS admission were
associated with a poorer cardiovascular outcome.
Amin et al (2008) found that reduced levels of omega-3 fatty acids in blood cell membranes, an
emerging risk factor for both ACS and depression, could help explain the relationship between
depression and adverse ACS outcomes. Furthermore, other studies have found
psychobiological processes to underlie the emotional triggering of ACS (Steptoe and Brydon
2009). Patients with advanced atherosclerosis may be triggered into ACS by acute anger, stress
and depression. Vos and Begg estimated that CHD accounts for 3.3% of DALYs attributed to
depression (Vos and Begg 2007).
1.4 Projected number of ACS events in Australia
There are two primary Australian data sources on ACS treatment that were available. The
AIHW provides an estimate of the number of separations by event type, gender, and 10 year
age brackets, with the latest data being 2006-07 (AIHW 2009). However, there is a possibility
that this data may over estimate the real number of separations because it does not adjust for
transfers and readmissions related to the same event.
The second data source is based on population-based linkage of health records in the Perth
Statistical Division, Western Australia. The linked data is created by determining connections
between core Department of Health Western Australia (DoHWA) data collections and other
administrative data sources and research collections, based on probabilistic linkage created
through the use of similar demographic information(for example, name, sex, date of birth and
address). The data collections linked for the purposes of this study are hospital admissions,
23
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
emergency presentations, and death records associated with the Registry of Births, Deaths,
and Marriages.
ACS separation rates per 100,000 people based on 28 day episodes within the Perth Statistical
Division are shown in Table 1.3. A breakdown into AMI and unstable angina is shown in
Appendix A. The data are derived from hospital admissions regarding diagnoses for AMI or
unstable angina in any diagnostic field and includes fatal and non-fatal cases. They relate to
residents of Perth aged 35 to 79 years and do not necessarily include persons admitted to
hospitals in Perth.
Table 1.3: ACS age standardised separations per 100,000 in the Perth Statistical Division
1998
1999
2000
2001
2002
2003
2004
Male
35-39
94.29
59.39
70.96
81.28
109.19
67.63
64.87
40-44
213.83
193.86
170.49
154.72
179.33
161.42
146.44
45-49
397.95
365.98
345.38
360.5
357.51
367.59
376.70
50-54
659.14
568.43
578.46
593.81
590.75
558.43
617.38
55-59
978.60
831.56
935.90
966.53
881.23
737.16
746.52
60-64
1,631.62
1,455.51
1,263.72
1,130.41
1,244.37
1,153.36
1,133.31
65-69
2,062.73
1,888.57
2,126.07
1,865.43
1,739.60
1,588.87
1,569.30
70-74
2,932.90
2,545.76
2,589.75
2,494.91
2,692.13
2,271.31
2,160.06
75-79
3,536.54
3,466.43
3,349.81
3,356.41
3,208.88
3,164.05
3,007.81
35-39
26.03
14.72
18.53
20.19
20.37
20.56
37.16
40-44
48.99
33.60
40.62
61.90
30.51
29.90
55.73
45-49
98.64
80.51
78.88
87.05
80.60
89.08
109.22
50-54
204.43
203.58
200.49
184.81
169.6
166.31
160.67
55-59
350.18
339.95
342.74
280.74
258.69
255.16
257.21
60-64
565.95
536.99
536.62
482.21
436.62
447.22
444.23
65-69
1,015.39
1,024.31
866.52
812.83
749.69
736.96
643.85
70-74
1,406.34
1,584.70
1,476.78
1,231.23
1,304.21
1,212.77
1,225.07
75-79
2,441.32
2,088.66
2,099.46
2,216.32
2,186.73
2,040.49
1,891.28
Female
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
As patient records are linked, the Western Australian data linkage information has the capacity
to avoid the inflationary effects of transfers and readmissions as it allows a patient to be
followed within the hospital system. To provide an estimate of the number of separations
within Australia, separation rates for AMI and unstable angina derived from the linked data
were applied to the Australian population by age bracket and gender. These were then
compared to the separation data supplied by AIHW.
Although the data accounts for re-admissions within a 28 day period there are some
limitations in their use for this study. As the most recent data are for 2004, and there is a
downward trend apparent in the data between 1998 and 2004, using 2004 data is likely to
overestimate the number of separations for 2009. In order to adjust for possible over
24
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
estimation, linear trends were projected to 2009 (by age group, condition, and gender) to
estimate a more recent measure of separation rates.
Actual and projected age standardised separation rates for AMI, unstable angina and ACS for
age groups 35 to 79 years are shown in Chart 1.9, Chart 1.10 and Chart 1.11 respectively. In
summary:
■
AMI in males has decreased from 425 separations per 100,000 in 1998 to 362
separations per 100,000 in 2004. It is projected that AMI in males will be approximately
326 separations per 100,000 in 2009.
■
AMI in females has decreased from 164 separations per 100,000 in 1998 to 147
separations per 100,000 in 2004. It is projected that rates for AMI in females will be
approximately 145 separations per 100,000 in 2009.
■
Unstable angina in males has decreased from 518 separations per 100,000 in 1998 to
382 separations per 100,000 in 2004. It is projected that unstable angina in males will be
approximately 275 separations per 100,000 in 2009.
■
Unstable angina in females has decreased from 252 separations per 100,000 in 1998 to
184 per 100,000 in 2004. It is projected that unstable angina in females will be
approximately 109 separations per 100,000 in 2009.
■
ACS in males has decreased from 943 separations per 100,000 in 1998 to 744 per
100,000 in 2004. It is projected that ACS in males will be approximately 601 separations
per 100,000 in 2009.
■
ACS in females has decreased from 416 separations per 100,000 in 1998 to 331
separations per 100,000 in 2004. It is projected that ACS in males will be approximately
254 separations per 100,000 in 2009.
The faster decline in unstable angina compared to AMI is consistent with the hypothesis
purported by Sanfilippo et al (2008) that the uptake of troponin testing between 1998 and
2004 has increased diagnosis of AMI at the expense of unstable angina. According to Emeritus
Professor Michael Hobbs (pers. comm. 06 May 2009) it is likely that this trend will continue.
However, there is evidence that separation rates for ACS are still declining (as shown in Chart
1.11), which is consistent with the long term decline in 28 day case fatality following AMI
(Sanfilippo et al 2008) and CHD (AIHW 2006).
The declining trend in age standardised separation rates for ACS is consistent with AIHW
findings that separation rates for CHD have been declining since its peak in the late 1960s
(AIHW 2009a). Specifically, AIHW (2009a) showed that CHD rates were 589.2 separations per
100,000 and 304.0 separations per 100,000 for males and females respectively in 1968, but
had declined significantly to 132.6 and 76.6 in 2006.
25
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.9: Actual and projected age standardised separation rates for AMI
Age standardised rates per 100,000
500
Male
Female
400
300
200
100
Projected rates
Actual rates
0
1998 1999
2000 2001 2002
2003 2004
2005 2006 2007
2008 2009
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009 and Access Economics calculations
Chart 1.10: Actual and projected age standardised separation rates for unstable angina
Age standardised rates per 100,000
600
Male
500
Female
400
300
200
100
Actual rates
0
1998 1999
2000 2001 2002
Projected rates
2003 2004
2005 2006 2007
2008 2009
Note: Based on age groups between 35and 79 years in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009 and Access Economics calculations
26
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.11: Actual and projected age standardised separation rates for ACS
Age standardised rates per 100,000
1,000
Male
800
Female
600
400
200
Actual rates
Projected rates
0
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009 and Access Economics calculations
One other limitation with the WA linked data for this study was that separation rates were
available only for those between 35 and 79 years. Although AIHW data suggests that less than
one per cent of all separations for ACS are for those aged less than 35 years (AIHW 2009),
evidence suggests that the burden of cardiovascular disease falls particularly heavily on those
above the age of 80 (Begg et al 2007; Vos and Begg 2007). Consequently leaving these age
groups out of the analysis would underestimate the true number of ACS separations in
Australia, and underestimate the costs associated with those separations.
In order to capture separation rates for patients over the age of 79, separation rates between
25 and 79 years were fitted with trends (by condition and gender) and then projected to age
groups beyond 79 years6. Separation rates and fitted trend lines are shown in Appendix A.
Projected separation rates for AMI and unstable angina are shown in Chart 1.12 and projected
separation rates for ACS are shown in Chart 1.13. In summary, age standardised separation
rates associated with:
■
AMI (males and females) and unstable angina (females) follow an exponential growth
curve with separation rates significantly increasing beyond the age of 80 years;
■
unstable angina (males) follow a polynomial curve, increasing with flatter growth
(compared to AMI) beyond the age of 80 years;
■
■
AMI are larger for males compared to females;
unstable angina are larger for males between 35 to 94 years, but female rates become
larger than males for 95 years and above; and
6
Unfortunately separations recorded by AIHW are truncated at age 85+ so a comparison of projected separation
rates used in this study for those 85+ could not be made.
27
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
■
ACS is larger for males but the gap between males and females becomes progressively
smaller for those aged 80 years and older.
Chart 1.12: Projected age standardised separation rates by condition 2009
12,000
Age standardised rates per 100,000
AMI (M)
10,000
AMI (F)
Unstable angina (M)
8,000
Unstable angina (F)
6,000
4,000
2,000
0
3539
4044
4549
5054
5559
6064
6569
7074
7579
8084
8589
9094
95- 100+
99
Source: Access Economics calculations
Chart 1.13: Projected age standardised separation rates for ACS 2009
Age standardised rates per 100,000
16,000
ACS (M)
14,000
ACS (F)
12,000
10,000
8,000
6,000
4,000
2,000
0
3539
4044
4549
5054
5559
6064
6569
7074
7579
8084
8589
9094
95- 100+
99
Source: Access Economics calculations
28
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
By projecting each age bracket (between 35 and 79) out to 2009 and fitting individual trends
for each year (by condition and gender) to estimate separation rates beyond 79 years,
separation rates for age 35 to 100+ were projected for each year from 1998 to 2009. These are
shown in Appendix A.
As the projected separation rates are based on rates associated with residents in the Perth
Statistical Division they do not pick up differences in rates between Indigenous and nonIndigenous Australians. According to Australia’s Health (AIHW 2008a), Aboriginal and Torres
Strait Islander people generally suffer from poorer health outcomes than non-Indigenous
Australians. Evidence shows that Indigenous Australians are three times more likely to have a
major coronary event compared to non-Indigenous Australians across all age groups less than
75 years (Mathur et al 2006). Mortality rates for Indigenous Australians from a major coronary
event are 1.5 times higher than for non-Indigenous Australians (Mathur et al 2006).
Furthermore, Indigenous Australians have higher rates of chronic kidney disease, which
contributes to ACS incidence and can lead to adverse outcomes after an event.
Overall, cardiovascular disease mortality rates amongst Indigenous Australians have been
increasing since 1977, even though this increase has been slower since the 1990s (Thomas et al
2006). In comparison, mortality rates for all Australians have been falling significantly. These
are consistent with the results found in You et al (2009) for Indigenous Australians in Northern
Territory.
The discrepancy between the prevalence and mortality rates of ACS between Indigenous and
non-Indigenous populations is due, in part, to the higher reported prevalence of factors that
increase the risk of coronary heart disease (CHD) for Indigenous Australians. In 2004-05,
Indigenous Australians were more likely to be overweight or obese, be physically inactive, and
have diabetes and high blood pressure. Indigenous Australians were also twice as likely to be
current smokers and had higher rates of consuming alcohol at high-risk levels and using illicit
substances compared to non-Indigenous Australians. These factors also contribute to poor
survival after an event.
Given that Indigenous Australians have higher rates of CHD and die from this condition at
more than twice the rate of non-Indigenous Australians, it is important to ensure they have
equal access to optimal care. However, data shows that the rate of cardiac angiography and
revascularisation (including PCI and CABG) is 40% lower for Indigenous Australians (Mathur et
al 2006). This is consistent with the results in Coory and Walsh (2005), who found rates of PCI
were significantly lower by 39% compared to non-Indigenous Australians. Furthermore,
Indigenous Australians tend to have relatively poor access to rehabilitation and secondary
prevention after an ACS event, which is likely to be playing a role in the worse survival
outcomes.
It is clear that the burden of disease of CHD is even greater for the Indigenous population. The
variation in the epidemiology and treatment of Indigenous patients should be included in any
future research plan associated with ACS in Australia.
1.4.2
Projected number of separations
To determine the number of annual separations associated with AMI, unstable angina and
ACS, projected age standardised separation rates for 2009 were applied to projected
29
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
population estimates derived from the Access Economics’ Demographic mode (AE-DEM).7
These are shown in Chart 1.14 and are compared to projected number of separations based on
data from the National Hospital Morbidity Database (AIHW 2009).
Chart 1.14: Comparison of projected ACS separations in Australia 2009
100,000
Projections using WA linked data
Separations
80,000
Projections using AIHW data
60,000
40,000
20,000
0
AMI
Unstable angina
Total
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009, AIHW (2009), Access Economics calculations
In total, it is projected that there will be around 79,900 separations associated with ACS in
Australia in 2009. Of these, 47,539 are expected to be associated with AMI while 32,452 are
expected to be associated with unstable angina.
In comparing the number of separations to AIHW data, projections using WA linked data are
smaller, particularly for AMI where projections based on the AIHW dataset is around 19.5%
greater. However, this difference is expected as WA linked data reduces the inflationary effect
of readmissions and transfers. For unstable angina, where readmission and transfers are less
likely, the difference is less pronounced, with AIHW separations being around 12.5% greater8.
The projected number of ACS separations was further broken down into age, gender, and
condition and are shown in Chart 1.15, Chart 1.16, Chart 1.17, and Chart 1.18. These are
summarised below.
7
AE-DEM is a model containing detailed projections of Australia’s population. Building up from the demographic
‘first principles’ of births, deaths, migration and household formation, the model projects population by age and
gender for each State and Territory.
8
According to Emeritus Professor Michael Hobbs (pers. comm. 22 May 2009), Perth may have lower ACS rates than
the national average. Although the World Health Organisation ‘s MONICA study (AIHW 2000) found that AMI rates
were much higher for those aged between 35 and 64 in Newcastle (NSW) compared to Perth between 1984 and
1993, it may be the case that Newcastle has a higher rate than the national average.
30
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
■
Total number of ACS separations associated with males is projected to be 48,820 (61%)
in 2009.
■

AMI is expected to account for 28,596 (59%) while unstable angina is expected to
account for 20,224 (41%).

Separations for AMI are expected to peak for males aged between 80 and 84
while the number of separations for unstable angina are expected to peak for
males aged between 70 and 74 years.

ACS separations are expected to peak for males aged between 75 and 79.
Total number of ACS separations associated with females is projected to be 31,170
(39%) in 2009.
■

AMI is expected to account for 18,943 (61%) while unstable angina is expected to
account for 12,228 (39%).

Separations for AMI and unstable angina are expected to peak for females aged
between 85 and 89.

ACS separations are expected to peak for females aged between 85 and 89.
Total number of ACS separations is projected to be 79,990.

AMI is expected to account for 47,539 separations (59%) while unstable angina is
expected to account for 32,452 separations (41%).

ACS separations are expected to peak for people aged 75 to 79 years.
Chart 1.15: Projected male separations in Australia 2009
8,000
AMI
7,000
Unstable angina
Separations
6,000
Total ACS
5,000
4,000
3,000
2,000
1,000
0
3539
4044
4549
5054
5559
6064
6569
7074
7579
8084
8589
9094
95- 100+
99
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009, AIHW (2009), Access Economics calculations
31
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.16: Projected female separations in Australia 2009
6,000
AMI
Separations
5,000
Unstable angina
Total ACS
4,000
3,000
2,000
1,000
0
3539
4044
4549
5054
5559
6064
6569
7074
7579
8084
8589
9094
95- 100+
99
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009, AIHW (2009), Access Economics calculations
Chart 1.17: Projected total separations in Australia by condition 2009
14,000
AMI
12,000
Unstable angina
Total ACS
Separations
10,000
8,000
6,000
4,000
2,000
0
3539
4044
4549
5054
5559
6064
6569
7074
7579
8084
8589
9094
95- 100+
99
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009, AIHW (2009), Access Economics calculations
32
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.18: Projected total separations in Australia by gender 2009
14,000
12,000
Male
Female
All
Separations
10,000
8,000
6,000
4,000
2,000
0
3539
4044
4549
5054
5559
6064
6569
7074
7579
8084
8589
9094
95- 100+
99
Source: Emeritus Professor Michael Hobbs, pers. comm. 07 May 2009, AIHW (2009), Access Economics calculations
State and territory breakdown of separations
State and territory breakdowns of AMI and angina pectoris public separations (unstable angina
could not be separated) derived from AIHW Hospital Statistics (AIHW 2008) are presented in
Chart 1.19.
Shares generally follow the share of population in Australia for each state and territory. NSW
has the greatest share of AMI, accounting for around 35% of all public separations in Australia
in 2006-07, although its share of angina pectoris is only 30%. There are small share differences
between AMI and angina pectoris for Victoria and Queensland, while shares are virtually the
same across conditions for the remaining states and territories.
33
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.19: Share of AMI and angina pectoris across states and territories 2006-07
Acute myocardial infarction
2%
Angina pectoris
1% 1%
3% 2%
8%
1%
NSW
8%
Vic
30%
8%
35%
Qld
9%
WA
SA
18%
Tas
22%
ACT
27%
25%
NT
Source: AIHW (2008)
1.4.3
Projected number of deaths
Separations associated with ACS can result in two outcomes – recovery or death. Trends in 28
day case fatality for persons aged 35 to 79 years old derived from the WA linked data are
shown in Chart 1.20. Between 1980 and 2004 there has been a significant reduction in 28 day
case fatality following AMI, falling from around 13.5% and 18.1% for males and females
respectively to around 4.7% and 7.1%. Using the linear trends established between 1980 and
2004, projected 28 day case fatalities for 2009 are expected to be 2.6% and 3.6% for males and
females respectively.
Although females have lower rates of ACS, they have a higher rate of 28 day case fatality than
males, although the gap has narrowed over the last 25 years. According to Emeritus Professor
Michael Hobbs (pers. comm. 12 May 2009), males tend to have more sudden deaths before
hospitalisation and the risk factors for ACS tend to be different in females, with higher
prevalence of both hypertension and diabetes that worsen the prognosis.
The 28 day case fatality presented in Chart 1.20 provides an estimate of the number of deaths
resulting from ACS after a person has been admitted to hospital and within 28 days of being
admitted. However, there are a significant proportion of people who do not survive an event
before they get to the hospital, or do not survive after 28 days. Estimates based on 35 to 79
year olds from the WA linked data suggest around 70% of total deaths from CHD are out of
hospital (Emeritus Professor Michael Hobbs, pers. comm. 12 May 2009). Chew et al (2008)
found that overall mortality associated with ACS was significant up to 12 months, with
mortality associated with patients experiencing STEMI, non-STEMI, unstable angina, and stable
angina being 8.0%, 10.5%, 3.3%, and 3.7% respectively. Due to the risk of missing out on a
significant number of deaths associated with ACS, mortality data from the WA linked database
was not used in estimating the number of deaths associated with ACS.
34
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Age-standardized 28-day case-fatality (%) .
Chart 1.20: 28 day case fatality following AMI
30
25
1980–1988
1989–1997
1998–2004
OR(slope) = 1.004
(95% CI: 0.974, 1.034)
OR(slope) = 0.942
(95% CI: 0.909, 0.976)
20
OR(slope) = 0.924
(95% CI: 0.866, 0.985)
15
10
OR(slope) = 0.965
(95% CI: 0.941, 0.989)
OR(slope) = 0.921
(95% CI: 0.895, 0.948)
5
0
1980
1984
1988
1992
1996
Women
Men
OR(slope) = 0.927
(95% CI: 0.880, 0.977)
2000
2004
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Sanfilippo et al (2008)
To determine the total number of deaths associated with ACS, data were extracted from the
Australian Bureau of Statistics publications titled Causes of Death, Australia. The underlying
cause of death was AMI. Although a small number of deaths were recorded for angina pectoris
(27 deaths in 2007), the data did not indicate deaths associated with unstable angina so they
were not included in the study.
The most recent year for which this data are available is 2007, however only the total number
of deaths by gender is reported. To obtain an estimate for 2009, the total number of deaths
due to AMI was linearly extrapolated to 2009 for each gender from a time series spanning
2003 to 2007. It was further broken up into age groups by assuming that the share of each age
group in the total remains the same as presented in the 2007 data.
Chart 1.21 shows the actual and projected number of deaths following AMI in Australia
between 2003 and 2009, while Table 1.4 presents projected deaths for 2009 by gender and
age bracket. In 2003 there were around 13,149 deaths, dropping to around 11,332 in 2007. In
2009, it is expected that there will be a total of 9,959 deaths following AMI. Of these, males
will account for around 50.4% and females will account for around 49.6%. Compared to the
projected number of AMI separations for 2009, this would suggest deaths occurring within 28
days of a separation account for around 24.3% of all deaths associated with AMI.
The decline in deaths and death rates associated with AMI can be attributed to a number of
factors. The WHO MONICA project (AIHW 2000) examined trends in AMI in 33 populations in
22 countries between 1984 and 1993. It found that large decreases in AMI rates could be
attributed to lifestyle changes, accounting for around 70%. The remainder could be attributed
to changes in medical treatment. AIHW (2009a) notes that the decline in rates of CHD can be
attributed more recently to improvements in detection, prevention, treatment and
rehabilitation care. Emergency medical services for heart attack have improved and increases
in specialist ACS care facilities around the country have also contributed to improved survival
35
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
probabilities and times. Furthermore, AIHW notes reductions in some risk factors have
contributed, for example the prevalence of daily smoking has declined by 45% for males and
42% for females between 1985 and 2007 (AIHW 2008a).
Chart 1.21: Actual and projected deaths following AMI Australia
16,000
Deaths following AMI
14,000
Males
Females
Total
Projected
Actual
12,000
10,000
8,000
6,000
4,000
2,000
0
2003
2004
2005
2006
2007
2008
2009
Source: ABS (2003, 2004, 2005, 2006 and 2007) and Access Economics calculations
Table 1.4: Projected deaths following AMI by age bracket Australia 2009
Males
Females
Total
35–44 years
81
18
99
45–54 years
239
44
283
55–64 years
478
137
615
65–74 years
892
428
1,320
75–84 years
1,905
1,570
3,475
85 years and over
1,427
2,741
4,167
Total
5,022
4,937
9,959
Source: ABS (2003, 2004, 2005, 2006 and 2007) and Access Economics calculations
1.5 Impact of demographic ageing
It is problematic to project ACS separation rates and total separations into the future as the
declines in rates between 1998 and 2004 may not be representative of the long term trends. It
is more than likely that separation rates will continue to decrease in the immediate future, but
for how long and how much is unknown.
As separation rates decline, it could be expected that further improvements in treatment may
be harder to achieve (that is, the marginal benefit of additional investment decreases as total
investment increases). Furthermore it is unclear how current trends in the risk factors
associated with ACS will impact on separation rates in the future. For example, as shown in
Section 1.3, tobacco use is currently decreasing in Australia along with the prevalence of high
36
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
blood pressure, while the prevalence of overweight and obese people and the prevalence of
diabetes are increasing rapidly.
One undisputable fact is that the Australia population is becoming older and this will put
increased pressure on ACS resources. For example, Chart 1.22 shows the larger bulge for age
brackets 70 to 74 and above, with the proportion of people in high risk age groups (65+ years)
expected to increase from 13.9% to 23.2% between 2009 and 2050.
Chart 1.22: Projected Australian population age structure
2009
100+
95-99
90-94
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
4.0
Female
2050
Male
100+
95-99
90-94
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
2.0
0.0
2.0
4.0
% of total population
4.0
2.0
0.0
2.0
4.0
% of total population
Source: ABS (2008) and Access Economics calculations
In order to gauge the pressure demographic ageing will have on the number of separations in
Australia, the separation rate was held constant at 2009 levels and total separations were
projected based on expected population growth and demographic ageing. Chart 1.23 shows
that in 2010 total ACS separations are expected to be around 82,429 but are projected to
increase to 246,031 by 2050 (or a 199% increase). Consequently, if the future trend in
separation rates starts to flatten, or even starts to increase as diabetes and obesity continue to
rise, then the expected impact on direct health care system costs and indirect costs associated
with productivity losses is likely to be compounded significantly by the changing underlying
demographic structure of the Australian population.
37
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 1.23: Projected ACS separations in Australia
300,000
Separations per year
250,000
200,000
150,000
100,000
50,000
0
2010
2020
2030
2040
2050
Note: Assumes separation rates for AMI and unstable angina are held constant at projected 2009 levels
Source: Access Economics calculations
38
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
2
Direct health care system costs
Although the treatment of ACS will clearly depend on the severity of the symptoms being
experienced, the presence of ACS symptoms should be treated as a medical emergency. All
patients will undergo a 12-lead electrocardiogram (ECG) to determine the type and severity of
the ACS event. AMI events are likely to require reperfusion, which restores blood flow to the
heart and can be achieved through angioplasty or fibrinolysis.
According to ACS Guidelines (NHF and CSANZ 2006), the preferred type of reperfusion is
angioplasty, which can only be performed within catheterisation laboratories. However,
fibrinolysis is still the most common form of treatment performed for ACS. Post operative care
is also an important part of effective ACS management and includes therapies such as aspirin,
β-blockers, angiotensin-converting enzyme (ACE) and lipid-lowering agents (LLAs).
The direct health care system costs related to ACS are therefore mostly composed of inpatient
and pharmaceutical costs, since in-hospital procedures and drug therapy are the most
important and vital part of ACS treatment. Patients also need to consult GPs and specialists in
relation to their condition, and require specialised pathology and imaging, such as
echocardiography.
2.1 Methodology
Estimates of direct health system costs are based on data from the Australian Institute of
Health and Welfare (AIHW), provided in a special data request. This data contains allocated
expenditures on Ischemic Heart Disease (ICD-10 codes I20–I25) for years 2000-01 and 2004-05.
The AIHW take a ‘top down’ approach to estimate expenditures associated with different
conditions, where total health system expenditures are first estimated and are then assigned
to the relevant conditions, based on the principal diagnosis of the patient. Expenditure
estimates are allocated across conditions using data from the hospital establishments
collection, hospital morbidity records and Casemix, Medicare, the Pharmaceutical Benefits
Scheme (PBS), the Pharmacy Guild Survey, and the BEACH (Bettering the Evaluation and Care
of Health) survey of general practice (AIHW 2008b). The data includes costs associated with:
■
■
■
■
■
■
■
hospital inpatients and outpatients;
aged care;
specialist and primary medical care;
pathology and imaging;
pharmaceuticals;
research; and
other professional services.
Due to changes in these categories from 2000-01 to 2004-05, some calculations were
performed on the 2004-05 data in order to maintain comparability with the earlier period.
Specifically, the 2004-05 data excludes costs related to outpatients; these were calculated
assuming that the proportion of outpatient costs to total hospital costs remains as in 2000-01.9
9
Total hospital costs consist of inpatient and outpatient costs.
39
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Costs related to other health professional services and aged care were also omitted from the
2004-05 data and a similar procedure was used to estimate these costs.10
An attempt was made to obtain specific expenditure data for Acute Coronary Syndrome (ACS)
(ICD-10 codes I20.0 and I21), however the AIHW were only able to supply the total cost for
ICD-10 codes I20-I25. Thus, in order to obtain costs relating specifically to ACS, AIHW data on
patient days by principal diagnosis was utilised. Specifically, the numbers of patient days for
unstable angina (I20.0) and acute myocardial infarctions (I21) were compared to the total
number of patient days for all Ischemic Heart Disease categories (I20-I25), in 2000-01 and
2004-05. These proportions were applied to the year-appropriate Ischemic Heart Disease cost
statistics and specific costs were calculated for unstable angina and AMI for 2000-01 and 200405.11
To estimate ACS costs in 2009, unstable angina and AMI costs were each linearly extrapolated
to 2009 based on the trend from 2000-1 to 2004-05. This method encompasses trends in the
prevalence of these two conditions and in health inflation. It also assumes that trends
observed between 2000-01 and 2004-05 persist for the next four years, to 2009. To estimate
the direct health care system costs per separation for AMI and unstable angina in 2009, total
direct health care system costs of each condition were divided by the projected number of
separations for each condition (as shown in Chapter 1).
There are potential problems with linearly extrapolating costs based on the observed trend.
There has been a large increase in the use of catheterisation labs in recent years, which are
more expensive, compared to fibrinolysis. This could lead to an underestimation in the rise in
costs. However, catheterisation labs have also led to better outcomes, in terms of fewer
complications and reduced hospital bed days, which lower costs and could lead us to overestimate of the cost increase. It is uncertain which effect dominates.
2.2 Direct health care system costs
It is projected that direct health care system costs will be around $1.8 billion for 2009. Table
2.1 shows the direct health care system costs of ACS by gender and age group. Costs are
substantially higher for males, accounting for around 62% of total costs. Males aged between
65 and 74 account for the largest direct health care system costs associated with ACS. For
women, the highest costs are in the 75 to 84 age group. The distribution of costs by age group
can be seen in Chart 2.1.
10
A subtotal was calculated for 2000-01, excluding other health professional services and aged care to obtain the
shares of these two categories, these shares were then applied to the 2004-05 data and the total cost was increased
to include these two categories.
11
Proportions were calculated for years 2000-01 through to 2006-07 for both patient days and separations, in order
to check for consistency; trends in the two measures were consistent.
40
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 2.1: Projected direct health care system costs by age and gender 2009
Males
0-4
5-14
15-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total - Males
0-4
5-14
15-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total - Females
All
0-4
5-14
15-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Total
Unstable Angina
AMI
ACS
$ (million)
$ (million)
$ (million)
0
0
0
2
13
40
100
104
89
16
364
0
0
0
2
6
22
40
46
69
27
213
0
0
1
8
31
92
172
191
190
56
741
0
0
0
3
11
29
57
86
157
106
450
0
0
1
10
44
132
271
295
279
72
1,104
0
0
0
6
17
51
97
132
226
134
663
0
0
0
4
19
62
140
150
159
43
0
0
1
11
42
121
229
277
346
162
0
0
1
16
61
183
369
427
505
205
577
1,191
1,767
Source: Access Economics calculations based on AIHW special data request
41
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 2.1: Distribution of direct health care system costs of ACS 2009
350
300
Males
Females
$ (million)
250
200
150
100
50
0
25-34
35-44
45-54
55-64
65-74
75-84
85+
Source: Access Economics based on AIHW special data request
Costs by expenditure type are presented in Table 2.2 and Chart 2.2, Chart 2.3, and Chart 2.4.
Inpatients account for by far the largest share of total ACS costs at around 63.4%. Costs
associated with pharmaceuticals are the next largest category, representing around 20% of
total costs. This is followed by out-of-hospital specialists and outpatients, at 5% and 4%
respectively.
Table 2.2: Projected direct health care system costs, by expenditure type 2009
Unstable Angina
AMI
ACS
$ (million)
$ (million)
$ (million)
Inpatients
Outpatients
Aged care
GPs
Imaging & Pathology
Out-of-hospital specialists
Pharmaceuticals
Other professional services
Research
361
22
10
11
10
30
114
6
13
760
47
20
23
21
60
219
13
29
1,120
69
30
34
30
90
333
19
42
Total
577
1,191
1,767
Source: Access Economics calculations based on AIHW special data request
42
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 2.2: Direct health care system costs of ACS by expenditure type 2009
Other professional
Research
services
2%
1%
Pharmaceuticals
19%
Total (m)
$1,767.4
Out-of-hospital
specialists
5%
Imaging &
Pathology
2%
GPs
2%
Inpatients
63%
Aged care
2%
Outpatients
4%
Source: Access Economics based on AIHW special data request
Chart 2.3: Direct health care system costs of AMI by expenditure type 2009
Other professional
Research
services
2%
1%
Pharmaceuticals
18%
Total (m)
$1,190.88
Out-of-hospital
specialists
5%
Imaging &
Pathology
2%
GPs
2%
Inpatients
64%
Aged care
2%
Outpatients
4%
Source: Access Economics based on AIHW special data request
43
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart 2.4: Direct health care system costs of unstable angina by expenditure type 2009
Other professional
Research
services
2%
1%
Pharmaceuticals
20%
Total (m)
$576.5
Out-of-hospital
specialists
5%
Imaging &
Pathology
2%
Inpatients
62%
GPs
2%
Aged care
2%
Outpatients
4%
Source: Access Economics based on AIHW special data request
2.3 Trends in direct health care system costs
Table 2.3 shows the trend in patient days associated with ACS has been decreasing since
2000-01. However this trend has not been uniform across conditions. For example, patient
days for those diagnosed with unstable angina have decreased from 243,538 in 2000-01 to a
projected 111,496 in 2009. However, patient days have been increasing for those diagnosed
with AMI, from 234,326 in 2000-01 to a projected 302,798 in 2009. When combined, the two
conditions reveal an overall decreasing trend in ACS from 2000-01 to 2009 of around 63,571 or
13%.
The increased trend in patient days for AMI is likely to be partly caused by the change in the
definition of AMI. In 2000, an international consensus document was published by the
American College of Cardiology and the European Society of Cardiology (ESC-ACC) that revises
the definition of AMI. The new definition of AMI confirms troponin as the most appropriate
biomarker (Urban et al, 2008) and lowers the troponin threshold for diagnosing AMI. Troponin
testing is a more specific and sensitive test for myocardial necrosis, compared to other
available biomarkers, and in itself improves the diagnosis of mild cases of AMI (Sanfilippo et al,
2008). Furthermore, the lower troponin threshold would have increased the number of
patients diagnosed with AMI and created a subgroup of patients that would have been
categorised as unstable angina according to the earlier definition and are now diagnosed as
AMI (Urban et al, 2008). This would lead to a decreasing trend in unstable angina patient days
and an increasing trend in AMI patient days.
44
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 2.3: Patient days associated with unstable angina and AMI
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
200912
Unstable angina
AMI
ACS
243,538
222,223
205,664
190,687
175,334
159,407
145,650
111,496
234,326
246,650
258,544
270,125
270,756
276,274
284,696
302,798
477,864
468,873
464,208
460,812
446,090
435,681
430,346
414,293
Source: AIHW (2009)
Total projected direct health care system costs associated with ACS are presented in Table 2.4.
The cost of AMI is expected to increase by around 140% between 2000-01 and 2009. The
increase in the cost of unstable angina over the eight years is projected to be more moderate
at around 16%, while the overall cost of ACS is projected to increase by around 77% to around
$1.8 billion.
Table 2.4: Trend in direct health care system costs associated with ACS
2000-01
2004-05
2009
Unstable angina
AMI
ACS
$ (million)
$ (million)
$ (million)
506
546
576
497
844
1,191
1,003
1,390
1,767
Source: Access Economics based on AIHW special data request
The decrease in the number of patient days and the increase in total health care costs
associated with ACS seem contradictory at first glance. However, the pattern is likely to be
caused by several factors. First, since the costs reported by AIHW are nominal, they include
health inflation for this period. Thus the same procedures are costing more. AIHW (2009a)
estimated that health inflation averaged 3.1% between 1995-96 and 2005-06, which would
account for around $277.5 million if applied to the 2000-01 costs up to 2009.
Furthermore, the overall decrease in patient days is likely to be caused by the more frequent
use of catheterisation labs, which provide better outcomes and a reduced need to observe
patients compared to fibrinolysis, but are also more expensive. Average length of stay in
hospital after an AMI event has been reduced significantly as a result of catheterisation labs
due to the reduced risk of death associated with the use of stenting with PCI. Moreover, the
increased use of drug eluting stents, which are also more costly, has contributed to the
observed increase in costs, along with the use of more expensive pharmaceuticals.
2.4 Direct health care system cost per separation
The cost per separation for AMI and unstable angina was calculated using the estimated
number of separations in 2009 derived from Chapter 1 and the estimated total cost of AMI and
12
Estimate – based on a linear extrapolation using the trend between 2000-01 to 2006-07.
45
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
unstable angina for 2009. The cost per separation in 2009 is projected to be $25,051 and
$17,766 for AMI and unstable angina respectively. These costs are broken up into their
components and are presented in Table 2.5.
Table 2.5: Direct health care system costs per separation 2009
Category
Inpatients
Outpatients
Aged care
GPs
Imaging & Pathology
Out-of-hospital specialists
Pharmaceuticals
Other professional services
Research
Total
Unstable Angina
AMI
$
$
11,114
684
300
339
295
914
3,526
191
404
17,766
15,982
984
422
489
433
1,269
4,600
270
602
25,051
Source: Access Economics calculations
46
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
3
Indirect costs associated with ACS
This chapter investigates indirect costs that are related to ACS. As they do not relate to the
direct health care system costs, these costs are indirectly associated with ACS rather than costs
associated with treatment. Indirect costs investigated within this chapter include:
■
productivity losses from reduced labour market participation through lower
employment, greater absenteeism, and premature mortality associated with ACS;
■
costs to informal carers from providing care to someone who has experienced an ACS
event;
■
■
private costs associated with rehabilitation; and
deadweight loss associated with raising additional tax revenue to publicly fund health
care services associated with ACS.
In evaluating indirect costs, it is important to make the economic distinction between real
costs and transfer payments. A real cost is incurred when economic resources are used in the
production of goods and services, such as land, labour and capital. Using resources in one area
of the economy reduces the opportunity to produce goods and services in other areas of the
economy. Transfer payments are defined as payments from one economic agent to another
that are made without receiving any good or service in return. Rather than payments made for
the use of any good or service, they are a transfer of claims over real resources. Some
examples of transfer payments include taxes, subsidies, unemployment benefits and pensions.
As transfer payments do not represent a real economic cost they have not been presented as
an economic cost within this study.
3.1 Productivity losses
There are a number of theoretical links between the level of an individual’s health and their
labour supply (Grossman 1972). Quite simply, better health outcomes allow an individual to
increase their supply of labour and to work more productively. Poor health outcomes are likely
to be associated with lower labour supply and lower productivity, thereby imposing a cost on
the economy.
The cost of lost labour supply and productivity due to ACS were estimated as the earnings lost
as a result of ACS-related mortality and morbidity. In estimating the cost, the human capital
approach was used, which assumes that an employee cannot be easily replaced from the pool
of the unemployed population, and thus that premature death or absence from work would
result in a loss of productivity in the economy. Under the human capital approach, a loss in
productivity due to ACS will only equate to a loss in productivity to the economy under fairly
strict conditions. These are:
■
the economy is at full employment so any reduction in hours worked due to ACS, or any
permanent reduction in labour force participation through early retirement or death,
cannot be replaced by employing or increasing hours of other workers; and
■
the income of an individual is proportional to the total value added to production.
47
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
The first condition will fluctuate over time as the economy moves into, and out of, full
employment. A reduction in labour when labour is scarce will have a greater impact on
productivity compared to an economy with an abundant labour supply. Although the
Australian economy is currently close to full employment it is problematic to determine the
scarcity of labour into the future. Given demographic ageing and current immigration and
workforce policy, it is reasonable to assume that the long term goal of government is to keep
the economy at full employment. This means a temporary or permanent reduction in working
hours due to ACS cannot be replaced by another worker. Consequently a loss in productivity
due to sight loss is expected to represent a real cost to the Australian economy.
The second condition (income of an individual is proportional to the total value added to
production) will occur if there is a perfect labour market such that the marginal benefit from
an additional hour of work (the value added) is equal to the marginal cost (the wage). In
reality, the labour market is far from perfect for a number of reasons, for example asymmetric
information within the market and labour market restrictions imposed by government
regulation and natural labour market barriers. In addition, synergy created between labour,
capital and land means a reduction in working hours may also impact the productivity of other
factors of production. Consequently, the value of productivity from labour is expected to be
larger than the wage provided to an individual, so using lost income as a proxy for lost
productivity will tend to underestimate the true cost.13
The productivity lost due to premature death associated with ACS was calculated by
multiplying the number of deaths that resulted from ACS in 2009, for those aged between 35
and 64, with the residual expected lifetime earnings at the time of death. Specifically, the
employment to population ratio for males and females (ABS 2009)14 was applied to estimate
the number of employed individuals who died as a result of ACS. Assuming a retirement age of
65, the residual number of years of employment was calculated by using the midpoint age of
each age group, while the gender-specific gross yearly wage (ABS 2008a)15 was used to obtain
the residual earnings for males and females in each age group. The present value of these
future earnings was estimated by assuming a five per cent per annum discount rate (NHMRC
2001).
The productivity losses due to ACS-related morbidity include the lost gross earnings for time
taken off work following an ACS event. Estimates of ACS-related morbidity were calculated as
the difference between the projected number of separations for ACS and the number of
deaths resulting from ACS extrapolated to 2009.
The time taken off work following an ACS event was estimated based on research findings in
this area. Specifically, the shortest time off work is assumed to be two months, based on
evidence that a return to work sooner than eight weeks after an AMI event is usually not
recommended (Kovoor et al 2006). It is also assumed that 80% of patients return to work
within 12 months following an ACS event, as reported in Bhattacharyya et al (2006) using UK
data. This study also finds that the average time between ACS and the return to work is 3.4
months, while Kovoor et al (2006) report an average time of 2.7 months. Based on these
13
One criticism of the human capital approach is that productivity losses for those outside the labour market (for
example, students, homemakers and volunteers) are not included in the estimation of total costs (Liljas 1998).
14
These are 77.9% and 66.6% respectively.
15
The latest available data is for October 2008, when the seasonally adjusted gross years wage was $57,356 for
males and $37,430 for females.
48
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
findings, the average time to return to work after ACS is taken to be three months in this
report. Moreover, is assumed that around 55% of patients had commenced work within six
months, a further 12% within seven months and 9% within nine months. The remaining 20% of
patients are assumed to retire or become long-term unemployed until their retirement. For
the 80% of patients who return to work within a year, the earnings lost are calculated using
the appropriate amount of time taken off work and the gender specific average gross yearly
wage (ABS 2008a).16
Based on Zhang et al (2009), it is assumed that the impact of an ACS event on the labour force
participation decision would be different between younger and older individuals17.
Consequently, the 20% of patients who are assumed to retire are also assumed to be aged
between 50 and 64,18 with the midpoint age of 57. Thus, there is on average eight remaining
work years for these patients. Their lost earnings are calculated as the present value of eight
years of the gross average yearly wage, with a five per cent discount rate.
Table 3.1 presents the discounted productivity loss due to premature death associated with
ACS. It is projected that 997 people still in the workforce will die in 2009 due to AMI, resulting
in an expected productivity loss of $287 million.
The productivity loss expected to result from ACS-attributable lost working days is summarised
in Table 3.2. It is projected that there will be 21,085 employed persons between the age of 35
and 65 experiencing an ACS related separation in 2009 that does not result in death. The total
gross earnings lost by these persons are estimated at around $2.3 billion. The largest share of
these productivity losses is attributed to persons who do not return to work following ACS,
amounting to around $1.9 billion.
Table 3.1: Productivity loss due to premature death 2009
Deaths
Discounted productivity loss
No.
$(million)
35–44 years
45–54 years
55–64 years
99
283
615
57
122
107
Total
997
287
Source: Access Economics calculations
16
It is assumed that productivity losses are strictly associated with the ACS event. However there is expected to be
considerable co-morbidity among patients that are attributable to common risk factors (such as diabetes, obesity
and high blood pressure) and these may also reduce the capacity to work after an event.
17
Zhang et al (2009) also suggests the decision to return to work will also differ between males and females,
although this has not been incorporated within this study.
18
Those >64 years are assumed to have already retired.
49
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 3.2: Productivity loss due to working days lost 2009
2 months
3 months
5 months
7 months
9 months
11 months
Retired
Total
Number of persons
Earnings lost
2,108
5,271
4,006
2,530
1,898
1,054
4,217
$(million)
18
69
88
78
75
51
1,949
21,085
2,327
Source: Access Economics calculations
3.2 Cost of informal care
An ACS event not only impacts the individual experiencing the event, it can also impact their
family and friends. This is typically through the emotional strain an event places on others,
such as anxiety and stress associated with uncertainty surrounding survival. However, it can
also impact through lifestyle changes that result from caring activities required immediately
after an event.
A range of informal care activities are usually provided to individuals who have experienced an
ACS event by partners, other family members, and friends. This is especially the case for an
AMI event. Clark et al (2007) notes informal care for those with heart failure is complex, as it
not only includes typical care activities but also invisible care that are not necessarily observed
within the carers behaviour, or known by the individual receiving care. These ‘invisible’ care
activities often relate to ensuring the patient is stable. Informal care activities can therefore
include:
■
■
collecting prescriptions and organising and timing the administration of medication;
■
basic nursing care, such as washing, dressing, assisting with going to the toilet, cooking
and laundry;
■
■
■
■
■
ad-hoc tasks, shopping, transporting and cleaning activities;
participating in the decision making process to seek help from a health care professional
if symptoms change;
surveillance of signs and symptoms associated with an ACS event;
monitoring of the patient’s physical and mental wellbeing;
delivering a support network for any depression that may result from an event; and
assessment of certain activities on the patient’s condition (for example, determining the
appropriateness of social engagements or work related activities).
It is difficult to separate the time family and friends spend helping someone as a result of an
ACS event and the time when they are simply undertaking activities with the person unrelated
to the event. It is even more difficult to estimate the cost of informal care as consideration
must also be given to the number of people receiving informal care, the amount of time
50
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
devoted to informal care per day, the number of days informal care is provided, and the value
of time associated with informal care (which depends on whether the informal carer has
substituted labour supply or leisure time in providing care).
However, international studies suggest informal care costs comprise a significant cost
component in the total cost of CHD and cardiovascular disease (CVD). For example, Allender et
al (2008) estimated that informal care costs totalled €9.1 billion in 2006 for CHD in Europe (or
approximately 18.3% of total costs), and £1.9 billion in the UK (or approximately 20.6% of total
costs). Similarly, Liu et al (2002) estimated that informal care costs associated with CHD in the
UK totalled £2.4 billion in 1999 (or approximately 34.3% of total costs).
Unfortunately, Australian or international data relating to the number of hours associated with
informal care for ACS is not available. Furthermore, data relating to informal care associated
with CHD are scarce. Studies typically apply informal care associated with limiting conditions
(for example, Allender et al (2008), however these studies suffer from not being able to
incorporate the different amounts of time associated with CHD compared to other chronic
conditions.
To estimate the cost of informal care associated with ACS, the opportunity cost method was
used. This method measures the value in alternative use of time spent caring, which is typically
valued by productivity losses (or value of leisure time) associated with caring. It is based on the
assumption that time spent providing informal care could be alternatively used within the paid
workforce or in leisure activities. The value of informal care provided by one individual using
the opportunity cost method can be represented by:
Value of informal care = tiwi
where ti is the time provided by individual i on providing care and wi is the net market wage
rate of individual i (van den Berg et al 2006). For those who provide informal care but are not
in paid work (for example, children or those who have retired) the value of providing informal
care is the value of the lost opportunity of undertaking leisure time. This can be approximated
by the willingness to pay to undertake leisure, or to avoid work. However, the value of leisure
time is often proxied by an average age and sex specific wage rate (Brouwer and
Koopmanschap 2000; Heitmueller 2007). If the value of non-work is more (less) than the
average wage rate, the opportunity cost method will under (over) estimate the value of
informal care.
To proxy the number of hours of informal care provided to people who experience an ACS
event in Australia, the number of hours of informal care per person diagnosed with CHD in one
year in the UK was used (Liu et al 2002).19 Of the 1.46 million people diagnosed with CHD in the
UK, there were around 408.4 million hours of informal care provided, which equates to around
279 hours of informal care per person, or approximately 12 days of 24 hour care. This seems
plausible given part of rehabilitation after an ACS event is a significant amount of bed rest at
home.
Applying the number of informal care hours per separation to the number of projected ACS
separations in Australia in 2009 (79,900), it is estimated that around 22.3 million hours of
19
This was based on a UK Department of Health study on informal care (Green 1988), although it is unclear whether
the study specifically looked at informal care associated with CHD.
51
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
informal care will be provided in 2009. Multiplying this by the seasonally average gross hourly
wage rate in Australia of $31 (ABS 2008a),20 the total cost associated with informal care is
projected to be $691.1 million in 2009.
3.3 Private costs associated with rehabilitation
Private costs associated with rehabilitation can include costs incurred for the purchase of
devices, special equipment, aids and home modifications that allow patients to function
adequately. It was estimated that around 20% of people with CVD have levels of disability
which would require the use of aids and modifications (Access Economics, 2005).
The main types of CVD that cause disability are stroke (cerebrovascular disease) and heart
failure. Since a stroke can damage a part of the brain and thus impair a range of functions,
such as movement, vision and communication, it is reported half of the survivors of stroke are
disabled in the longer term. These patients would require a number of aids and modifications
to be able to function, and would account for most of the need for aids and modifications by
CVD patients. It is not likely that ACS contributes to this need, given the nature of
rehabilitation.
However, rehabilitation after an event usually involves some form of light exercise to reduce
the risk of a repeat event. Consequently, some patients are likely to purchase sporting
equipment, exercise clothes and shoes, and may even join a private gym. Furthermore, there
are private costs associated with attending rehabilitation centres (for example, travel costs),
and opportunity costs associated with time devoted to rehabilitation.
Although these types of private costs represent a direct cost associated with ACS, there are no
data available to estimate them. Furthermore, they are likely to be insignificant compared to
direct costs and other indirect costs (such as productivity losses and informal care costs).
Consequently they have not been included in this study.
3.4 Deadweight loss associated with public funding of health care
Public funding of direct health care system costs related to ACS means that the Australian
government must increase tax revenue to achieve a budget neutral position.21 Consequently
tax rates such as income tax rates and Goods and Services Tax (GST) must be higher that they
would have otherwise been.
Tax and subsidy revenue are not an economic cost but a transfer of payments from one
individual to another. It has therefore not been included in this study. However, increasing tax
revenue is not frictionless as tax reduces the efficiency with which the economy’s resources
are used. For example, an increase in income tax rates will increase the relative price of work
compared to leisure and therefore create a disincentive to work. Alternatively an increase in
the GST increases the price of goods and services that are taxed, resulting in reduced sales.
Consequently there is an associated reduction in consumer and producer surplus, which is
known as the deadweight loss, or excess burden, of tax.
20
Calculated by dividing the seasonally adjusted gross weekly wage for full time adult ordinary time earnings in
November 2008 ($1,166.50) by 38 hours.
21
This implicitly assumes funds have not been directed from some other area of the health care system.
52
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
While the costs associated with deadweight loss will depend on the method used to raise
additional taxes,22 the social cost will not be zero and should therefore be included as a cost of
ACS. The usual assumption in program evaluation is to assume that additional taxes are raised
through income tax rate changes, and this has been assumed in this study.
Seminal studies that have evaluated the marginal welfare cost of raising additional tax revenue
(known as the marginal cost of public funds (MCF)) mostly relate to the United States
(Browning 1976, Stuart 1984, Ballard 1985, Browning 1987). Estimates have ranged from zero
marginal cost to well over 100%. This wide range has been due to alternative models used
(partial versus general equilibrium), alternative parameter estimates, and assumptions on the
adjustment of employment relative to changes in tax rates (labour supply elasticities).
The deadweight loss arising from taxation used in this study was derived from the Productivity
Commission (2003), who estimated a rate of 27.5%. This means that for every one dollar of
additional tax revenue raised there is an associated deadweight loss of $0.275. Multiplying this
rate by total direct health care system costs associated with ACS ($1.8 billion), the deadweight
loss is estimated at $486.2 million.
22
In general it is more efficient to place taxes on markets that are relatively inelastic.
53
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
4
Burden of disease
People who suffer from unstable angina or have had an acute myocardial infarction (AMI) may
experience a considerable loss in both the length and quality of life. As a result, the total stock
of health capital in Australia will be reduced, by an amount that reflects the prevalence of
these conditions as well as their severity. As people place a value on their health, for example
by paying for treatments that increase their health, it is possible to assign a value to the loss in
the stock of health capital due to specific conditions.
This chapter estimates the value of the reduction in health in the Australian population aged
35+ from disability and premature death associated with ACS. The reduction in health is
estimated by using the burden of disease methodology, developed by the World Health
Organisation, the World Bank and Harvard University. The value of this reduction is calculated
by using the value of a statistical life year (VSLY), based on the best practice proposed by the
Department of Finance and Deregulation (DoFD 2008).
4.1 Methodology used for measuring and valuing the burden of disease
The burden of disease methodology was developed as a comprehensive measure of mortality
and disability from diseases, injuries and risk factors for populations around the world in 1990,
projected to 2020 (Murray and Lopez 1996). It uses a non-financial approach, where pain,
suffering and premature mortality are measured in terms of Disability Adjusted Life Years
(DALYs).
DALYs are a measurement unit that quantify the morbidity aspect as well as the premature
death associated with various diseases and injuries (Murray and Acharya 1997). DALY weights
are measured on a scale of zero to one, where a zero represents a year of perfect health and a
one represents death. Other health states that result from specific diseases or injuries are
given a weight between zero and one to reflect the quality of life that is lost due to a particular
condition. A disability weight of, for example, 0.395 for people who survive a heart attack, is
interpreted as a 39.5% loss in the quality of life relative to perfect health. The disability weights
are pre-agreed on by a reference group convened at the WHO on the basis of a person tradeoff method for measuring health state preferences (Murray and Acharya, 1997).
Under the DALY framework, the total burden of disease for an individual with a condition is the
sum of the mortality and morbidity components associated with that condition, and includes
the years of health life lost due to disability (YLDs) and the years of healthy life lost due to
premature death (YLL). If the time preference for health is incorporated, a DALY can be
represented as:
a L
DALYi
t a
Dwi ,t
(1 r )t
a
Where Dw is the DALY weight of the condition experienced by individual i, L is the residual life
expectancy of the individual at age a, and t represents each year within that life expectancy.
Aggregating the DALYs of all individuals with a particular condition produces the total burden
of that disease on society:
54
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Nt
DALYt
DALYi ,t
i 0
where N is the prevalence of that condition at time t.
The DALY approach is not financial, and thus not directly comparable with monetary costs and
benefits associated with a particular condition. In order to undertake an economic evaluation,
a monetary conversion of the loss in healthy life is usually performed. This allows the
determination of the total cost of a condition and also the comparison of this cost to the
benefit from a particular health intervention. The monetary conversion involves applying a
value of a statistical life year (VSLY) in perfect health to the total number of DALYs estimated
for a particular condition. The VSLY emerges from estimates of a willingness to pay for a
reduction in the risk of physical harm in the context of OHS policy, transport and airspace
regulation and environmental policy. The VSLY essentially estimates how much society is
willing to pay to reduce the risk of premature death, expressed in terms of a saving a statistical
life year. In this report, a VSLY of $161,276 was used, as recommended by the Department of
Finance and Deregulation (DoFD 2008).23
4.2 Burden of disease from ACS
To quantify the loss resulting from premature mortality and loss of health associated with ACS,
the Global Burden of Disease methodology was used. Disability weights for unstable angina
and AMI are based on the weights derived in a study on the burden of cardiovascular disease
in Australia (Vos and Begg, 2007). These are:
■
■
0.238 for unstable angina; 24 and
0.395 for AMI.
The total burden of ACS in Australia is calculated using the methodology outlined in section
4.1. The total burden of disease includes two components, the Years of healthy life Lost due to
Disability (YLDs) and Years of Life Lost due to premature death (YLLs). Estimates of the
projected number of ACS separations in Australia were derived from Chapter 1 of this report,
and were used to calculate YLDs from ACS in 2008. YLLs from ACS were estimated using
projections on the number of deaths associated with AMI for 2009 (also derived from Chapter
1)).25 The value of life lost was obtained by applying the VSLY to the residual life expectancy at
the time of death26 and a discount rate of five per cent per annum (NHMRC 2001).
4.2.1
Years of healthy life lost due to disability
YLDs from ACS in Australia were calculated by multiplying the number of separations
associated with unstable angina and AMI that did not result in death by the appropriate
23
As the recommended DoFD figure ($151,000) is expressed in 2007 prices, the VSLY was inflated to 2009 prices
($161,276) using inflation rates of 4.2% for 2007-08 and 2.5% for 2008-09 (ABS 2009a).
24
The disability weight for unstable angina was calculated as the middle point between the disability weights for
AMI and mild/moderate angina pectoris, reported by Vos and Begg (2007).
25
Data was available up to (and including) 2007, and was linearly extrapolated to 2008.
26
Residual life expectancies were obtained from the ABS Life Tables (ABS 2008b).
55
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
disability weight. It is assumed that the disability is experienced for three months following
unstable angina and AMI (Vos and Begg, 2007). In order to obtain the total financial cost
associated with the years of healthy life lost due to disability from ACS, total YLDs were
multiplied by the VSLY. Table 4.1 summarises the estimated value of healthy life lost due to
disability from ACS in Australia in 2009.
Table 4.1: Value of YLDs associated with ACS 2009
35-44
45-54
55-64
65-74
75-84
85+
Total
AMI
Unstable angina
Total
$(million)
$(million)
$(million)
17
76
88
133
220
185
719
8
35
51
71
86
62
311
25
111
138
203
306
246
1,030
Source: Access Economics calculation based on ABS (2008a; 2008b)
AMI accounts for a much larger share of the disability burden, valued at around $719 million,
while the burden associated with unstable angina is valued at around $311 million. This yields
an estimate of around $1.0 billion for the total cost associated with the years of healthy life
lost due to disability in 2009.
4.2.2
Years of healthy life lost due to premature death
The years of life lost due to premature death from ACS are shown in Table 4.2. The estimated
total number of deaths associated with ACS in 2009 was 9,959. Using residual life expectancies
at the time of death (ABS 2008b), the total YLLs from ACS are estimated at 98,733. Applying
the VSLY and a discount rate of 5 per cent, the value of the years of life lost due to premature
death associated with ACS is estimated at around $11.3 billion in 2009.
Table 4.2: YLLs from ACS 2009
Number of deaths
YLLs Discounted value of life lost
$(million)
35–44 years
45–54 years
55–64 years
65–74 years
75–84 years
85 years and over
Total
99
283
615
1,320
3,475
4,167
9,959
4,103
9,051
14,360
20,564
31,508
19,147
98,733
277
721
1,347
2,263
4,001
2,698
11,307
Source: Access Economics calculation based on ABS (2008a; 2008b)
4.2.3
Value of a loss in the stock of health capital due to ACS
The total cost associated with the burden of disease consists of the burden associated with
years of healthy life lost due to disability (YLD) and years of healthy life lost due to premature
death (YLL). Using the estimates presented in the last two sections, the total cost is estimated
to be $12.3 billion in 2009.
56
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
4.3 Burden of disease comparisons
In order to compare the burden of disease associated with ACS to other conditions within
Australia, DALYs estimated by AIHW for each condition for 2003 (AIHW 2007) were linearly
extrapolated to 2009.
The total burden of disease in Australia in 2009 is summarised in Table 4.3. Cancer is the
leading causes of the burden of disease in Australia, accounting for 19% of the total burden.
This is closely followed by cardiovascular disease (including ACS), whose share of the total
burden in 16%. However a large part of this burden is derived from ACS, accounting for around
22%. As a separate condition, ACS imposes the ninth largest burden of disease in Australia.
Table 4.3: Burden of disease in Australia 2009
Males
Females
Total
DALYs
DALYs
DALYs
Malignant neoplasms (all cancers)
287,682
253,354
541,035
Cardiovascular disease
249,289
221,776
471,065
60,462
44,656
105,119
Mental disorders
181,072
198,493
379,565
Nervous system and sense organ disorders
177,185
195,946
373,131
Chronic respiratory disease
102,152
96,468
198,620
Injuries
134,962
57,441
192,402
Diabetes mellitus (Type 1 and 2)
98,228
84,089
182,318
Musculoskeletal diseases
51,984
70,724
122,708
Genitourinary diseases
33,135
41,155
74,290
Diseases of the digestive system
29,744
30,754
60,498
Infectious and parasitic diseases
31,392
18,736
50,128
Acute respiratory infections
20,477
21,410
41,887
Endocrine and metabolic disorders
17,562
17,551
35,113
Neonatal causes
17,917
14,748
32,666
Congenital anomalies
18,384
14,069
32,453
Oral conditions
12,952
14,786
27,738
Skin diseases
11,008
11,774
22,781
Other neoplasms
4,982
6,709
11,692
Ill-defined conditions
4,314
7,041
11,355
Nutritional deficiencies
1,677
5,183
6,860
0
2,285
2,285
- Acute Coronary Syndrome
Maternal conditions
Source: AIHW (2007) and Access Economics calculations
57
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
5
Summary of costs
Table 5.1 presents a summary of projected separations, deaths and costs in 2009. In total, AMI
is expected to cost around $15.5 billion. The majority of these costs are associated with the
burden of disease, accounting for around 78%, which is representative of the large amount of
premature mortality associated with AMI. Total direct health care system costs and indirect
costs are expected to total around $3.5 billion in 2009. The total cost per AMI event (cost per
heart attack) is expected to average $281,000.
Unstable angina is expected to cost around $2.4 billion in 2009. However the burden of
disease only comprises $311 million, or around 13%. The majority of costs are associated with
direct and indirect costs, totalling around $2.1 billion. The total cost per unstable angina event
is expected to average $74,000.
Table 5.1: Summary of estimated separations, deaths and costs 2009
AMI
(Heart attack)
UA
(Chest pain)
ACS
7,536
0
7,536
Hospitalisations without death
Hospitalisations with death occurring later
Total hospitalisations
45,115
2,423
47,538
32,452
0
32,452
77,567
2,423
79,990
Events
55,074
32,452
87,526
$ (million)
1,191
1,254
287
411
328
719
11,307
15,497
$ (million)
577
1,073
0
280
159
311
0
2,400
$ (million)
1,767
2,327
287
691
486
1,030
11,307
17,895
$
25,000
$
18,000
$
22,000
281,000
74,000
204,000
Deaths before reaching a hospital
a
Direct health care system costs
Productivity loss (reduced participation)
Productivity loss (premature mortality)
Informal care
Deadweight loss
Burden of disease (YLD)
Burden of disease (YLL)
Total costs
Cost per separation (direct costs only)
Cost per event (all costs)
b
b
Note: (a) Within 28 days of being admitted to hospital (b) Cost per separation and cost per event has been rounded
to the nearest $1,000. Source: Access Economics
58
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
6
The future of ACS management
It is clear from preceding chapters that ACS is a large source of disease burden and of direct
and indirect costs in Australia. Due to the potential severity and speed of ACS symptoms, an
efficient and effective treatment path is vital in reducing mortality and preventing future cases
of cardiovascular disease and stroke.
Although separation rates for ACS are decreasing, demographic ageing and increasing health
care costs will place a burden on ACS treatment. This presents an opportunity to invest in
areas that will bring further gains to reduce the burden of disease associated with ACS, and to
increase the efficiency of current health care resources. This chapter identifies areas where
further investment to identify potential cost effective strategies in the treatment and
management of ACS is warranted.
6.1 A multidisciplinary approach to ACS care
Due to the nature of ACS, rapid diagnosis and immediate cardiac intervention are important in
influencing clinical outcomes. According to the American College of Cardiology (ACC) and
American Heart Association (AHA) ACS management guidelines, there needs to be a
multidisciplinary continuum of care that stems from the initial onset of symptoms to post
hospital discharge and rehabilitation. Corbelli et al (2009) suggests that without an integrated
pathway of care, appropriate therapy may be underused in ACS patients because of limited
application of best clinical practice as well as poor communication between health service
providers.
To ensure early intervention for ACS patients in Australia, ambulances need to be equipped
with proper facilities in order to minimise the time between the onset of symptoms and
treatment. This includes defibrillators and remote ECG monitoring and thrombolytic
capabilities. ECG readings should be transmitted to a cardiologist to confirm the patient has
ACS. Paramedics should be trained to interpret ECGs and perform thrombolysis if appropriate
so that treatment can be offered to patients immediately on-site or in the ambulance on the
way to a hospital. A pre-hospital thrombolysis program is already being trialled in the Hunter
region by Ambulance Services of NSW in conjunction with Hunter New England Health (and the
John Hunter Hospital). A similar trial was conducted by the Queensland Ambulance Service in
2008
It is necessary to extend the treatment path beyond in-hospital care because patients with a
history of ACS are more susceptible to recurrences of vascular or ischemic events. Rockson et
al (2007) found that ACS increases the risk of future coronary, cerebrovascular, and peripheral
arterial events, thereby increasing the risk of further cardiovascular morbidity and mortality.
Furthermore, substantial benefits to the patient’s wellbeing can be generated through
supporting patients’ spouses, carers and family members in all stages of the treatment
pathway.
In a study of three Australian hospitals, Scott et al (2004) found that the quality of ACS care can
be significantly improved. Suggestions included:
■
the introduction of simple in-hospital interventions such as patient education program
for self-management;
59
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
■
■
■
reminder tools to support adherence to clinical guidelines;
performance feedbacks to generate discussion; and
ongoing improvements in care and facilitation of multidisciplinary approach to work
practices.
Following quality improvement interventions, Scott et al (2004) found there were statistically
significant improvements in timeliness of ECGs, prescription of coagulants at discharge and use
of patient counselling and rehabilitation services.
6.2 A national ACS registry
Despite the recognised advantages of evidence based care (Corbelli et al 2009) gaps between
evidence based treatment strategies and actual practice currently exist within Australia. For
example, Chew et al (2007) and Walters et al (2008) found that some ACS patients are
undertreated and there are significant delays in patients receiving guidelines based treatment.
Both studies highlight the persistent suboptimal utilisation of established pharmacological
therapies. For example, Chew et al (2007) found that only 56.7% of patients with STEMI
received all five secondary prevention medications recommended by the Australian Guidelines
at hospital discharge. One reason suggested was the lack of recognition of patient risk factors
due to limited data documenting patient management.
Although many clinical studies attempt to compare risk factors amongst patients, treatment
methods and resulting outcomes, these are typically done within a controlled and sterilised
environment. Consequently, results may differ when applied to the health care system (Tonkin
2001). In addition, most studies of ACS treatment pathways and health outcomes focus on
international health care systems. It is difficult to extrapolate results from these studies to an
Australian context because Australia has its own unique health care system, patient
characteristics and behaviour, and health environment.
At present, Australia does not have a state wide database on ACS patients or care, let alone a
uniform national ACS registry. Collection of comprehensive and consistent data at a local level
across Australia is necessary in order for ACS treatment and outcomes to be measured. This
will provide the opportunity to identify best practice and shift limited health care resources to
those areas that are cost effective. Subsequent advantages are expected to include improved
quality of care, more appropriate treatment, better health outcomes, and a reduction in costs
relative to health gains.
To isolate factors that increase the risk of ACS and cause variations in treatment outcomes
amongst different patients, data needs to be collected on those factors that impact individual
health and treatment outcomes, both within and outside the health care system. Table 6.1
presents some of these factors. Ideally, an ACS registry would include pre-treatment data, data
associated with treatment, and post treatment data such as the effectiveness of rehabilitation
programs.
An ACS registry that collects comprehensive data across Australia could also be used to
develop performance indicators. Performance indicators that measure the contribution of
treatment stages to health outcomes could be used to identify best practice treatment
strategies and develop best practice guidelines. They could also be used to determine the costeffectiveness of current therapies and assist in identifying redundant therapies.
60
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table 6.1: Factors that impact on health and health outcomes
Individual
Geographical
Institutional
Type and severity of condition
Residence of patient
Capabilities of ambulance
treatment
Co-morbidities (number and
types)
Geographical status of hospital
(e.g. urban versus rural)
Procedure type and complexity
Post operative complications
Health region
Devices and prosthetics used
Morbidity and mortality within
one year of treatment
State/territory
Qualifications and experience of
staff
Health behaviours
Access to treatment (symptom
to treatment times)
Hospital facilities (e.g. surgical
and post operative care)
Biomedical factors
Access to hospital
Hospital type (e.g. teaching)
Psychosocial factors
Access to catheterisation
laboratory
Rehabilitation program
Socioeconomic
Access to rehabilitation
Pharmaceuticals prescribed
Demographic
Cultural
Genetic
Adherence to clinical advice and
use of medicines
Access to informal care
Co-payments
Source: Access Economics
Performance indicators could also allow comparisons to be drawn between the performance
of clinicians and institutions within, and across, health regions. This will provide an opportunity
for shared learning between clinicians and institutions identify reasons why some institutions
perform better than others, and generate greater accountability within the health care system.
Performance indicators could also assist in recognising outliers in the health care system, for
example, the best and worst hospitals in terms of outcomes.
According to Tonkin (2001) and Scott (2008), an ACS registry is expected to lead to several
advantages. These include:
61
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
■
■
Identification of trends in adverse outcomes as a result of PCI use;
■
identification of population groups that are underserved, such as Indigenous Australians,
ethnic groups, those with co-morbidities including renal disease and diabetes, and the
elderly;
■
■
■
improved management of ACS patients;
a common set of indicators and definitions used amongst ACS management
stakeholders;
clinicians and health institutions become publically accountable; and
better information for patients to make informed choices about their treatment options.
One area that a national ACS registry will need to address is the lack of data on ACS treatment
and health outcomes associated with Indigenous Australians. The most comprehensive data on
Indigenous health and outcomes collected by the ABS still only relies on four jurisdictions for
accurate Indigenous status identification. As a result, this makes it extremely difficult to
analyse general trends in the burden of disease and treatment in the Indigenous population
and impedes on the assessment of secular trends.
The high economic cost associated with ACS means there could be the potential for large
effectiveness and efficiency gains through the development and use of an ACS registry. This is
expected to lead to cost savings and better health outcomes for all ACS patients.
6.3 Rehabilitation
According to the Australian Guidelines, initiating a comprehensive cardiac rehabilitation
program post hospital discharge is important in the management of ACS, particularly in the
secondary prevention of recurrent coronary heart disease.
Evidence shows that formal cardiac rehabilitation programs following an ACS event can reduce
morbidity and mortality associated with an event, and the risk of a recurrent ACS event
(Rockson et al 2007). Outpatient rehabilitation is particularly important because hospital stays
are becoming shorter, thereby limiting the opportunities for inpatient education about risk
reduction and lifestyle changes (Ades et al 2001). Briffa et al (2005) estimated that postdischarge rehabilitation (including an exercise regime to improve function capacity, education
on lifestyle changes and pharmalogical treatment) compared to conventional care had an
incremental cost-effectiveness ratio of $42,535 per quality-adjusted life year (QALY) saved,
assuming that rehabilitation increased survival rates.27 This is within the acceptable range of
the cost effectiveness threshold set by the World Health Organisation (WHO) and the
Pharmaceutical Benefits Advisory Committee (PBAC).
Despite evidence pointing towards the cost effectiveness of cardiac rehabilitation, studies
show that outpatient care is still underutilised in Australia. For example, Scott (2003) showed
in a study of public and private hospitals in Queensland that the adoption of rehabilitation
programs was slow, with only 30% of patients referred to an outpatient cardiac rehabilitation
program after discharge. In another study of hospitals in various States by Walters et al (2008),
27
If we assume rehabilitation only impacts on the quality of life and not the length of life, then the incremental
cost-effectiveness ratio increases to $70,580
62
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
less than 11% of patients across all centres included in the study were referred to cardiac
rehabilitation.
The rehabilitation model of care generally comprises of three phases: inpatient care,
outpatient care and maintenance care. Figure 6.1 outlines one model of care for rehabilitation.
Following the inpatient clinical delivery of hospital treatment, patients should be referred to a
pathway of services post hospital discharge that extend for a period of two years to enable
permanent positive lifestyle changes. Rehabilitation programs should be designed on a case by
case basis depending on the patient’s overall risk factor profile and co-morbidities (such as
diabetes).
Figure 6.1: A model of care for rehabilitation
Rehabilitation
Program
Inpatient care
Education on
diagnosis,
procedure type,
stenting (if any)
Information on
the pathology and
anatomy of the
condition
Outpatient care
Education about
lifestyle changes
(eg dietary) and
risk factors
Follow-ups on each
patient on physical
and emotional
health after ACS
Ensure long term
medical therapy
Source: Access Economics
An important part of inpatient care is education of the patient on their diagnosis, the type of
procedure that was performed (i.e. type of stenting) as well as the time they may need off
work after discharged from the hospital. Patients should be provided with the information
necessary to fully understand the anatomy and pathology of their condition. In particular,
patients should be given appropriate information about their risk factors (e.g. smoking, high
cholesterol, overweight etc) and options for lifestyle changes to reduce the risk of an ACS
event in the future.
Outpatient care consists of various components. The most important of these are
rehabilitative and disease prevention programs (recommended for six to 12 weeks) preventing
the progression of coronary and other diseases following from ACS. There should also be
ongoing monitoring, support, education on self management, exercise and social support for
patients and their carers. A pathway of services provided for an extended period of time (up to
two years) would encourage permanent positive lifestyle changes. All programs should collect
key performance indicators and report on these.
63
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
For rehabilitation to be effective, comprehensive patient follow-up interviews after discharge
are essential. At these follow-up interviews, the patient should undergo both physical (i.e.
blood pressure, cholesterol tests, ECGs, emotional and psychological (i.e. signs of depression,
anxiety, stress, financial hardships) assessments. The psychological impact following an ACS
event is an important, but often neglected, area in the management of ACS. Thus, if patients
can better understand their conditions, it can empower them to cope with their anxieties
caused by ACS.
Returning to work can require an adjustment in duties and the conditions under which the
employee works. Workplaces can also provide an excellent environment to facilitate the
ongoing rehabilitation and lifestyle changes to prevent the reoccurrence of ACS events. No
standardised national program exists to support this extension of rehabilitation practices, and
employees and employers would benefit from such an initiative.
Another important aspect of rehabilitation involves long term therapy with a number of
medications. Table 6.2 outlines recommended medications for ACS treatment. Antiplatelet
agents including aspirin and adjunctive clopidogrel should be given to patients undergoing PCI
and for all outpatients who have had an ACS event. Education about risk-factor management
such as lifestyle changes and ensuring continued use of vasoprotective medication can extend
overall survival rates and reduce reoccurrence of ACS and the costs associated with
subsequent treatments (Briffa et al 2005).
Table 6.2: Recommended medications for ACS treatment
Medication
Use
Aspirin
Blood thinning antiplatelet agent
Clopidogrel
Blood thinning antiplatelet agent used if stenting is
present
β-Blockers
In the event of a heart attack
ACE inhibitors
Regulate blood pressure
Statin
Lower cholesterol
Source: NHF and CSANZ (2006)
Rehabilitation also needs to involve a specialist nurse led multidisciplinary team of
psychologists, dieticians, physiotherapists, exercise psychologists, pharmacologists and
doctors. Once a full clinical assessment of patient’s health post-discharge has been completed,
the patient can set goals for rehabilitation that are within the guidelines and develop an
individualised dietary and exercise plan to prevent the progression of ACS or other coronary
heart diseases.
There is a need for adequate resourcing of cardiac rehabilitation centres and hospitals to
ensure places for patients to attend and complete rehabilitation programs, as well as
strategies to improve compliance and adherence their long-term medications for the total
rehabilitation program to be effective. There are several reasons for patients not attending
rehabilitation programs or dropping out of a program or therapy, some of these include:
■
■
time restrictions imposed through work commitments;
transportation and mobility concerns, especially for the elderly and disadvantaged
groups;
64
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
■
■
communication barriers for cultural and linguistically diverse groups; and
co-payment costs associated with some rehabilitation programs.
Women have lower participation rates for angiograms than men, as well as lower involvement
in and completion rates of rehabilitation programs. Specific strategies are needed to increase
the uptake of both angiogram rates and to place them in suitable cardiac rehabilitation
programs.
These issues all hinder the effectiveness of cardiac rehabilitation and need to be addressed for
outpatient and maintenance care to reach its full potential. Redfern et al (2007) found that
patients who did not attend standard cardiac rehabilitation after discharge were commonly in
the high risk factor groups (such as high cholesterol, overweight or obese, a smoker or have
diabetes) or had poor knowledge about risk factors associated with ACS. Balady (2007) have
found that factors shown to increase the compliance and adherence to cardiac rehabilitation
programs include; having a strong medical recommendation to attend, meeting a member of
the rehabilitation team whilst an inpatient, having an appointment or discharge plan for
accessing local cardiac rehabilitation services, offering a mode of service delivery that suits the
person’s schedule (e.g. full day programs, weekend programs, early morning classes). All these
would allow patients to interact with other who have similar problems and reinforce the
rehabilitation process.
Senes and Penm (2007) also found that a large proportion of patients discontinue their longterm medications despite their effectiveness in preventing a second heart attack or chest pain
Stafford (2003). The reasons for therapy discontinuation are not clear, but may be due to the
cost of medications, the side effects associated with a medication, poor understanding of their
condition, and poor communication and coordination between health workers and patients
(Senes and Penm 2007). Therapy discontinuation by patients increases the likelihood of a
repeat ACS event. Subsequently, this increases the burden of disease and the costs associated
with ACS. Further work relating to compliance and adherence within the framework of the
Quality Use of Medicines in Cardiovascular Health project will enhance understanding of the
reasons, and strategies for improvement. The UK’s National Institute of Health and Clinical
Excellence (NICE 2009) advocate both a “bottom-up” approach targeting consumers and
health professionals along with “top-down” (government) engagement.
Participation in rehabilitation should ideally be on a patient opt-out basis rather than an opt-in
basis. If patients have limited access to formal rehabilitation services, individualised home
based rehabilitation programs should be developed.
6.4 Next generation antiplatelet agents
Antiplatelet drugs can reduce the likelihood of blood clots by targeting and inhibiting the
activation of chemicals that cause platelet aggregation. They are recommended by the
Australian Guidelines for the primary and secondary prevent of ACS, and in recent years have
drawn the most attention in pharmaceutical research for ACS, hence the focus in this study.
There are other evidence-based pharmacological therapies proven to prevent the progression
and recurrence of ACS (see Figure 6.2). Of these, there have only been mild improvements in
statins in the form of higher potencies and increased dosing for ACS patients.
65
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Generally, platelets circulate in the blood to form blood clots (through platelet aggregation)
and stop ongoing bleeding rapidly (for example, when you have a wound). Platelet activation
and aggregation is triggered by specific receptors for each physiological stimuli (including vWF,
Collagen, ADP, Thrombin and Thromboxan A2; see Figure 6.2). When these blood clots form in
coronary arteries, it blocks the flow of blood to the heart. In general, antiplatelet drugs assist
blood clots by targeting and inhibiting the activation of chemicals that cause platelet
aggregation. These are recommended by the Australian Guidelines for the primary and
secondary prevent of ACS.
The effectiveness of antiplatelet drugs in preventing further ischemic events and death is
widely accepted (Antithrombotic Trialists’ Collaboration 2002; Krotz et al 2008). However,
these have also been associated with increased bleeding, and the rates of recurrent ischemic
events still remain quite high (Becker et al 2009). As seen in Figure 6.2 there are still numerous
triggers that activate platelet aggregation. As such, it is possible for further gains to be made
via novel antiplatelet drugs that take advantage of these other receptors in inhibiting platelet
aggregation without increasing the risk of excessive bleeding.
Aspirin is the most widely used antiplatelet therapy and the Australian Guidelines recommend
that it be prescribed indefinitely (in the absence of any contraindications). The Australian
Guidelines also recommend that Clopidogrel be prescribed for up to 12 months after an ACS
event, the exact duration of which depends on the presence and type of stenting. Both drugs
work by inhibiting the chemicals that cause platelet aggregation. The dosage, efficiency and
indications of established antiplatelet agents need to be constantly re-evaluated to improve
their effectiveness.
66
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Figure 6.2: Signalling pathways that activate platelets
Source: Krötz et al
A number of new generation antiplatelet drugs are currently being evaluated for their efficacy
and safety (see Table 6.3). These drugs target previously unrecognised mechanisms of action
for inhibiting platelet activity. Prasugrel, Cangrelor and AZD6140 are ADP P2Y12 inhibitors, the
latter being reversible. SCH 530348 will be a completely new class of antiplatelet agents called
thrombin receptor antagonists (TRAs). It blocks the PAR-1 platelet receptor from binding to
thrombin, which is the most potent platelet agonist and thereby hinders platelet aggregation.
Table 6.3: Status of new antiplatelet agents
Agent
Clinical
studies
Mechanism of antiplatelet activity
Current status
Prasugrel
JUMBO-TIMI
26; TRITONTIMI 38
Irreversible ADP P2Y12 inhibitor (oral)
Phase 3 results
published
Cangrelor
Storey;
Jacobsson
Reversible ADP P2Y12 inhibitor (only
available intravenously)
Phase 2/3
AZD6140
Husted;
DISPERSE-2
Reversible ADP P2Y12 inhibitor (oral)
Phase 2/3
SCH 530348
Moliterno
PAR-1 thrombin receptor antagonist
Phase 2/3
Source: Wadhawan (2009) and Smyth et al (2009)
67
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Clinical studies have shown some improvements to current therapies. For example, Prasugrel
has been found to have a greater and a quicker inhibitory effect on platelet aggregation
(Wadhawan 2009). However, these drugs are still being tested for their safety as one side
effect of inhibiting platelet aggregation is a high risk of excessive bleeding. Other possible
complications include lack of efficacy in some patients, significant variability in patient
response and potential resistance to the drug (Shalito et al 2009).
Furthermore, various studies are looking at the effectiveness of combining various agents.
Hankey and Eikelboom (2003) found that the addition of clopidogrel and glycoprotein IIb/IIIa
reduces the risk of serious vascular events among patients with NSTEACS and among patients
undergoing PCI by up to 30%. SCH 530348 is also being tested for use with current therapies
rather than in place of them (Wadhawan 2009).
If new drugs are found to be safe, lead to substantial improvements in effectiveness, and are
cost effective, they should become an important part of future ACS treatment in Australia.
Access Economics
June 2009
68
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Appendix A: Epidemiology estimates and projections
Table A.1: Male AMI age standardised separations per 100,000
1998
1999
2000
2001
2002
2003
2004
35-39
37.7
40.8
46.7
43.5
70.9
46.4
42.0
40-44
102.0
116.3
92.8
79.3
98.0
79.8
67.9
45-49
186.8
168.0
184.6
165.3
201.5
202.3
197.9
50-54
313.4
293.0
290.3
273.3
302.5
299.6
312.8
55-59
465.2
385.4
404.4
422.2
485.1
379.3
343.9
60-64
655.9
739.5
569.6
506.0
539.7
575.0
493.8
65-69
885.4
869.1
1025.7
714.6
771.2
800.9
731.8
70-74
1401.7
1209.1
1108.4
1111.8
1330.4
1094.0
1077.4
75-79
1574.5
1737.0
1763.5
1629.3
1607.9
1754.9
1510.4
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
Table A.2: Female AMI age standardised separations per 100,000
1998
1999
2000
2001
2002
2003
2004
35-39
13.0
5.5
5.6
7.3
9.3
9.3
20.4
40-44
28.3
7.5
25.9
23.7
16.2
12.3
27.9
45-49
32.2
33.4
36.6
34.1
30.0
37.1
43.7
50-54
77.9
64.8
88.1
72.7
73.6
74.1
75.4
55-59
113.4
111.2
127.4
83.9
93.3
99.1
109.9
60-64
204.7
155.7
177.6
167.9
187.1
195.0
132.0
65-69
403.5
382.5
328.2
341.6
315.9
352.3
273.2
70-74
584.8
669.5
568.0
461.7
614.8
520.4
580.3
75-79
1000.1
849.9
835.3
1067.5
1039.8
1051.8
919.8
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
69
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table A.3: Male unstable angina age standardised separations per 100,000
1998
1999
2000
2001
2002
2003
2004
35-39
56.6
18.6
24.3
37.8
38.3
21.3
22.9
40-44
111.8
77.5
77.7
75.5
81.4
81.6
78.6
45-49
211.2
198.0
160.8
195.2
156.0
165.3
178.8
50-54
345.7
275.4
288.2
320.5
288.2
258.8
304.6
55-59
513.4
446.1
531.5
544.4
396.2
357.9
402.7
60-64
975.7
716.0
694.1
624.4
704.7
578.3
639.5
65-69
1177.4
1019.5
1100.3
1150.8
968.4
788.0
837.5
70-74
1531.2
1336.7
1481.4
1383.2
1361.7
1177.3
1082.6
75-79
1962.1
1729.5
1586.4
1727.2
1601.0
1409.2
1497.4
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
Table A.4: Female unstable angina age standardised separations per 100,000
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
1998
1999
2000
2001
2002
2003
2004
13.0
20.7
66.4
126.6
236.8
361.3
611.9
821.6
1441.3
9.2
26.1
47.1
138.8
228.8
381.3
641.8
915.2
1238.8
13.0
14.8
42.3
112.4
215.4
359.0
538.3
908.8
1264.1
12.9
38.2
53.0
112.1
196.8
314.3
471.3
769.5
1148.8
11.1
14.4
50.6
96.0
165.4
249.5
433.8
689.4
1147.0
11.2
17.6
52.0
92.2
156.1
252.2
384.7
692.4
988.7
16.7
27.9
65.5
85.3
147.3
312.3
370.7
644.8
971.5
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
Table A.5: Male ACS age standardised separations per 100,000
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
1998
1999
2000
2001
2002
2003
2004
94.29
213.83
397.95
659.14
978.6
1631.62
2062.73
2932.9
3536.54
59.39
193.86
365.98
568.43
831.56
1455.51
1888.57
2545.76
3466.43
70.96
170.49
345.38
578.46
935.9
1263.72
2126.07
2589.75
3349.81
81.28
154.72
360.5
593.81
966.53
1130.41
1865.43
2494.91
3356.41
109.19
179.33
357.51
590.75
881.23
1244.37
1739.6
2692.13
3208.88
67.63
161.42
367.59
558.43
737.16
1153.36
1588.87
2271.31
3164.05
64.87
146.44
376.7
617.38
746.52
1133.31
1569.3
2160.06
3007.81
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
70
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table A.6: Female ACS age standardised separations per 100,000
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
1998
1999
2000
2001
2002
2003
2004
26.03
48.99
98.64
204.43
350.18
565.95
1015.39
1406.34
2441.32
14.72
33.6
80.51
203.58
339.95
536.99
1024.31
1584.7
2088.66
18.53
40.62
78.88
200.49
342.74
536.62
866.52
1476.78
2099.46
20.19
61.9
87.05
184.81
280.74
482.21
812.83
1231.23
2216.32
20.37
30.51
80.6
169.6
258.69
436.62
749.69
1304.21
2186.73
20.56
29.9
89.08
166.31
255.16
447.22
736.96
1212.77
2040.49
37.16
55.73
109.22
160.67
257.21
444.23
643.85
1225.07
1891.28
Note: Based on age groups between 35 and 79 years old in Perth Statistical Division, Western Australia
Source: Emeritus Professor Michael Hobbs, pers. com. 07 May 2009
Chart A.1: Male AMI separation rates and trends
Age standardised rates per 100,000
1,800
y = 39.772e0.4061x
R2 = 0.9212
1,600
1,400
1,200
1,000
800
600
400
200
0
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Source: Access Economics calculations
71
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart A.2: Female AMI separation rates and trends
Age standardised rates per 100,000
1,800
y = 8.9208e0.4968x
R2 = 0.9764
1,600
1,400
1,200
1,000
800
600
400
200
0
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Source: Access Economics calculations
Chart A.3: Male unstable angina separation rates and trends
Age standardised rates per 100,000
1,800
y = 17.414x 2 - 39.872x + 68.297
R2 = 0.9874
1,600
1,400
1,200
1,000
800
600
400
200
0
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Source: Access Economics calculations
72
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Chart A.4: Female unstable angina separation rates and trends
Age standardised rates per 100,000
1,800
1,600
y = 10.022e0.455x
R2 = 0.9584
1,400
1,200
1,000
800
600
400
200
0
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
Source: Access Economics calculations
73
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table A.7: Actual and projected ACS separation rates for males
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90-94
95-99
100+
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
94
214
398
659
979
1632
2063
2933
3537
5867
8306
11865
17141
25064
59
194
366
568
832
1456
1889
2546
3466
5438
7722
11040
15932
23235
71
170
345
578
936
1264
2126
2590
3350
5113
7255
10380
14999
21904
81
155
361
594
967
1130
1865
2495
3356
5030
7048
9947
14181
20446
109
179
358
591
881
1244
1740
2692
3209
4814
6600
9069
12526
17425
68
161
368
558
737
1153
1589
2271
3164
4785
6799
9717
14002
20366
65
146
377
617
747
1133
1569
2160
3008
4535
6390
9064
12975
18763
73
137
360
576
734
985
1482
2132
2965
4293
6003
8431
11926
17014
72
128
359
571
700
909
1394
2033
2882
4099
5729
8040
11358
16175
71
119
357
567
667
833
1306
1934
2799
3911
5466
7666
10819
15387
70
110
355
562
633
758
1218
1835
2716
3719
5201
7296
10296
14635
69
101
354
557
600
682
1130
1737
2632
3533
4947
6946
9807
13940
Source: Access Economics calculations
74
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Table A.8: Actual and projected ACS separation rates for females
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85-89
90-94
95-99
100+
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
26
49
99
204
350
566
1015
1406
2441
5091
9026
16012
28417
50458
15
34
81
204
340
537
1024
1585
2089
5856
10974
20578
38608
72477
19
41
79
200
343
537
867
1477
2099
5157
9401
17146
31282
57097
20
62
87
185
281
482
813
1231
2216
4145
7207
12533
21801
37933
20
31
81
170
259
437
750
1304
2187
4446
8025
14484
26140
47178
21
30
89
166
255
447
737
1213
2040
4159
7419
13239
23630
42182
37
56
109
161
257
444
644
1225
1891
3088
5063
8305
13626
22362
29
43
96
150
222
401
578
1140
1901
3088
5181
8692
14584
24469
31
44
98
142
203
378
513
1088
1841
2790
4622
7658
12688
21025
33
44
100
134
184
355
449
1036
1782
2505
4097
6703
10968
17951
34
44
102
125
165
332
384
984
1723
2231
3603
5821
9407
15211
36
44
104
117
146
309
320
932
1664
1965
3134
5001
7987
12766
Source: Access Economics calculations
75
The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
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Notes
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The economic costs of heart attack and chest pain (Acute Coronary Syndrome)
Notes
86
Information about Acute Coronary
Syndrome and its treatment
Baker IDI Heart and Diabetes Institute
www.bakeridi.edu.au
Tel: 1300 728 900
Heart Support Australia Ltd
www.heartnet.org.au
Tel: 61 2 6280 7211
Heart Foundation
www.heartfoundation.org.au
Tel: 1300 36 27 87
People with Acute Coronary
Syndrome are at greater risk of a
second heart attack or chest pain.
It is critical that once a person has
had a heart event they maintain
their medication, rehabilitation and
healthy lifestyle changes life-long to
prevent another serious event. An
ongoing commitment to research
will also help to better understand
the risk factors, the need for early
intervention, and help to prevent the
onset of serious disease.
Adoption of healthy lifestyle
behaviours including regular exercise,
good nutrition and co-prescribed
medications with participation in
rehabilitation programs can all help
prevent further heart attacks or chest
pain. Join your local Heart Support
Australia branch for self-management,
support, information, encouragement
and motivation and achieve your
optimum health potential.
Your heart needs care for life.
Everyone can do something to help
prevent themselves getting heart
disease. Making small, steady
changes to your lifestyle can help to
prevent you getting heart disease.
Don’t ignore the warning signs of heart attack!
Get help fast. Every minute counts. Call 000.