Download MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK

MAPPING THE
HEALTHCARE DATA
LANDSCAPE
IN DENMARK
Report
Authors
Vinay Venkatraman
Priya Mani
August Ussing
August 2015
About this report
This report is prepared by Leapcraft Aps on request by
Copenhagen Healthtech Cluster, Copenhagen Capacity
in May 2015.
The premise of research has mainly been intensive
desk research done over 8 weeks and a combination
of Leapcraft’s experiences on working with big data
solutions for the Danish market. We have tried to
ensure that the list of medical databases referred to
and listed in this report are still active and that the list
itself is exhaustive. However it is not a comprehensive
or complete list by any means.
Wherever possible and relevant, statements about
institutions and organisations have been borrowed from
their own website to ensure the correct interpretation
of their role and activities.
DISCLAIMER : All material presented in the report is
meant to be indicative and to inform Copenhagen
Healthtech Cluster’s research needs. This report is not
for public use or research purpose.
MAPPING THE
IN IN
DENMARK
MAPPING
THEHEALTHCARE
HEALTHCAREDATA
DATALANDSCAPE
LANDSCAPE
DENMARK
CONTENTS
CONTENTS
Pg.
04
05
05
06
1. Introduction
1.1 Background
1.2 Identity as a National Infrastructure
2. The Landscape of Danish healthcare
2.1 The State
2.1.1 Danish Regions
2.1.2 Municipalities
08
2.2 Data Infrastructure
2.3 Data Administrators
2.3.1 Documentation- General Practitioners (GP)
10
2.3.2 Who generates what type of data?
2.3.3 Types of documentation
2.3.4 Registration Practices
14
15
2.3.5 Double Registrations and Inconsistencies
2.3.6 The role of Medcom
2.4 The Data Documentation Initiative
2.4.1 Platforms, Integration and connectivity
16
2.5 Data for citizen access
2.5.1 Sundhed.dk
2.5.2 e-Journal
17
3. Sources of information
3.1 National registries
19
20
22
3.1.1 Clinical databases
3.1.2 Cohort Studies
3.1.3 Genome Data in Denmark
3.1.4 Biobanks
23
3.1.5 A note on Economic and Social Data
4. Accessing the health data
4.1 Legislation
24
4.2 The Danish Data Protection Agency : Datatilsynet
4.3 The Danish Data Archive: Dansk Data Arkiv
4.4 Danish Research Ethical Council: Den Nationale Videnskabsetiske Komité
4.5 The Danish Council of Ethics Etiskråd
4.6 Challenges in intersectoral research
25
28
5. Society as a Cohort
30
6. Mapping the Databases
32
7. Contextual extrapolation of Healthcare Data
36
8. Conclusion
38
9. The Next Steps
5.1 Demographic focus : Women, Children, Elderly & Veterans
Appendix
List of National Registers : Data quality, period of collection and contact.
List of Clinical Databases : Data quality, period of collection and contact.
List of Cohort Studies : Data quality, period of collection and contact.
List of Centers of Genome Research : Data quality, period of collection and contact.
3
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
1.Introduction
This report aims to understand the known sources of
healthcare data in Denmark and see how this data is
connected and can be corelated to each other and other
social data to make it meaningful to more stakeholders
in the healthcare sector, the healthcare industry of
diagnostics, medical devices, private healthcare and
insurance and ofcourse, to citizens themselves. The
report also outlines the legislative and ethical guidelines
around usage of healthdata in Denmark through
scenarios of use to highlight challenges in information
exchange at intra- and inter-sectoral levels.
Beginning with a comprehensive layout of the Danish
social welfare system which is the primary link between
the citizen and state and thus a robust database, the
report in chapter 2 introduces all the public sector
players who collect, collate and use health data. Points
of contact and interaction in the system that generate
this data have been discussed in detail along with
possibilities for citizen access to both personal and
public data. A short overview of the procedures around
retrieval and use of data for research access as well
as commercial use (including research for commercial
pursuits) is presented. While the registrations are
intensive and often exhaustive, the formats themselves
are not aligned and hence this chapter delves deeper
into the issues of data integration and discusses in
further detail the registration practices, even at the
most basic patient - doctor level, that essentially
generates this data. This analysis helps outline the
barriers and challenges in the healthdata landscape as
it is now, and can help in improving the framework for
future databases.
Chapter 3 discusses in further detail the various
categories under which this healthcare data is collected
describing the periods of time and population breadth
covered in these, thus reflecting on the quality of the
available data. The various registers are classified
in detail here covering clinical data registers, quality
indicator registers and tissues and bio materials sample
databases.
Privacy around personal data is given great importance
in Denmark, giving great credibility to health data
generated here. Chapter 4 lists the various agencies
that work towards keeping this system secure in good
detail giving one an overview of the legal framework for
potential cross sectoral research projects and further
data mining. The challenges to accessing information
stored in specific registers at both intra- and inter
sectoral levels has been outlined.
Chapter 5 looks at possibilities to synthesise the
various data sources and make new sense from it. After
mapping existing efforts, the report looks at potential
new lenses to see the same data like demography,
general wellbeing and chronic illnesses. An attempt has
been made to see the entire landscape of data sources
mapped on a lifetime. As we see this historical data
collection activity as a mass of data on specific factors,
it reveals evolution of lifestyle syndromes, focus of
the healthcare sector and policy making, gender based
tendencies etc. Analysis can take take a predictive turn
as the map can be interpreted across many indicators.
Using the body as a spatial metaphor in chapter 6, the
various registers are mapped giving one an overview of
areas of keen research interest, funding and of value
to population studies. All kinds of registers are notably
mapped here, stressing the volume of data that exist for
a particular area of study.
A detailed contextual extrapolation of data use is
explained in chapter 7 citing potential use case scenarios
and the way forward to realise these mentioning the
different stakeholders and a possible road map.
The report concludes with a road map for use of this
healthcare data combined with other rich socioeconomic data collected in Denmark for welfare projects
and private sector projects.
5
1.1 Background
1.2 Identity as a National Infrastructure
The Nordic countries have been front runners in the
collection of data on births, deaths, disease and
its control. Data on education and employment,
immigration and emigration have also been duly
collected as it was and is the backbone of the welfare
state model. Growing population, tax collection and
disbursement of complex welfare funds pushed the
state’s early foray into digitisation of data. Thus very
high quality data of the whole society is available for
varying, yet long periods of time.
Using a unique personal identification number assigned
to all persons with a permanent residence in Denmark
(CPR-number)5, it is possible to link data from one or
more registers or from other sources with registerbased information at an individual level 6. It was
established in 1968 and contains the name, address,
personal identification number, date and place of birth,
citizenship and other information about the country’s
citizens and residents.
For example, information on causes of death has been
collected since 1875 in Denmark1, information on
compulsory schooling and continuing education are
available for cohorts born after 19452, information on
twins are available for cohorts born after 1870 3, and
cancer incidence has been registered for the whole
country since 1943 4 .
Additionally, each Danish firm has a unique identification
number, the CVR Number 7, which makes the link between
a firm and employees possible 8 . Thus, the access to
information on important exposures, confounders
such as education, income, and ethnicity and various
health-related outcomes offers immense opportunities
for doing epidemiological research on, for example, the
association between occupational exposures, disease
incidence, mortality, social issues, clinical indicators,
and rehabilitation.
Additionally, all data pertaining to real estate properties
in Denmark are maintained in the BBR 9 which includes
detailed historical data on property evaluation,
condition, renovation, ownership and pollution levels
of constructions. This indepth recording reflects
socio-economic data that can be related to population
transition , lifestyle and well being.
1
Helweg-Larsen K. The Danish Register of Causes of Death.
Scand J Public Health 2011;39(Suppl7):26–9.
2
Jensen V, Rasmussen A. Danish education registers. Scand J
Public Health 2011;39(Suppl 7):91–4
3
Skytthe A, Christensen K, Kyvik K, Holm N. The Danish Twin
Registry. Scand J Public Health 2011;39(Suppl 7):75–8.
4
Gjerstorff M. The Danish Cancer Registry. Scand J Public Health
2011;39(Suppl 7):42–5.
5
CPR- Det Centrale Personregister https://cpr.dk/
6
Pedersen CB. The Danish Civil Registration System. Scand J
Public Health 2011;39(Suppl 7):22–5.
7
CVR- Det Centrale Virksomhedesregister http://datacvr.virk.
dk/data/
8
Petersson F, Baadsgaard M, Thygesen LC. Danish registers
on personal labour market affiliation. Scand J Public Health
2011;39(Suppl 7):95–8.
9
BBR - Bygnings og Boligregisteret - The Building and Housing
Register. www.bbr.dk.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
2. The Landscape of Danish
Healthcare
The layout of the Danish healthcare system and the
Danish political system forms an important basis for the
work on eHealth in Denmark. Health care in Denmark is
based on two main principles:
Free and equal access to public health care. This
includes general and specialised practitioner services
and services at all public hospitals. Dentists and outof-hospital medicines and some therapies are provided
under private or co-payment models on a case basis.
Universal coverage. All residents in Denmark are
entitled to public health care benefits in kind.
The public health care system is organised in two main
sectors: primary health care and the hospital sector. The
primary health care sector deals with general health
problems and care and consists primarily of general
practitioners, practising specialists, practising dentists,
physiotherapists and home nursing. Primary health care
also includes preventive health schemes, public health
care and dental care for children.
The hospital sector deals with medical conditions that
require specialised treatment, equipment and intensive
care. A general practitioner (GP) must refer the patient
to a hospital for examination and treatment unless it
is a question of an accident or acute illness. Usually
it is necessary to be referred by a GP for treatment by
a specialist. Since 1993, patients have had the right
to choose between all public somatic hospitals for
treatment. An extended free choice, since 2002, has
given patients the right to choose a state financed
treatment at a private hospital if waiting times at the
recorded in the BBR are nationwide registers pertaining
to all citizens and residents of Denmark and established
protocols means the extrapolation of all this data
with a single identification number is possible, but not
explicitly done today. The data is informative and forms
the basis of nearly all register based researches in the
country. The data is gathered and accessible nation wide
and a large part of this (except the CPR number itself) is
available for research and commercial use and further,
the anonymisation of data, partly or wholly is possible.
Aggregated data and statistics from these registers is
made public.
2.1.1 Danish Regions
The Danish Regions coordinates the common interests
of the 5 regions at the national level and negotiate the
annual financial framework for the regions with the
government as well as enter into agreements with the
private practising sector including GPs and dentists.10
Public hospitals and contracts with all GPs are the
undertaking of Danish Regions (Danske Regioner)11. The
data collected is currently from the primary healthcare
and the hospital sector which use different platforms
and registration protocols. Yet, the data collected is
almost entirely digitised thus generating an intense, deep
pool of e- health records pertaining to every individual’s
healthcare history. While the data can be transferred
across systems, the format is still text documents. The
Regional eHealth Organisation (Regionernes SundhedsIT organisation – RSI, est. 2010)12 accelerates and
coordinates the implementation of eHealth across
the five regions. All projects, collection of data and
maintenance of databases are carried out with one of
the regions as the main principal.
2.1.2 Municipalities
public hospitals are too long.
The administrative break up of the between:
1. The State
2. Danish Regions (Danske Regioner)
3. Municipalities (Kommune)
The Sundhedsdatastyrelsen, part of the Sundheds- og
Ældreministeriet is the agency for the National Sundhed
IT (NSI) that until August 2015 was part of the Statens
Serum Institute.
2.1 The State
The CPR and CVR registers along with property data
The regions are divided into 98 municipalities
(Kommuner) and are responsible for a wide range of
health services like local and specialised dental care
and rehabilitation preventive treatment, homecare,
nursing homes, rehabilitation (not hospital), treatment
of alcohol and drug abuse, social psychiatry and
physiotherapy.13 Thus the municipalities collect data on
various socio-economic indicators giving deep insights
into every individual where therapy and chronic care at
the municipality level can thus be linked to various other
municipality activities such as education, work place
conditions, tax collection, welfare schemes.
7
Illustration 1: The Landscape of Danish Health Care - Infrastructure & Access
The nation wide infrastructure is continuously recording personal data at
the state (geo-bio data), region (e-health records) and municipality levels
(e-care records). The data, specifically, healthcare data is recorded in
national registers, tissues and samples are collected in bio banks and data of
specific health conditions is actively recorded in clinical databases, by active
participation and inactively by course of treatment in hospitals.
Access to the data is made available both for personal use (one’s own
data) and is systematically anonymised at various resolutions for research
purposes. This infrastructural landscape is well integrated ensuring every
instance of interaction between the state and the resident is documented
both qualitatively and quantitatively.
Hospitals
ECR
EPR
Lab, Imaging
sytems
chronic
care
Electronic
Care Record
Electronic
Patient Record
BBR
Building & Housing
Register
Municipal
Infrastructure
Regional
Infrastructure
National Shared
Infrastructure
State / Intra
Governmental
E Medical Records, with
education,housing, employment
records
Secure Data
National IT,
Architecture,
Standards,
CPR &
Civil Registration
System
INFRASTRUCTURE
CVR
Central Virksomhed
Register
National
Clinical
Clinical
Registers &
Databases
Databases
Services
Biobanks
Research
DOCUMENTATION
Registeries, tissue samples, databases
Secure Data
Danskerne
Sundhed
Denmarks
Statistics
ESundhed
Healthcare
Professional
ACCESS
Research
Doctors
Citizen
Aggregated / Inter register Research
Open Data
Sundhed.dk
Citizen
Doctors
Personal health records, hospital
journals, reports
Secure Data
INTERACTION
5 regions
http://www.medcom.dk/dwn5350
www.regioner.dk
12
http://www.regioner.dk/sundhed/sundheds-it/rsi
13
http://www.ikas.dk/IKAS/English/The-Danish-healthcaresystem.aspx
10
11
96 Municipalities
3500 GPs
Commercial
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
2.2 Data Infrastructure
2.3. Data Administrators
All the health databases are administered by a data
manager who works within the Regions Competence
Center. Data entry for some databases is directly done
into the nationwide register, while some others are
maintained in regional registers which in turn plug into
the nation wide register. There is double documentation
of some variables in this case.
The Regions’ Clinical Quality Development Programme
(Regionernes kliniske Kvalitetsudvikling Program,
RKKP)20 represents infrastructure supported nation
wide clinical databases, Danish multidisciplinary
Cancer Groups (DMCG) and centers of epidemiology,
biostatistics, health informatics and clinical quality.
The program’s primary objective is to ensure continued
improved utilisation of the nationwide clinical
databases It was formed in Sept. 2010 and has since
focused on ensuring the framework for prioritisation
and management of databases; better use of existing
data / reduction of data entry tasks; standardisation
of inputs and outputs in relation to databases; product
development and proper method development. The
RKKP is located in Århus. The five regions have their own
competence centers for clinical epidemiology and they
work together with the Joint Secretariat (the RKKP).
Competence centers have been established in all the 5
regions and they oversee the IT requirements of each
database, identify relevant clinical content, workflows,
IT advice and offer data analysis validated by statistical
epidemiological principles. There are 3 competence
centers for register based Epidemiology Studies while
the other 2 are focussed on data quality and indicators.
Kompetencecentre for Epidemiologi & Biostatistik
(KCEB)
KCEB-Nord – Located in Aarhus/Aalborg14
KCEB-Syd –Located in Odense Universitetshospital15
KCEB-Øst – Located in Glostrup as a part of the
Forskningscenter for Forebyggelse og Sundhed
(Research center for Prevention and health)16
Kompetencecentre
for
Klinisk
Kvalitet
&
Sundhedsinformatik (KCKS)
KCKS-Vest – Located in i Århus, along with RKKP17
KCKS-Øst – located in København Ø, as part of IT,
Medico og Telefoni, Region Hovedstaden
The Danish Healthcare Quality Programme ( Den Danske
Kvalitetsmodel, DDKM)18 is a national accreditation
system for quality development across the entire
healthcare sector along with methods to measure
and control this quality. The programme serves as a
method to produce continuous and persistent quality
development across the entire healthcare sector. The
DDKM aims to generate and combine data which is
already being collected in the Danish healthcare sector.
This data includes, among other things, the national
quality databases, data on adverse events, national
patient satisfaction surveys. DDKM is public and
multisectorial.
The Danish Institute for Quality and Accreditation
in Healthcare (Institut for Kvalitet og Akkreditering i
Sundhedsvæsenet) IKAS19 develops, plans and manages
the DDKM.
2.3.1 Documentation- General
Practitioners (GP)
In Denmark around 98% of the population (health
insurance group 1) are assigned to a specific general
practitioner through a list system. The GP acts as a
gate-keeper with regard to referrals to specialists and
hospitals, and services are free of charge. The remaining
2% of the population (health insurance group 2) have
chosen the right to consult any GP or practising specialist
at any time, in return for paying a substantial part of the
doctor’s fee. 21 Services to both groups are registered in
the National Health Service Register (NHSR).
The data in the register is generated through the
GP’s invoices to the Regional Health Administration.
All practices are computerised and they send an
electronic fee request containing information about
the citizens, the provider, and the type of service to
14
http://www.kea.au.dk/klinisk%20kvalitet/kompetencecenternord/kompetencecenter.html
15
http://www.ouh.dk/wm220632
16
https://www.regionh.dk/kliniskedatabaser/Sider/default.aspx
17
www.kcks-vest.dk
18
http://www.ikas.dk/DDKM.aspx
19
www.ikas.dk
20
http://www.rkkp.dk/om-rkkp/
21
John Sahl Andersen, Niels De Fine Olivarius, and Allan Krasnik.
The Danish National Health Service Register. Scand J Public
Health July 2011 39: 34-37, doi:10.1177/1403494810394718
9
Illustration 2: The Danish Healthcare Landscape: What data is collected? Who has health data? Who can access it?
Examples of databases
CLINICAL
State / Intra
Governmental
Biological data & samples
related EMR
Pato Bank
Dansk transfusionsdatabase
PKU Registret
National BioBank
Cause of Death Register
ADHD databasen
Dansk Føtalmedicinsk Database
Organdonationsdatabasen
etc.
Citizen Research
TREATMENTS
Citizen
Research
Specific Procedures/ Conditions
related EMR
Dansk almenmedicinsk database
IVF Register
Rehabilitation Register
National Patient Register
Cancer register
Akut Kirurgi Databasen
Blærecance
Dansk Anæstesi Databaser
Dansk apopleksiregister
Dansk børnecancer register
Dansk Brystkræft Database
etc.
TREATMENTS
access
CLINICAL
NON-CLINICAL
NON-CLINICAL
Research
Citizen
Information connecting to CPR
Donorregistret
Livstestamentregister
Autorisationsregisteret
Fællesmedicinkort
venteinfo.dk
Administration af udleveringstilladelser
Mobilt Akut System Databasen (MAS)
Ventetid på danske apoteker
DEMOGRAPHIC
www.regioner.dk
Data from all hospitals
DEMOGRAPHIC
Doctors
Research
Person related data
CPR (Det centrale personregister)
Fødselsregisteret
Dødsårsagsregisteret
*Also includes other reflecting
databases like eductaion,
employment, welfare benefits etc.
AGENCIES
Doctors
PLATFORM
Here, it can be seen that the state itself is actively involved in cross sectoral
data analysis that it presents through various platforms both at the individual
level (Statens Institut for Folkesundhed) and nation wide level (Danmarks
Statistics). The data collected and managed by various agencies reflects their
focus and in turn the various kinds of research projects the data feeds into.
The data owners work under larger universities (for domain knowledge), as
national infrastructure (regions, municipalities) and independently (Statens
Serum Institute, National Biobank). Data is accessible at various resolutions
depending on the need for access ( fundamental research, industry assisited
research, self health monitoring, nation-wide health and wellness trend
monitoring etc.)
However it appears, that a holistic overview of all of a person’s personal data
is perhaps visible only to the State through the CPR number. While the linking
all the various data silos is technically possible, there are no platforms that
offer this linked socio-economic-health view to the individual.
ACCESS
Citizen
Doctors
Research Commercial
State / Intra
Governmental
At a higher demographic level, population data will need to be parsed quite
extensively to collect similar parameters for comparitive studies across
specific population studies. The nature of data, both raw and collated that is
readily available for commercial research remains however unclear.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
the Regional Health Administration every week which
passes the information on to the National Board of
Health (Sundhedsstyrelsen). The list of variables is
comprehensive. 22
The GPs occupy a central position in the Danish health
care system as the patients’ primary point of entry to
health services. The GP ensures that the patient is given
the right to treatment and right treatment and is referred
to the right professionals in the health service. The GP is
thus the coordinator and the person with professional
responsibility for referring patients to hospitals,
specialists and other healthcare professionals.
Table 1 : Who generates what type of data?
2.3.2 Who generates what type of data?
Every point of contact with the health care system
generates information and data about a patient. This
can be both quantitative and qualitative and registers
are maintained to that. Some of this data is of primary
nature ( raw data) and the rest is secondary data that is
derived from the registers or reflecting registers.
In the Danish context, most of the healthcare is managed
by the public healthcare system, and yet a small fraction
is supplemented by the private healthcare who are
still obliged to maintain the personal heath records of
the patient during the period of treatment at a private
center. Examples of data generated are provided in the
table below. For further reading refer Sec.3 on Pg 13
Raw data generated at every touch point contributes to the bigger data pool. Here are some examples of qualitative and quantitative fields that are populated
through the data gathering process. Secondary data is generated by numerous sources that service the larger healthcare industry. The list here is only indicative.
EXAMPLES OF
QUALITATIVE CONTENT
EXAMPLES OF
QUANTITATIVE CONTENT
General Practice records
Observations
symptoms
diagnosis
medical history
prescriptions
requisition of tests
Vital statistics
test results
Frequency of visits
Total time per case
GPs
Pharmacy records
Prescription
Compliance
Drug Interactions
Allergies
Waiting time
Frequency of order
Population health
Pharmacies, Hospitals
Electronic Care Records
Summary of point of care
Patient Satisfaction
Record of Incomplete care
Use of resources personnel, time,
infrastructure etc.
Treatments
Tests if any
Electronic Health Records
diagnoses, treatment, imaging,
Pathology, lab results,
outcomes, Treatments
Tests if any
Health Insurance records
treatment, outcomes
Private or Public health insurance
Biological samples
-
Bio banks, Hospitals
PRIMARY DATA
SECONDARY DATA
Health registers
EXAMPLES OF
QUALITATIVE CONTENT
EXAMPLES OF
QUANTITATIVE CONTENT
Costs, resources
Patient communites
(e.g Diabetes, Cancer,
psoraisis, alcohol rehab
etc.
John Sahl Andersen, Niels De Fine Olivarius, and Allan Krasnik.
The Danish National Health Service Register, Scand J Public
Health July 2011 39: 34-37, doi:10.1177/1403494810394718
22
RESPONSIBILITY
Hospitals
RESPONSIBILITY
Individual register owners
11
2.3.3Types of Documentation
2.3.4 Registration Practices
All data generated and collected can be broadly
classified under the following types. While some of
them are qualitative, some others are quantitative and
the format can be both text (.xml) and numerical values.
Typically, entering data to the central registers is handled
by secretaries who report the interaction between
the doctor and the patient. The reporting of data from
hospitals to the central records is ongoing in the patient
administration systems (PAS) systems.
Patient behaviour
Health issue, compliance with treatment, outcomes,
personal choices or preferences
Health outcomes
Medical records, hospital statistics, insurance data,
observational indicators
Longitudinal Patient records
Pathology, drug and product information, social and
environmental factors, medical history consisting
of diagnosis codes, doctor’s notes, lab reports and
diagnostic images - wounds, xrays etc.)
Resource Use
Each contact with the health care system (time waited,
spent and quality), treatments, costs etc.
Population Health
All clinical data generated under controlled randomised
trials, other structured content like lab tests, images or
unstructured content like notes, medical history etc.
Montoring devices
At home monitoring devices, personal devices, apps
that quantify the body or physiological data generated
from bed side monitors at hosiptals and other sensors.
Sales & Marketing
Data from pharmacies, sales, marketing and product
data, insurance claims etc.
Other reflecting data
Environmental data like weather, pollution, atmospheric
allergents, diease outbreaks etc.
23
http://www.sum.dk/Aktuelt/Publikationer/Analyse-afkvalitetsoplysninger-i-Danmark-juni-2010/Kapitel%204.aspx
24
ibid.
For further reading refer Sec.4.7 on Pg 24.
The decision on who is responsible for registering the
quality databases is taken at the branch level. This
means that it varies from department to department,
on whether the registrations are made by
​​ a clinician, a
nurse or a secretary. However, in most cases, doctors
or nurses in charge of the case inputs to quality
databases. 23
The input of data to the central registers typically
happens as follows:
1) The doctor collects information as part of a
conversation with the patient, or an operative procedure
and writes notes, fills out forms or dictates notes to the
secretaries.
2) The information is thus transferred to the secretaries
who in turn input the information in the patient
administrative system and edit or debug the entries.
Input of data to the clinical quality databases are
1) The doctor inputs the information - but rarely as
the collection of information happens (i.e not during a
patient visit or procedure)
2) The nurse inputs the data
3) The doctor fills out a form which is then input by the
secretary.
The most common is of course the first two options and
a conservative estimate is that 2/3rd of all information
input happens this way. 24
Recording practices in clinical quality databases can be
generally categorised into three main groups.
1) The recording is directly done into the other central
registers (LPR, pathology register, etc.) and thus there
are no independent records in the database.
2) The recording reports directly to their own database.
The same information is reported in varying degrees to
both the central registers and database causing double
registrations.
3) Combination of shared recording with central, and
separate reports.
Continued on Pg. 14
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
Illustration.3 Platforms, Flow of Messages and Quality of Data between the various stakeholders.
All messages between the different
stakholders and sectors (primary &
secondary) are marked in this flow
chart of electronic messages.
The administrators (municipality)
and online interfaces (sundhed.dk)
are also marked here as a source of
generating and receiving messages.
The digitalisation strategy in the
public sector of Denmark has intended
to reduce person based interactions
(enquiry, reporting etc.) and paper
work (intimations, collection, imposing
of fines etc.) to a bare minimum by
creating a single online interface for
this. Here, one sees only the health
sector, but a similar messaging
protocol exists in other public sectors
as well.
The nature of the messages are
both qualitative (text, like surveys,
journals, notifications, reports) and
quantitative (numerical, like pathology
reports, biological profiles etc.).
Numerous databases on quality of
healthcare are maintained reflecting
resource utilisation, costs and patient
satisfaction.
This flow chart is loosely based on a
representation of flow of electronic
messages in the health sector in the
Report “IT brings Danish Health sector
together” Pg.6, published on the public
portal sundhed.dk.
Information from medcom.dk, IKAS
and quality indicators of databases
has been added to this to include every
data point in the system, reflecting
whether they are clinical, non clinical,
and if the data reflects a economic
value or not.
The stakeholders often use multile
platforms
which
cause
some
discrepancies in data formats and
sharing and this number is indicated
on the chart as well.
In 2014, EPIC, an American solutions
provider has been chosen to overcome
the many challenges posed by non
synchronous platforms and data
formats. In the years to come, EPIC
is expected to create unanimity
between the messgaing systems
and architecture, reducing lag and
irrelevance.
2100 clinics
60
hospitals
96 Kommunes
in 5 Regions
16
15
1
PRACTITIONERS 3500 in
PLATFORMS
GP
Hospital
1
12
sundhed,dk
stakeholders
Citizen
GP
Hospital
Public Health
Insurance
Online booking of
appointments.
Online consultations
In-person visit.
Prescription renewal.
Communication to
the citizen.
Transfer of patient
records
Referral Bookings
Call for participation
in surveys, change of
doctor etc.
Change of address
Request for
Prescription Renewal.
Communication &
Information from all
Danish healthcare
services.
Access & update
journal
Requis
Lab Re
Booking report.
Discharge letters
Transfer of patient
records
Billing and
Reimbursement
Billing and
Reimbursement
Requis
Lab Re
Billing and
Reimbursement
Billing a
Reimb
Lab Re
Sundhed.dk
Data type
Clinical
Non clinical
economic
non economic
13
250
726
550 in
250
clinics
3
5
10
9
11
ed,dk
ation &
from all
thcare
date
5
Telemedicine
12
245
Requisitions
Requisitions
Lab Reports
Lab Reports
Requisitions
X Ray Referrals
Lab Reports
Lab Reports
Billing and
Reimbursement
Billing and
Billing and
Billing and
Billing and
Billing and
Billing and
Reimbursement Reimbursement Reimbursement Reimbursement Reimbursement Reimbursement
Lab Reports
Prescriptions
Referrals
Referrals
Referrals
Discharge letter
Discharge letter Discharge letter
Referrals
Discharge letter
Prescriptions
Billing and
Reimbursement
etc.
ETC.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
The registration and any duplicate entries in the
clinical databases depends on how each database is
constructed. Since there are no overarching guidelines
for building databases input fields, the area is
characterised by different solutions. Also, irrespective
of the database, typically the same variables especially
from the LPR is what is double registered. These are
about basic demographic information, administrative
healthcare information and clinical information about
diagnoses, procedures, examinations and medical
history.
2.3.5 Double Registrations &
Inconsistencies
a clinical quality database.
Over the spring of 2010, the Sundhedsstyrelsen mapped
and analysed double registrations across the system.
32 nationwide clinical databases, equivalent to 90 per
cent. of all registered patients in quality databases were
mapped. The focus was the extent to which health staff
use unnecessary time on record in quality databases,
Documentation and exchange of data in the Danish
Healthcare Data Landscape is clearly seen in the
illustration hereunder.
Illus 4. Det danske Sundhedsvæsenen
Although the data is computerised, much of the data is
manually entered and the nature of the administrative
distribution causes the same data to be entered a
multiple times. When this happens across different
platforms used in the practice, it results in different
formats of documentation, minor variations caused by
human entry and thus it can be challenging to achieve
a unified longitudinal data set without setting aside
preparatory time for parsing the data.
Part of the problem of inconsistency stems from
Denmark’s own digitalisation history. An early foray into
digitising health records while providing long periods of
data, often comes with data recorded across platforms
that do not integrate very well or possibly support the
same fields of data entry. Technically speaking, since
Denmark was a frontrunner in digitalisation of its
medical records, the data pool is inundated by a huge
challenge of legacy systems and outdated platforms.
Within the GPs alone, 16 different platforms are in
use. The hospitals use 15 different platforms which
are not the same as the ones used by GPs. Transfer of
patient data is mainly textual (.xml) based between the
systems except for when numerical data is used, for e.g.
pathology reports.
Another instance is the restructuring of the
municipalities in 2007 when 276 municipalities were
reduced to just 98, resulting in codes that don’t match.
Different collection periods, changed or altered variables
all mean that there could be issues of inconsistent
longitudinal datasets.
A double registration in this context can be defined
as data with mandatory inputs into the LPR or other
central registers but is also simulatnoeusly collected in
Primary Health Care
Practitioners
Pharmacies
Home Care
Nursing Homes
Visiting nurse
All Rehab work
XMLformat
text based
Messaging
System
Secondary Health Care
Hospitals
because the database variables are also reported to
a central repository. The variable was categorised
as a double registration only if all outcomes for the
given variable is registered in a central register. The
survey shows that annually, ​​almost 30 million. double
registrations were made between clinical databases
and central health records. Between clinical databases
and LPR / CPR alone, there were 25 million. double
registrations annually, equivalent to about 85 per cent.
of the total number of double registrations. About
75% of annual double registration takes place in five
of the clinical databases. Double registrations could be
avoided by increasing integration with data from the
central health records. 25
The Center for Register-based Research lists some
interesting challenges in the existing Danish healthcare
data.
Examples of inconsistencies include,
1) The Danish Civil Registration System (CPR) contains
http://www.sum.dk/Aktuelt/Publikationer/Analyse-afkvalitetsoplysninger-i-Danmark-juni-2010/Kapitel%204.aspx
25
15
information on permanent residence including
emigrations, immigrations and disappearances. This
is recorded in 9 different data sources with (although
minor) missing and inconsistent information, where
persons may be registered to reside at a specific address
in Denmark while also being registered as living abroad. 26
2) The municipal reform in 2007 reduced the number of
municipalities from 276 to 96 causing a difference in
codes assigned to these municipalities. 27
3) The National Patient Register (NPR) contains an
administrative database containing patient-level
information, a database describing diagnoses given
at somatic in- and outpatient departments, and
procedures performed at somatic in- and outpatients
departments. This information is contained in one
database per year, so far yielding 35 administrative
databases, 35 diagnostic databases, and 35+ databases
on procedures performed. In addition, there are some
changes in what types of information are included, as
well as inconsistencies due to varying variable lengths
between years. 28
Ref, Illustration. 4 Platforms, Flow of Messages and
Quality of Data between the various stakeholders. on
Pg. 12.
2.3.6 The role of Medcom
MedCom is a public, non profit organisation that
facilitates
cooperation
between
healthcare
stakeholders. It contributes to the development,
testing, deployment and quality assurance of electronic
communication and information in the health sector.
It is jointly financed by the Ministry of Health, Danish
Regions and Local Government Association.
Medcom sets the digitisation standards across
the industry, providing authorisation and approvals
for platforms and data exchange formats used by
professionals across the healthcare sector.
municipalities, pharmacies and private laboratories.
Messaging systems between the primary and secondary
healthcare sector are crucial and currently Medcom
oversees the approval of platforms and formats for this
service.
2.4 The Data Documentation Initiative
The Data Documentation Initiative (DDI) is an
international cooperation for setting metadata
documentation standards for describing data from
the social, behavioral, and economic sciences. Data
is unanimously expressed in .Xml and the DDI has
a specification on how metadata must be stored.
It now supports the entire research data life cycle.
DDI metadata accompanies and enables data
conceptualization, collection, processing, distribution,
discovery, analysis, repurposing, and archiving. 29
2.4.1 Platforms, Integration and
connectivity- The Danish case
While the registers and databases have an impressive
record of quality of treatments, outcomes of care and
improvement initiatives and numerous guidelines at
local, regional and national levels written over a long
period of time, a rather obvious problem of integrating all
these initiatives has surfaced. About 3500 practitioners
across 2100 clinics in 98 municipalities use 16 different
platforms to make a data entry of Primary health care.
While mostly they accept and send the same data fields,
there are differences which eventually affects the
completeness of the data.
The case is similar with the hospitals. 60 public hospitals
use 15 different platforms to record and exchange data.
The chance to leapfrog into a futuristic data repository
seems a bit challenging - both from a technological
aspect and behavioural resistance from the large
administrative work force.
Medcom ensures relevance and a strong IT
infrastructure needed for secure and coherent access to
healthcare data across the regions, municipalities and
all practitioners. They set the standards for software
platforms used by the practitioners to ensure that a
comparable depth of data is collected nation wide.
CIRRAU Advantages . www.cirrau.au.dk
ibid.
28
ibid.
29
http://www.ddialliance.org/what
26
Working in alignment with the national strategy for
healthcare digitalisation, Medcom has come to cover
telemedicine infrastructure, public health insurance,
27
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
2.5 Data for citizen access
Anyone with a CPR number can access their health data.
The portal sundhed.dk, gives access to journals and
entries made at every contact point with a healthcare
professional. This gives the individual a good amount of
personal data for basic understanding. To get overviews
on societal health data and statistics, aggregated data
is also made available for citizen use. To understand
a particular health condition, citizens can access the
portal esundhed.dk, which gives access to aggregated
data from specific, nation wide registers with a
possibility to select variables for viewing. Danmarks
Statistics offers a rich repository of annually published,
aggregated and analysed data. Danskernessundhed30
publishes its findings from nationwide surveys to
offer a big picture view of the nations state of heath
and healthcare. The Interaktiondatabase 31 describes
drug interactions and citizens are given the possibility
to check this online. Sundhed.dk also offers a huge
repository of common illnesses and treatment, therapy
and medication options for them.
2.5.1 Sundhed.dk
Sundhed.dk is an online portal that was established
in 2003 to provide a common digital entry to reliable
information about an individual’s health and the
Danish health system and at the same time create an
opportunity to provide health care professionals with
access to improved ways of communicating digitally
between each other and with patients. The partners
behind sundhed.dk are Danish Regions, the Ministry of
Health and municipalities through Local Government
Denmark (LGDK). 32 As a citizen, one can log in with their
CPR number and access their health records generated
at the GP, reports from the hospitals and any associated
pathological tests or any other contact points with
other healthcare professionals. While most records are
real time, pathological reports are still deferred by a few
weeks.
of the Danish population. Clinicians at hospitals have
access to e-Journalen directly through the hospital’s
eHR system, while GPs can access the system through
sundhed.dk. Furthermore, patients can also gain access
to their own data via sundhed.dk.
2.6 Data for research access
All large institutions concerned in the collection of
data provide an interface to apply for access to data.
Researchers are requested to furnish details of their
study for access. This procedure also applies to
other socio-economic data sources which opens up
possibilities for intersectoral research. Some databases
are more parsed and better tagged than others
depending on how the data was gathered.
As a case, consider the National Biobank that has a
repository of over 16 million biological samples. The
samples accessed by robots can be retrieved based on
multiple variables - For example, it is possible to retrieve
blood spots from diabetics of Danish origin, between a
particular age and income window, having had a case of
a broken arm, and with three children.
2.7 Data for commercial access
Commercial entities can apply for use of personal data
across sectors. Their permission of use and application
is governed by the Danish Research Ethical Council which
is the approval body for all register based research.
2.5.2 e-Journal
The e-Journalen (“e-record”) system gives patients and
healthcare professionals digital access to information
on diagnoses, treatments and notes from eHR systems
in all public hospitals. 30–40 per cent of the hospitals
also provide access to information on medicine and
sample results from laboratories. By the end of 2011, the
system contained health data on more than 85 per cent
www.danskernessundhed.dk
http://www.interaktionsdatabasen.dk
32
www.kl.dk
30
21
17
3.Sources of information
Mainly, three types of data are used by public and private
entities to steer or design healthcare products, services
and for policy making :
1. Health survey data,
2. Information about general consumption patterns
3. Administrative data generated by the healthcare
delivery system.
Data based on clinical care come from electronic health
records, clinic-based administrative datasets, and
government reimbursement datasets. Large-scale
registries are generated and maintained by the Regions,
state health authorities, professional societies,
pharmaceutical and device companies, and the
government. Clinical trials, whether publicly or privately
funded, can function as rich sources of observational
data, useful for exploring questions that go beyond their
original hypothesis. Common features of all these types
of data include an electronic format, predefined fields,
and for most, large numbers that enable robust analysis.
Data collected through these various registers, clinical
studies, pathology tests etc, can be broadly classified
as clinical and nonclinical data.
Clinical data usually refers to a real time database that
can be a data collective as any of the under:
Electronic health records - This is the most basic, yet
vital data collected at the point of interaction between
the healthcare provider and the citizen. It includes
demographic information, diagnoses, treatments,
prescriptions and medicines, pathology tests,
hospitalisation, insurance, cost reimbursements etc.
Administrative data provides statistics and
information on hospital inpatient and emergency
department utilisation.
Health insurance data includes data on all touch points
that provide a service reimbursable by the public health
insurance and details of subsidies provided on certain
treatment offers.
Disease registries contain data within a very specific
range of fields relevant to the disease type. These would
include registries for diabetes, cancer, heart disease,
asthma etc.
Health surveys could be regional or national and contain
data specifically collected for research purposes
pertaining to behaviour, diets and lifestyle, quality and
experience of healthcare etc.
Clinical trials data is registries of controlled and
randomised studies conducted by hospitals, research
centers and private companies.
Non clinical data includes psychological, behavioral and
sociodemographic factors in addition to information
about a patient's relationships, neighborhoods and
communities.
Healthcare data collected through the system reflect
economic data - data that indicate infrastructural
expenditures, medicine, treatment or therapy costs.
Information on the nationwide registers and clinical
quality databases we found, are distributed across
multiple sources, not one giving a detailed overview
of the landscape. While the National Board of Health
(Sundhedsstyrelsen) lists a majority of the national
databases, details of administrators, quality indicators
and data variables, period of data collection and access
is distributed across many websites. Hereunder is a list
of sources of information we have used to compile the
list of national health registers and clinical databases.
Refer to Table 2 for list of websites with information on
ehealth records
3.1 National registries
From 1 March 2012, all data on the state of public health
and data concerning health service activity, economics
and quality has been consolidated at, and analysed by,
Statens Serum Institut (SSI). The data is utilised for
national and local authority tasks and made available
for research and analysis purposes in the field of health.
The registries comprise data on the nation’s health,
morbidity and mortality, together with data on
healthcare sector organisation and economics. The
national registries publish statistics on a regular basis,
and offer access to data extraction. In addition, extracts
from the registries are provided for activities such as
analysis, research and planning.
Examples of National registries include, the Register
for causes of death which has information on death
and relating causes based on death certificates
issued from 1875, or the National Patient Register
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
Table 2 : Health agencies with information on clinical databases.
INSTITUTION
INFORMATION ON DATABASE
Statens Serum Institute
www.ssi.dk
e-Sundhed
eSundhed.dk
National Biobank
www.biobankdenmark.dk
Explains the biobanks in Denmark and how data from various registers can be combined.
Gives researchers online access to combined data from all the biobanks participating in the
Danish National Biobank initiative.
Datal Protection Agency
Datatilsynet
All legal requirements required to start, maintain and access registers and databases
pertaining to personal data and how they may be processed.
Kompetencecenter for Klinisk Kvalitet og
Biostatistik, Nord
www.kea.au.dk
Kompetencecenter for Klinisk Kvalitet &
Sundhedsinformatik
Competence Center for National Clinical
Databases, East
Region H
Region Hovedstaden
www.regionh.dk
List of nation wide clinical databases with format of the database explained along with
purpose, indicators, data collection, annual reports, organisational contacts, current status
and funding.
Competence Center for National Clinical
Databases, South
Center for Clinical Epidemiology
Center for Kliniske Epidemiologi
Odense Univery Hospital
www.ouh.dk
Very brief information on only national databases that are populated and maintained by the
center with details of those incharge and relevant weblinks.
Center for Register-based Research
Center for Register Forskning
nccr.au.dk
A rich repository of all nationwide registers (non-health included). Very brief information on
each, but contains contact details and organisational structure of the database.
Regionernes Kliniske
Kvalitetsudviklingsprogram (RKKP)
www.rkkp.dk
Links to clinical databses, annual reports, their own websites (in case of important ones like
diabetes or cancer)
Center for Integrated Register-based
Research
Excellent overview on application & approval procedures for inter-register research,
especially useful for interdisciplinary predictive analysis.
Some regional databases within the Capital Region are also listed.
19
(NPR) which collects information on diagnoses and
operations performed in hospitals since 1977, or the
National Health Service Register (NHSR) which since
1990, collects information from primary health care
contractors about quality of treatment and services,
or the Pathology Register which from 1997 holds data
on all pathological studies conducted by the country’s
pathology departments etc.
3.1.1 Clinical databases
A clinical quality database is a registry containing
selected measurable indicators which, based on
individual disease courses, serves to shed light on
either parts of or the overall performance standards
within the health service and outcomes for a limited
category of patients. These databases are all restricted
to a diagnostic group, a medical speciality or procedure.
This means that separate databases are maintained for
patients with conditions such as COPD, breast cancer,
cardiac insufficiency etc.
Illustration 5: Clinical Databases - Construct & Workflow
This depicts the administrative construct of clinical databases in Denmark. Each stakeholder contributes to the data quality both by intrinsic domain knowledge,
and computation infrastructure. The representation of Danish Regions in the maintainence of a database ensures nationwide outreach for data collection. The
establishment of the database itself is overseen by Datatilsynet where anyone wishing to setup a database applies for permissions and further clearance from the
the Danish Research Ethical Council. Formats for setting up the database are established by the Datatilsynet.
Regions
Steering Comittee
RKKP
Oversees resource &
experience utilisation
between competence
centers and ensures
consistent workload.
Clinical Database
Professional support to ensure
coverage, professional consensus
on indicators and necessary
acceptance of Database
performance
Regional
Competence Center
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
The data are used for monitoring the quality of
treatment in order to assess any underperformance
and potentials for improving quality of care. There are
currently approximately 60 national clinical quality
databases, which in combination cover approximately
60 categories of medical conditions.
Examples of clinical quality databases could be the
Colorectal Cancer Database which contains diagnostic,
treatment and follow up on all colorectal cancer patients
from 2001, or the Hysterectomy Database that since
2004 contains diagnostic, treatment and follow up
information on all women who undergo hysterectomy,
the Cytogenetic Register which since 1968 contains
information on persons who have undergone prenatal
chromosomal diagnostic procedures.
The clinical databases are organised under a public
authority (for e.g, the Regions) for reasons of
administrative ownership and data security and based
within a scientific institution to ensure professional
support, consensus on indicators and peer acceptance.
The databases are attached to one of three Centers for
Competence for epidemiology and Biostatistics who
provide IT and workflow advice and bring expertise on
data analysis.
3.1.2 Cohort Studies
Over the last 50 years numerous cohort studies have
been conducted providing ample opportunity for
researchers to revisit contextual data with new research
probes.
Cohort studies are often established with a specific
focus (for e.g. to study the establishment, development
or progress of a particular condition). Yet in a context like
Denmark, where personal data has been meticulously
documented and digitised for decades, cohorts assume
a new dimension. The same data can be reassembled
and also combined with other socio-economic data
pertaining to the same person to derive new findings.
An example of a broad spectrum cohort is the Danish
National Birth Cohort where children are followed
continuously through their childhood (pre-teenage
year) via qualitative questionnaires and quantitative
recordings of vital statistics at regular intervals.
This data can be understood with data on their
sensorial and lanuguage development at kindergartens,
education records at primary school, data on other
members of the family, parents income, residence etc.
which have broader implications if considered for future
socio-welfare frameworks and governmental policies.
Another such study is the Diet, Cancer and Health cohort
which in its very nature is broad, recording lifestyle and
its effect on overall onset, treatment and therapy of
cancer. Such studies could generate data points that
are relevant to other sectors such as the agriculture and
food industry, manufacturing industry at large or feed
into fundamental genome research.
The data will further reflect on the economy of persons
and their families and thus data is very valuable in the
welfare model as every instance of welfare payout (
unemployment, rehabilitation, support etc.) is only
adding burden to the system.
While these are very large scale cohorts, smaller
cohorts can be very valuable too. The Gerda Frentz
Cohort for example is not just another cancer register.
The true incidence of non melanoma cancers is a very
vital information in the nordic populations due to their
predisposition to skin cancers co-affected by their
environment (sun and UV radiation), diet and subsequent
absorption of food and importantly lifestyle factors like
sun based activities which prolongs exposure and risk.
21
Here are some of the largest cohorts conducted in Denmark:
The Danish National Cohort Study (DANCOS) is a nationally representative public health survey based on
linkage of information in the repeated Danish Health Interview surveys, 1986–2005
Diet, Cancer and Health is a Danish prospective cohort study aimed at investigating the associations between
dietary habits, lifestyle, and cancer development. The participants were recruited during 1993—1997.
The Danish National Birth Cohort (DNBC)33 aims to study the period from conception to early childhood and
examine how this period influences health conditions at later stages in life. Determinants for reproductive
failures, identifying pre- and perinatal determinants for important health problems in childhood and improving
the infrastructure for future studies of health and disease using a life-course perspective are key.
101,042 pregnant women were recruited in first trimester at first antenatal visit at the GP’s during a massive
enrolment plan between 1996-2002 and 96,986 children resulting from the pregnancies are being followed
through. 34
The Danish HIV Cohort Study(DHCS)35 collects data to study temporal changes in the demographic
composition of the HIV population. The effects of the antiretroviral therapy is recorded alongside mortality,
any new AIDS-defining events etc. All clinics treating HIV infected patients in Denmark participate in DHCS.
As treatment is restricted to eight departments of infectious diseases and medicines are delivered free of
charge, medicines cannot be purchased from pharmacies in Denmark.
The Soon-Pregnant Cohort Study 36 is a web based study investigating risk factors for delayed fecundability
and miscarriage. Women are between 18-40 years old, trying to become pregnant and not using contraceptives
or fertility treatments. Feasibility of web based cohorts is also being explored in this study.
The Danish Newborn Screening Biobank (NBS-Biobank)37 from 1976, collects blood spots of all newborns
to screen for Phenylketonuria, congenital hypothyroidism and toxoplasmosis in order to improve screening,
statistics and eventually diagnostics later in infancy.
The Gerda Frentz Cohort (GFC)38 studies the profile and true incidence of non-melanoma skin cancer and was
initiated as the registration of cancers was incomplete in the Danish Cancer Registry.
The DANVIR Cohort39 records prevalence and mortality with chronic viral hepatitis (Hep B, Hep C) and its
comorbidities with cancer and cirrhosis.
33
Data collection began in 1996, and was nationwide by 1999.
Danish Epidemiology Science Centre, Statens Serum Institut.
34
http://www.cls.ioe.ac.ukpage.27aspx?&sitesectionid
=342&sitesectiontitle=Danish+National+Birth+Cohort
35
Data collected from 1995 onwards. Department of Infectious
Diseases, Copenhagen University Hospital.
36
Snart Gravid-The Danish Web based Pregnancy Planning
study. Mikkelsen, Ellen M et al. “Cohort Profile: The Danish WebBased Pregnancy Planning Study—‘Snart-Gravid.’” International
Journal of Epidemiology 38.4 (2009): 938–943. PMC. Web. 24
June 2015.
37
Data with dried blood spots collected from 1982 onwards.
Department of Clinical Biochemistry, Statens Serum Institute
38
Data collected from 1995. Department of Clinical
Epidemiology. Århus University Hospital.
39
Data has been collected once from January 1 1995 to end
2006. Updates are planned at intervals of three years.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
3.1.3 Genome Data in Denmark
It appears that genetic research in Denmark is
not specifically funded by private firms, scientific
educational institutes or government institutions alone.
Rather, funding and support seem to be co-established
and funding is mostly to large research initiatives,
genomic efforts being a prominent path.
Genome research has benefitted with numerous public
private partnerships and efforts initiated by Danish
private companies like Novo Nordisk A/S, Carlsberg
Laboratory, Statens Serum Institute, Christian
Hansen’s Lab, Danisco, Leo Pharma, Lundbeck Pharma,
Neurosearch, Nordic BioScience Diagnostics A/S etc.
The Danish Parliament in 1991, recognising the need
for channelising research, funding and intellect in
fundamental research setup The National Research
Foundation 40 (Danmarks Grundforsikningsfond) as an
independent organisation. Funding is effected through
Centers of Excellence (CoE), but various programs and
initiatives towards the internationalisation of Danish
research is supported.
The Danish Reference Genome Project44 is a database
of 30 (of an expected 150) individual, fully mapped
genomes from the Danish population. It allows detailed
analysis of the individual genetic differences between
the individuals and is seen as a starting point for
individualised treatments in the future. The database
is small, thus providing a benchmark on who is a normal
Dane and a perceived deviation from this normal, thus
a cause of illness. The database is administered by
Genome Denmark.
Danish Platform for Large-scale Sequencing and
Bioinformatics is a collaboration between the University
of Copenhagen, the Technical University of Denmark
(DTU), Aarhus University and Aalborg University and will
co-operate with Bavarian Nordic A/S, Beijing Genomics
Institute Europe A/S and Genomic Expression ApS. This
platform brings Beijing Genome Institute (BGI) Europe
to establish what will be the world’s largest and most
elite genome research lab in the world.
3.1.4 Biobanks
Danmarks Nationale Biobank
See Appendix for List of CoE for healthcare in Denmark
Genome Denmark41 is a national platform for sequencing
and bioinformatics involving universities, hospitals and
private companies and one of their strongest research
agendas is to use genomic research for improved
efficiency of personalised treatment and healthcare
delivery in the future.
The Danish health system has routinely collected
biological material from a large number of individuals and
this is documented and physically stored at the National
Biobank. 45 The main purpose of the Danish National
Biobank is to give scientists from Denmark and abroad
overview and access to more than 16 million biological
samples in both existing and future collections.
The Center for Genomic Epidemiology42, located within
the Danish Technical University, works to set up a
central database which will provide internet based
solutions with a simplification of the total genome
sequence information and comparison. This activity
is being expanded to include microorganisms (vira and
parasites, metagenomic samples) which can be path
breaking for epidemiology studies.
The Danish Biobank Register gives researchers online
access to combined data from all the biobanks
participating in the Danish National Biobank initiative.
Through national collaboration large biobanks, based at
hospitals, universities and other research institutions in
Denmark, regularly submit data to the Danish Biobank
Register. Data from the biobanks are linked to disease
codes and demographic information from national
The Center for Biological Sequence Analysis 43 conducts
basic research in the field of bioinformatics and systems
biology. The group has a highly multi-disciplinary profile
including molecular biologists, biochemists, medical
doctors, physicists and computer scientists. CBS
represents one of the largest bioinformatics groups in
academia in Europe.
www.dg.dk
www.genomedenmark.dk
42
http://www.genomicepidemiology.org/index.html
43
www.cbs.dtu.dk
44
http://www.genomedenmark.dk/english/about/
referencegenome/
45
www.biobankdenmark.dk
40
41
23
administrative registries on an individual level.
4. Accessing the health data
Anonymous data sets are made available to researchers
around the world through a web-based search system.
So far, information from the following biobanks are
available through the Danish Biobank Registry:
While healthcare data in Denmark looks apparently well
documented and retrieval of huge volumes of data pose
no doubt, there are still technical and administrative
frameworks that regulate the access of data and its
resolution. Procedurally, some registers can be accessed
at the research institution administering the data with
due permissions while some data is on an individual
level needs approval of multiple agencies for access and
analysis. A typical approval process might involve the
Datatilsynet (Danish Data Protection Agency), Statens
Serum Institute and Statistics Denmark. Agencies
like CIRRAU facilitate in organising research within
the premise of necessary paperwork. This could take
anywhere between 12-18 months.
1. The Danish Patobank (approx. 12 million tissue
samples from national hospitals)
2. The Danish Cancer Society’s project biobank “Kost,
kræft og helbred” (samples from 57,000 cohort
participants)
3. The new DNB biobank at Rigshospitalet (50,000
samples collected annually)
For further reading refer Sec.4.6
4. The Cancer biobanks (de Kliniske Kræftbiobanker)
Samples from the Danish National Birth Cohort (300,000
samples)
5. Blood spots from all newborn Danes since 1976 (1,9
million samples)
3.1.5 A note on social and economic data
Economic and social data is collected with as much
breadth and depth as healthcare data in Denmark,
making data analysis rich and addressing multi party
needs.
The Danish Data Protection Agency and the Danish
Data Archive are still responsible for the overall
authorisation and archival of this data but the collection
is distributed at the municipality, regional and national
levels. Aggregated analysis of this data can be found
with Denmark’s Statistics and to some extent on
Danskernessundhed.dk and eSundhed.dk
4.1 Legislation
Data entry, access and retrieval in Denmark is
governed by the Act on Processing of Personal Data
(Persondataloven)46 The Act on Processing of Personal
Data (Act No. 429 of 31 May 2000) entered into force on
1 July 2000. The regulations of the Act on Processing of
Personal Data apply to the processing of personal data
if the processing is conducted for scientific or statistical
purposes.
Personal data is understood as data about a person
that directly or indirectly can be identified.
Processing is understood as all forms of handling of
data, i.e. collection, registration, storage, application,
etc. 47
However, the act does not apply to data already made
anonymous. Anonymous data is defined as any data
that cannot be traced back to an individual.
4.2 The Danish Data Protection Agency
Datatilsynet
Read the Act here: http://www.datatilsynet.dk/
english/the-act-on-processing-of-personal-data/
read-the-act-on-processing-of-personal-data/
compiled-version-of-the-act-on-processing-of-personal-data/
47
http://www.datatilsynet.dk/ As retrieved on 18th July 2015
48
www.datatilsynet.dk
46
The Data Protection Agency48 is the state authority
that oversees the Act on Processing of Personal Data.
The agency consists of a Data Council (DataRåd) - and
a secretariat. The agency maintains an inventory of all
databases maintained in the country under the category
“Fortegnelsen”. However this is not offered for public
use as a handbook or directory of databases yet.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
4.3 The Danish Data Archive
Dansk Data Arkiv
The Danish Data Archive (DDA) is Denmark’s national
social science data archive acquiring, preserving and
disseminating data generated from social science,
health science and history. Through an agreement with
the Danish Data Protection Agency the DDA preserves
data materials containing personal identifiers. The data
and personal identifiers are stored separately and a
special permit is required for the access to the data. The
DDA adheres to metadata documentation guidelines
set by the DDI. 49
4.4 Danish Research Ethical Council
Den Nationale Videnskabsetiske Komité
Under the Committee Act, it is the responsibility of the
committee system on health research ethics to ensure
that from a research ethic point of view, health research
projects are carried out in a responsible manner, and
that the rights, safety and wellbeing of trial subjects
participating in such biomedical research projects are
protected, while at the same time possibilities are
being created for the development of new, valuable
knowledge. 50 They are the single authorising body
for all register based research for both research and
commercial purposes.
4.5 The Danish Council of Ethics
Etiskråd
The Council was established in 1987 as a result of a
directive from the Parliament to advise the Parliament
and other Government agencies on new bio and gene
technologies, while creating discussions and debates
around this area. Members of the council are honorary
and elected for their experience in this field. The Council
advises and creates debate on biotechnology, which
affect human life, our nature, the environment, and
food. The Council also works with ethical issues related
to the healthcare sector. 51
4.6 Challenges of intersectoral data
access
Data transfer between sectors in many cases needs
approval from the patients. This means that while
data coverage is complete at the organisational level,
extracted databases may not reflect the true incidence
of cases. For example, an incidence of hospitalisation
will be reported to the GP only on approval from the
patient. Or a case of psychiatric treatment at a hospital
can be kept out of the patient’s journal if the patient so
wishes, and only reflected in the hospital’s own case
file. This choice of disclosure is a vital part of the trust
framework that data collection in Denmark builds on.
The role of the Act on Processing of Personal Data and
the Danish Research Ethical Council are nuanced in that
the transfer of personal data between registers (for
example, between the hospital’s register and a Cancer
Register, or the case of information on hospitalisation
being intimated to the GP ) is governed by the Act itself
while the extrapolation of data from any of the registers
is under the purview of the Danish Research Ethical
Council and prior approval is mandatory.
However, some agencies are helping bridge this gap by
facilitaing help with paper work and legislative issues.
For example, the following agencies are useful
references :
Center for Register based Research (NCCR) is a national
institution, established in 2000, and embedded in the
Faculty of Social Sciences in Aarhus in 2005, contributes
to the integration of health sciences and and social
register based research to strengthen the social
scientific use of register data. The center, apart from
advice, helps in the practical participation in researches
of this kind. 52
Center for Integrated Register-based research (CIRRAU)53
located at Århus University facilitates interdisciplinary
research in the academic areas of Social Sciences,
health sciences and elements from Natural Sciences
based on databases and biobanks within a framework
of translational population studies. Five categories of
data constitute the CIRRAU data resource:
1. The Family Relations Database
2. Economic, Social and Contextual Data
3. Prescription Data
4. Geocodes
5. Data Contributions from Participnts
http://samfund.dda.dk/dda/default-en.asp
http://www.cvk.sum.dk/
51
http://www.etiskraad.dk/
52
http://ncrr.au.dk/om-centret/
53
http://cirrau.au.dk/
49
50
25
5. Society as a Cohort
The data from various national registries and conditionspecific clinical databases are linkable with varying
degrees of effort and parsing to an individual’s level.
The challenge if any, is of data completeness. The
Danish National Health Service Register for Primary Care
(Sygesikringsregisteret, NHSR)54 contains information
about the activities of health professionals contracted
with the tax-funded public healthcare system. These
are general practitioners (GPs), practicing medical
specialists, physiotherapists, dentists, psychologists,
chiropractors, and chiropodists. The purpose of the
register, which is within the remit of the National
Board of Health (Sundhedsstyrelsen), is to document
activities in primary health care for administrative use
and to contribute to research in public health. Since
this register is concerned with reimbursements, it is
considered fairly complete. In this context, every person
with a CPR number, i.e anyone legally residing in Denmark
leaves a trackable and comprehensible trail of data on
quality of life and consumption of resources.
Presented here are three different scenarios of
viewing a person’s health data along his lifetime, which
represented aptly, presents itself as a cohort and
represented collectively, is a cohort conducted on an
entire society.
Illustration 6 : Society as a Cohort -A scenario view on how data is populated and could be accessed over a
lifetime.
A sample of a healthy person’s health data gathered through a lifetime.
Numerous screening efforts for a spectrum of conditions results in population data that is rich with health indicators that
help determine population health trends, genetic predispositions and lifestyle corelated to life stages. This scenario view
gives us an idea of how meticulously our lives are documented, even in the case of a largely healthy life with few interactions
with the healthcare system.
WELL BEING
BIRTH REGISTER
DIAGNOSIS
HOSPITAL
Patobank
Radiologiske ydelser
DRG (diagnoserelaterede
grupper)
Danes treated at foreign
hospitals (DUSAS)
Database for Geriatri
Dansk Anæstesi Database
Demensdatabasen
Landspatientregisteret
Akut mave-tarm kirurgi
databasen
Fælles akutdatabasen
Akut Kirurgi Databasen
MEDICATION
Lægemiddelstatistikregisteret
Danske medicinpriser
THERAPY
Tværsektoriel
Rehabiliteringsdatabase
Genoptræningsregisteret
http://www.ssi.dk/Sundhedsdataogit/Registre%20og%20
kliniske%20databaser/De%20nationale%20sundhedsregistre/
Sundhedsokonomi%20finansiering/Sygesikringsregister.aspx
54
GERIATRIC
Dansk Palliativ Database
Landsdækkende
DEATH REGISTER
Dødsårsagsregisteret
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
Furthermore, the Danish population is considered as
being largely homogenous and non-transient which is
ideal for long term population (also gene-pool) studies .
With a wide range of register based studies, cohorts
can be easily assembled to observe developments
across a group for specific factors. An example is the
Borberg cohort of patients with neurofibromatosis that
was established in 1940 55 and was reinvestigated in a
follow-up study 46 years later. Sørensen et al 56 revisited
this established cohort and linked to data from the DCR
to follow patients for the development of malignant
neoplasms after diagnosis of neurofibromatosis 1. The
registry-based approach was also used in the same
study to investigate risk factors and survival. 57
Illustration 7 : Society as a Cohort - Scenario of accident and physical & mental rehabilitation cases
From such a scenario view, it is easier to understand and infer the treatment quality in hospitals and post trauma care. It is very relevant to varied sectors from
transportation and traffic ( for e.g response time), disbursement of welfare funds (for e.g unemployment in case of long rehab or disability) etc. if the data can
be parsed and visualised in interesting ways. The various registers that would /could be populated by a single incident are shown here under. When seen in
conjunction from birth and various other registeries that are populated as part of the healthcare, it is interesting to analyse the incidence of accidents, quality of
treatment and thus healthcare.
An accident which involves admittance in a hospital is treated as a case of secondary care. All documentation pertaining to this episode is maintained only at the
hopital, including medications given and any tests conducted. Should the patient have any degree of rehabilitation provided, this is also kept within the hospital
records. All this data is shared with the GP only after prior consent from the patient on discharge. If the patient so wishes, the entire data or a part of it can be kept
unreported, exclusively within hospital records. This is very interesting when considering the true breadth of all the registries.
WELL BEING
BIRTH REGISTER
HOSPITAL
ACCIDENT
Ulykkeregisteret
Mobilt Akut System
Databasen (MAS)
Dansk Intensiv Database
Dansk transfusionsdatabase
Landspatientregisteret
Danes treated at foreign
hospitals (DUSAS)
Dansk Anæstesi
Database
Akut mave-tarm kirurgi
databasen
Fælles akutdatabasen
Akut Kirurgi Databasen
Organdonationsdatabasen
INCIDENT
Alkoholbehandlingsregisteret
Stofmisbrugere i Behandling
Dansk Depressiondatabase
Dansk apopleksiregister
Clinical and genetic investigations into tuberous sclerosis
and Recklinghausen’s neurofibromatosis; contribution to
elucidation of interrelationship and eugenics of the syndromes.
Borberg A. Acta Psychiatr Neurol Scand Suppl. 1951; 71():1-239.
56
Long-term follow-up of von Recklinghausen
neurofibromatosis. Survival and malignant neoplasms.
Sørensen SA, Mulvihill JJ, Nielsen A. N Engl J Med. 1986 Apr 17;
314(16):1010-5.
57
Nguyen-Nielsen M, Svensson E, Vogel I, Ehrenstein V, Sunde L.
Existing data sources for clinical epidemiology: Danish registries
for studies of medical genetic diseases. Clinical Epidemiology.
2013;5:249-262. doi:10.2147/CLEP.S45228.
55
REHAB
Tværsektoriel
Rehabiliteringsdatabase
Genoptræningsregisteret
DEATH REGISTER
Dødsårsagsregisteret
PSYCHIATRY
Klinisk database for
børne- og ungdomspsykiatri
Psychiatric Research
Register
Coercive Psychiatry
Register
Database over børns
dødsfald efter ulykker
27
Illustration 8 : Society as a Cohort - Scenario of screening, treatment and care in chronic ailments
In this wellness journey of a person, some instances of chronic care have been mapped. Specific registers have
been instituted for these illnesses. Viewing the registers as different scenarios allows one to see the relevance of
the registers . This scenario makrs the registers that reflect the life-long use of resources in a chronic condition,
treatment, efficacy and outcomes. Much can be learnt about demographic tendencies in developing chronic
illnesses and the state’s role in prevention and cure. Some reflecting databases are also mentioned here, as the
earliest screening factors or diagnosis has happened through other procedures. Read in tandem, regsiters across
these stages could provide vital insights into early screening, genetic predisposition and lifestyle.
WELL BEING
BIRTH REGISTER
DIAGNOSIS
Patobank
Radiologiske ydelser
DRG (diagnoserelaterede
grupper)
Chronic genetic
HÆMOPHILIA
Rehabilitation Register
CEREBRAL PALSY
Opfølgningsprogram for
Cerebral Parese
Dansk Føtalmedicinsk
Database
Chronic Lifestyle
DIABETES
Dansk Voksen Diabetes
Database
Dansk Register for børne- og
ungdomsdiabetes
Den landsdækkende klinisk
kvalitetsdatabase for
screening af diabetisk
retinopati og maculopati
Det Nationale Diabetesregisteret
Dansk Diabetes Database
CANCER
DEATH REGISTER
Dødsårsagsregisteret
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
5.1 Demographic focus : Women,
Children, Elderly & Veterans
Several registers have been established to study
specific demographic groups, as clinical databases,
registers and cohort studies. The health of women has
been a particular area of focus with cervical cancer,
mammography screening, breast cancer, gynaecological
cancers being important. Reproductive health of women
is important especially seen with other population
indicators and thus quality of birthing, IVF, abortion,
pregnancy screening, early pregnancy related abortions,
birth & complications are all registered. Cohorts have
been established to study pre-pregnancy, pregnancy
and eventually birth and development of a child in close
relationship to its mother thus giving researchers a
chance to develop population prognosis especially with
health indicators for genetically and nurture induced
predisposed conditions.
Children, with some registers concerning birthing share
register data with women, but on their own have several
health registers especially for conditions like childhood
diabetes & cancer. Together with health records
maintained at schools, this can be extrapolated with
family data and education data to analyses data for
welfare schemes, future job markets, diet & nutrition
studies, mental health etc.
Geriatric care is a huge component of social welfare
& healthcare, which gives no surprise to detailed
information maintained Nationwide database of
Geriatrics, the Danish Palliative Care database and the
Danish Dementia Database. Apart from these there are
other socio-economic databases maintained by the
different kommunes on spending for the elderly in home
care, institutional nursing, food delivery, transport etc.
The Armed forces maintain the Sessions Register, but
we have been unable to find further information on this
and related registers in the scope of this study.
29
Illustration 9: Women and Children: Unique and symbiotic datasets for future population studies
A specific case of registers pertaining to women and children is considered
here. While most of these registers concern demographic specific data,
some are about reproductive health, birth and early infancy. These registers
are closely linked by their very nature and have been shown as such in the
illustration.
While some of these registers are popluated based on true incidents, many are
populated by surveys and more recently entire cohorts are being tested with an
exclusive online platform with only online engagement with participants. The
Soon to be Pregnant study is one such cohort being conducted only through
online participation.
Diabetes
Børnedatabasen (Børns helbred) - Indskoling og Udskoling (BMI, højde & vægt)
Børnedatabasen (Børns helbred) - First living year
Klinisk database for børne- og ungdomspsykiatri
Database over børns dødsfald efter ulykker
Opfølgningsprogram for Cerebral Parese
Dansk børnecancer register
Cancer
General
Child
Danish National Birth Cohort
Reproduction
Education
women
Employment
Birth
health
records
at School
Body
Cancer
Familie
database
Dansk Bræstkraft Database
Dansk Gynækologisk Cancer Database
DDD-Dansk Register for børne- og ungdomsdiabetes
The larger Danish cohort studies on Soon to be pregnant women, and child
development could be read with smaller nation wide registers on pregnancy
screening, complications, birthing and post natal care. They are insightful on
various levels- from life style to life stage - a clear insight can be reached upon
on co-related demographic shifts, patterns in income groups and this could
have huge inputs in pharmaceutical research and go-to market strategy for
such companies.
The State benefits from this understanding for a better structuring of its
welfare funds and infrastructure.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
6. Mapping the Databases
With a plethora of registers, databases, clinical studies
and cohorts, it was imperative to see them mapped
on the body - the body being the metaphor for areas of
study. The obvious inferences were the areas where a lot
of research is done, but it also revealed the many areas
of concern where there is a lack of systematic data
collection.
The many registers that have been enlisted in the report
are essentially specific health condition data drawn from
the National Patient Register (NPR) and categorised
into a specific register. So the individual registers do
not provide any extra breadth of information than the
NPR. Yet, the depth of clinical data specifically logged
into specific registers makes cross sectoral research
rich and diverse. Individual factors can be measured
against other socio-economic factors to project new
connections and value for other stakeholders.
The body view of the registers also allows one to see
the different research strategies adopted to study
a particular area - For example, female reproductive
sciences in the Danish population is now studied
with smaller registers collecting nation wide data on
gynaecological cancer, cervical cancer, birthing and
abortion. There are specific registers recording IVF
treatment and abortion in early pregnancy. Further
there are cohort studies that are recording the months
leading upto conceiving (pre-pregnancy environment
and factors ) and birth and child rearing. This way, a part
of the selected population has a deeply documented
wellness journey which could be very valuable for other
stakeholders.
Pharmaceutical research stakeholders who also invest
heavily into health research delve into huge volumes of
anonymised data for research on new drug delivery or
their future strategies.
Illustration 10 : A body based view on health registers, cohorts and clinical studies
Studies and registers pertaining to men and women are
presented in this illustration. The numbers correspond
to the List of Registers presented in the Appendix to this
report. This allows us to see the health areas where we
have the largest amounts of data which is reflective of
population health and governmental priority.
The diabetes and cancer registers are extrapolated
separately, the numebr of registers reflecting the dimension
of the illness. However the registers for the children and
elderly have to be viewed with other socio-economic
registers as these are intesive on time and healthcare
personnels in a welfare system.
Please refer to the appendix for The List of Registers.
(109)
(149)
(4,7,8,12,28,34, 49,63)
(88,99,115,126, 143, 147, 151)
(163)
(100)
neck
(13)
(108)
(18,31, 40,41, 42, 43,55 )
(30,33, 52)
(125)
(122,138,141,142 )
(22, 25)
(10)
(29,37,38,39, 48)
(123)
(15)
(30,33)
(11, 26)
(148)
(24,91)
(14,16,17,19,80)
(92,119, 162)
(118)
(65, 113)
(27, 35, 50)
(6, 21,62,64,111)
(114,144)
(150)
(58, 59,60)
Screening database
(32,44,45,46,47, 70)
National Register
Cohort Studies
Nationwide
Clinical Study
(119, 96,163)
(17,23,80,92)
(15,22,24,25)
(165,166)
(148)
Demographic Data
(59,60,150,
58,64)
DIABETES
(40)
(37,38,48,112)
(39)
(11,143,149)
(23, 37,96,117)
(14,)
(153,168)
(117,38)
(98,102,103,104,124,132,133,134)
CANCER
(116)
(53,126)
MEN
WOMEN
(83,84,85,114,115,144,148)
(6,9,13,21,26,28,29,30,40,50,56,58,60,62,64,108,111)
(22,24,25 )
(160)
(9,10,16,150)
MAPPING THE
IN IN
DENMARK
MAPPING
THEHEALTHCARE
HEALTHCAREDATA
DATALANDSCAPE
LANDSCAPE
DENMARK
CONTEXTUAL
EXTRAPOLATION OF
HEALTHCARE DATA
Data for Calculation and verification of business cases.
Demographics, Segments and Costs
The Danish health care data landscape is fragmented but very rich. When this dataset is
combined with demographic from Denmark Statistics and budget allocations from various
regions, it will provide an in-depth view into the segment of healthcare and how the spending
patterns are organised. This is a vital piece of market analytics that help existing companies
but also point to new areas that startup and foreign investors could take deep interest. We
foresee new service possibilities, optimisations and novel products to fill the any gaps that are
emerging from the landscape.
Data to quantify non-economic effects of new solutions.
Support Innovation Decisions
Interestingly the data available in the Danish healthcare system is a mix of qualitative and
quantitative data. A large pool of journal entries and text logs could actually be mined to
extract a semantic model that can inform and support decision making on levels like quality
of service, quality of counselling and support etc. There are numerous extrapolations that
might support non economic indicators that would make the overall system better for the
end user or patient support.
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
Data for basis of new solutions, collaborations
Data is the new currency of the digital age. The Danish health data is not just a goldmine
waiting to be tapped but also could form the basis for totally new types of solutions – esp
new collaborative ones. Traditionally the diagnosis to care to prognosis pathway has been a
fragmented journey both in terms of data and patient care. Modern data technologies will
create a more unified opportunities for stakeholders to engage in a more seamless data
landscape. This cementing of data process will also enable new business cases to emerge
from this confluence. This collaborative culture around health care innovation fuelled by data
would be a strong growth market and enormous potential – esp for non traditional players.
Data for pattern analysis at large scale for planning and research.
The Danish healthcare system is quite intensive (excellent raw material) but is yet to see the
emergence of large scale pattern recognition models. The cause – effect relationship and
spotting of trends have happened in relative isolation based on disease areas (e.g diabetes)
or demographic basis (e.g elderly). This is mostly due to the professional specialisation
and administrative legacy of many of these initiatives. This is going to change rapidly
with the introduction of many big data technologies which will enable the cross finding
and correlation mapping of various data sets at very large scale. There are numerous
opportunities to be exploited in terms of large scale epidemiological studies, market
analysis and better optimisation strategies based on macro-economic view of the health
care system. This though would need extensive cross organisational collaboration and
reduction of administrative silos. There are indications of such an approach already being
used in research – esp genetic and phenotype. This approach is yet to be systematically
done on administrative and economic aspect of the healthcare system
MAPPING THE HEALTHCARE DATA LANDSCAPE IN DENMARK
CONCLUSION
The Danish health care data is perhaps the earliest of its kind and thus, is a fantastic opportunity
as well as a challenge at the same time.
The richness and depth of data combined with a unique person identification number is a gold
mine of data driven opportunities for new types of services and products to evolve. On the
other hand the legacy of the old systems means, many of these datasets are fragmented and
reside in numerous organisational and technological silos.
In this study, we realised the extent to which new possibilities could emerge in tandem with
new technological trends. Some of the new technological trends that will highly influence the
data landscape of the Danish healthcare systems are :
1. Big data analytics - the rise of cloud enabled solutions for identifying and analysing new
treatments.
‘
2. Quantified self - Patients being empowered with data collation tools and devices at home.
3. Genetic modelling driven Machine learning and pattern recognition at large scale, typically
driving new pharmaceuticals.
4. IOT in hospitals - sensor enabled data collection of both therapy as well as patient status.
5. Software as a service - new forms of services that are entirely enabled by software tools
6. Service robotics - the automatisation and augmentation of many basic services esp. in
convalescence and elderly care.
7. Personalised Medicine - tailor made therapy based on genetic as well as physiological data.
8. Telemedicine - remote care enabled by new communication technologies
9. Tertiary care - the emergence of new types of services that are more focused on overall
wellbeing rather than diseases.
These trends are global and some of them will be pioneered in Denmark and many in other parts
of the world but the foundation for the fostering of these new innovations are deeply engrained
in the Danish Society. This is due to 5 major factors that are unique to the Danish system :
1. Very rich data sets from many decades - the basis of many types of new data enabled services
2. Good governance and regulation on data privacy - balanced by an open data approach to non
sensitive data
3. Data Policy and politics - a well debated but progressive policy environment that works in the
favour of citizens and end users.
4. Pharma and health tech cluster in greater Copenhagen area and neighbouring southern
Sweden.
5. Pervasive internet and data connectivity across the entire country.
We can foresee the rise of a new type of health care economy that is driven by entrepreneurship,
public private partnerships and university based research. These are clear trends and the signals
to support them are visible though there is a long way for these to flourish into a rich ecosystem
with the right business models. The coming decade will be the rise of the data driven economy
for the Danish health tech cluster.
MAPPING THE
IN DENMARK
MAPPING
THEHEALTHCARE
HEALTHCAREDATA
DATALANDSCAPE
LANDSCAPE
IN DENMARK
THE NEXT STEPS
The Danish Healthcare system is abundant with opportunities. Denmark has had a long
tradition in providing advanced healthcare with universal access to all its citizens. The
quality of healthcare depended for long on good clinical practice supported by purchasing
modern technology to support it. At this point in time, the confluence of good medicine and
management alone is not enough. The new paradigm of healthcare is clearly moving towards
a system that is based on collaboration, data driven and precision-tailor made medicine. This
combined with change in social structures influenced by media and internet technologies, shift
in demographic etc will make it necessary for the Danish healthcare system to evolve itself and
the logical next steps as a recommendation could be as below:
1. The use of data driven methods to drive public procurement The public sector is the largest buyer of healthcare in Denmark, its a clear value addition to
have a more accurate, evidence based tendering process. There are huge efficiency gains to be
made and the public-private partnership initiatives already point to the right directions. Still the
purchasing of healthcare services and products will have to be smarter for both cost-benefit of
the system itself but also to nurture pioneering systems and innovation. Luckily the Øresund
region has a huge health-tech industry that should be an excellent collaborator in the process.
2. Using connected technology with a more collaborative clinical practice The interaction between the patient and caregiver will undergo major shifts driven by the
quantified self, web technologies and communication technologies. This will question the
current way in which both primary and secondary healthcare sector is organised. Its a natural
progression to build new systems to support this paradigm in the participatory traditions of
the welfare model.
3. A data driven approach to preventive healthcare Following advances in genomics, bio-informatics, predictive analytics, sensor driven data
gathering etc is a clear global tendency that will change citizen expectation very fast in
Denmark, considering how fast and early on the social media trend is adopted in Denmark.
Having the policies and governance in place to embrace this trend would be crucial link to
growth for this sector.
4. The myth of the rich data set in Denmark Paradoxically the Danish healthcare system is a gold mine of data to drive the above three
paradigms due the excellent data quality and density available. Though the data is trapped in
organisational silos and data architecture is not designed for collaborative use at scale. There
is an urgent need to build unified data interchange protocols and allow faster turnaround for
data mashups to happen.
These above paradigm shifts are also ripe with opportunity for delivering better healthcare to
citizens but also nurturing entrepreneurship and growth for companies.The following are some
clear pointers that could pave the road to support healthy growth.
1. Digital Marketplace
Copenhagen Healthtech Cluster could enable a digital market place that brings together
research, clinical practice and commercial partners in tandem with public agencies and
hospitals. This marketplace would need to be very governed and regulated for it to be a
trustworthy exchange of value. It has to be imagined as an online platfrom where insights and
ideas blend in a very practical context.
2. Sandbox development environment
To support the Digital Marketplace it’s highly recommended to create a virtual sandbox that
has a wide selection of anonymised sample data from the various databases identified in this
report. This will have to be wrapped in a modern API (Application programming interface) and
due care should be given to data availability, quality and privacy. The participants in the sandbox
should be able to logically scale the solution they prototype by allowing a pre-screened and easy
connectivity at the right terms. This would be vital to make this a long lasting system. This sort
of facility would make it much easier for companies and startups to prototype solutions faster
in collaboration with clinical and regulatory settings.
3. Smart Procurement
The biggest and most obvious beneficiary of a digital marketplace would public purchasers
who can both seed specific problems and needs into the system. If there is a critical mass of
participants it would create healthy competition letting the most innovative as well as cost
effective solutions to foster.
Kategori (Reg / CDb / Coh.)
DBCG
Danish Stroke Register
Danish Childrens Cancer Register
Danish Breast Cancer Operative
Group
Danish Depression database
Danish esophagus,
Gastroesophageal transitional
DECV
cancer and Stomach-cancer group
Danish Ultrasound scannings
during pregnancy database
Landsdækkende kliniske databaser /
Dansk apopleksiregister
National Clinical Database
Landsdækkende kliniske databaser /
Dansk børnecancer register
National Clinical Database
Landsdækkende kliniske databaser /
Dansk Brystkræft Database
National Clinical Database
Landsdækkende kliniske databaser /
Dansk database for fedmekirurgi
National Clinical Database
Dansk Føtalmedicinsk Database
Landsdækkende kliniske databaser / (ultralydskanninger i graviditeten) ?= Is
National Clinical Database
this the FØTO-databasen
Cancer, Child
Women
Condition,
Obesity
kliniske databaser / Dansk Depressiondatabase
Condition, mind Landsdækkende
National Clinical Database
Landsdækkende kliniske databaser / Dansk Esofagus-, Cardia- og
National Clinical Database
Ventrikelkarcinom database
Condition,
Cardio, Brain
Condition,
cancer
Women, Child
Condition,
Landsdækkende kliniske databaser /
Dansk Galdedatabase
Abdomen, Gall National Clinical Database
8
9
10
11
12
13
14
15
Women,
reproduction
DBCR
Danish Anaesthesia database
Landsdækkende kliniske databaser / Dansk Anæstesi Database
National Clinical Database
Specific
Procedure,
Brain
7
16
UOFDanish Bladder Cancer Committee DABLAC
A
kliniske databaser / Blærecancer
Cancer, urinary Landsdækkende
National Clinical Database
6
Landsdækkende kliniske databaser / Dansk Gynækologisk Cancer Database
National Clinical Database
Quality of
Treatment
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Region H - KCKS
West
Danish Regions,
KCKS, vest
DGCD
2005->
Clinical quality
RegionH
Danish Regions
Danish Gynaecological Cancer
Database
2011->
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/apopleksi/
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DanskAnaestesi-Database-DAD.aspx
http://www.uofdatabase.dk/
KCKS, vest:
Kvalitetskonsulent
Annette Odby
Claus Høgdall,
Rigshospitalet, Tlf. 3545
4248
claus.hogdall@regionh.
dk
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DanskGynaekologisk-Cancer-DatabaseDGCD.aspx
http://www.dfms.dk/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/decv/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/danskdepressionsdatabase/
Kvalitetskonsulent
Susanne Stenkær
Ravnkilde http://www.dapho.dk/
Susanne.Stenkaer@sta
b.rm.dk,
Maj-Britt Jensen, E.mail
Århus
Tlf. 3866 www.dbcg.dk
Universitetshospital [email protected],
0662
Kompetencecenter Data Manager : Lasse
for Klinisk Kvalitet og Pirk, KCKS,West
Biostatistik, Nord
RegionH
Anne Nakano KCKSWest,
[email protected].
dk
Kristian Antonsen,
vicedirektør, Bispebjerg
Hospital,
kristian.antonsen.01@r
egionh.dk, Tlf. 3531
2941
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/akutkirurgidatabasen/
Kompetencecenter
for Klinisk Kvalitet og
Biostatistik, Nord
Danish Regions
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/adhd-databasen/
Danish National
Biobank
http://www.biobankdenmark.dk/Danish
Tel: 3268 5199 / 3268
%20Biobank%20Register/Biobanks%2
9163,
[email protected] 0in%20the%20register.aspx
k
http://www.organdonation.dk/organdon
ationsdatabasen/
http://www.organdonor.dk/
Link
Competence Center
for Clinical Quality
and Information
Technology West
(KCKS-West)
Biobank
Scientific Research Danish
Registry
30 92 23 28,
[email protected]
Contact person
KCKS, vest:
Kvalitetskonsulent
Lea Haller
[email protected]
Statistics / data
manager: Heidi Larsson
2003->,
Danish Regions,
(KCEB-north) Data
expanded after Clinical quality
KCEB North, KCKS Manager Poul Erik
2007
West
Schødt Schlosser
(KCKS-west) :
[email protected]
Styregruppeformand
Olav Bjørn Pedersen,
Email: [email protected],
Århus
Tlf. 4033 1158
2008->
Scientific Research
Universitetshospital Camilla Bernt Wulff, Tlf:
3545 3722
Camilla.Bernt.Wulff@re
gionh.dk
Sep 2010-> ,
2015-> includes
related plastic
surgery
Administration
Administration
Region H Kompetencecenter
Øst
FØTO
DDD
DFR
1976->
2003- >
2003 - >
2005->
2003- >
2011- >
1990->
Data owner
Danish gall database
Danish database for bariatric
surgery
-
DAD
Emergency Surgery Database
Acute
kliniske databaser / Akut Kirurgi Databasen
diseases,Ulcer, Landsdækkende
National Clinical Database
Hospital
Attention Deficit Hyperactivity
Disorder Database
-
5
Landsdækkende kliniske databaser /
ADHD databasen
National Clinical Database
The Danish Pathology Bank
Condition
Patobank
-
-
Abreviat Data collected Purpose
ion
4
Kliniske støtteregistre
Donor Register
Statement of Will Register
Donorregistret
Data source (English)
Livstestamentregister
Data source (Danish)
Diagnosis
Specific
Kliniske Støtteregistre
Procedure,
Patientinformati Kliniske Støtteregistre
on
TAG
3
2
1
CODE
List of National Registers and Clinical Databases
APPENDIX
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
https://www.regionh.dk/kliniskedata
baser/nationaledatabaser/Sider/FoetalmedicinskDatabase.aspx
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
Referenced from
DID
KRC /
DCCG
Danish intensive database
Danish Colorectal Cancer
Database
Danish quality database for breast
cancer screening
Danish Quality Database of Birth
Danish quality database for cervix
screening
Danish Quality Database for
Mammography Screening
Danish Liver and Biliary Cancer
Database
Danish Nephrology Society Land
Register
Danish neuro-oncology register
Dansk Pancreas Cancer Database DPCD
Danish Sarcoma Database
Landsdækkende kliniske databaser / Dansk Intensiv database
National Clinical Database
Landsdækkende kliniske databaser / Dansk Kolorektal Cancer Database
National Clinical Database
Landsdækkende kliniske databaser / Dansk Kvalitetsdatabase for
National Clinical Database
brystkræftscreening
Landsdækkende kliniske databaser /
Dansk Kvalitetsdatabase for Fødsler
National Clinical Database
Landsdækkende kliniske databaser / Dansk Kvalitetsdatabase for
National Clinical Database
livmoderhalskræftscanning
Landsdækkende kliniske databaser / Dansk kvalitetsdatabase for
National Clinical Database
mammografiscreening
Landsdækkende kliniske databaser / Dansk Lever- og Galdevejscancer
National Clinical Database
Databasen
Landsdækkende kliniske databaser / Dansk Nefrologisk Selskabs
National Clinical Database
Landsregister
Landsdækkende kliniske databaser / Dansk neuroonkogisk register
National Clinical Database
Landsdækkende kliniske databaser /
Dansk Pancreas Cancer Database
National Clinical Database
Landsdækkende kliniske databaser /
Dansk Sarkom Database
National Clinical Database
Cancer
Cancer,
Women
Birth,
Child,women
Cancer,
Women
Cancer,
Women
Cancer
Nephrology
Cancer
Cancer
Cancer
Specific
Landsdækkende kliniske databaser / Dansk transfusionsdatabase
Procedure,
National Clinical Database
Blood, Hospital
20
21
22
23
24
25
26
27
28
29
30
31
Landsdækkende kliniske databaser / Database for behandling af
National Clinical Database
reumatologiske patienter
Condition,
Orthopaedic
33
Database for treatment of
rheumatologic patients
Landsdækkende kliniske databaser / Dansk Tværfagligt register for Hoftenære Danish Interdisciplinary Register for
National Clinical Database
Lårbensbrud
Femoral Thigh Break
Acute Diseases
32
Danish transfusion database
2008->
2008->
Sep 2010->
2001->
2008->
Oct 2003->
2000->
1998->
2003->
1997, 2007->
2009->
2011->
1990-> But
contains data
back to 1964
DANBIO 2006->
DTDB
DSD
DNOR
DNSL
DLGCD 2011->
DKMS
DKLS
DKF
DHHD
Specific
Procedure,
hospital
Danish Hysterectomy and
Hysteroscopy Database
Landsdækkende kliniske databaser / Dansk Hysterektomi og Hysteroskopi
National Clinical Database
Database
Specific
Procedure,
reproduction
19
DHR
Danish Heart Register
Landsdækkende kliniske databaser / Dansk Hjerteregister
National Clinical Database
Cardio
18
Danish Hernia Database
17
Landsdækkende kliniske databaser / Dansk Herniedatabase (ingvinalhernier
National Clinical Database
og ventralhernier)
Condition,
reproduction
Clinical quality
Clinical quality
Investigative
Clinical quality
Clinical quality
Clinical quality
Region H Kompetencecenter
Øst
Danish Regions
Region H Kompetencecenter
Nord
Danish Regions
Danish Regions
Region H Kompetencecenter
Syd
Danish Society of
Nephrology (DNS)
Data
Manager:Michael
Due Larsen
Therapy
efficacy,Treatment
quality
Clinical quality
Danish Regions
Region H Kompetencecenter
Nord
Region H Kompetencecenter
Nord
Clinical quality
Clinical quality
Treatment quality
Clinical quality
Analysis
Hans Ulrik FriisAndersen,
[email protected].
dk
Thor Schmidt ,
[email protected]
k
Ann-Dorthe Zwisler,
[email protected]
Monika Madsen,
monika.madsen.01@re
gionh.dk
Annette Settnes,
Hillerød Hospital,
Annette.Settnes@regio
nh.dk, Tlf: 4829 6237
Sofia Kyndesen,
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk,Tlf. 2992 0248
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DanskHysterektomi-og-HysteroskopiDatabase-DHHD.aspx
karbase.dk
www.herniedatabasen.dk
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
https://www.regionh.dk/kliniskedata
baser/nationaledatabaser/Sider/DanskHjerteregister-DHR.aspx
https://www.regionh.dk/kliniskedata
baser/nationaledatabaser/Sider/DanskHerniedatabase.aspx
www.gicancer.dk
www.nephrology.dk
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
KCKS West: Quality
http://www.kcks-vest.dk/kliniskeConsultant :Annette
http://www.dnog.dk/database
kvalitetsdatabaser/dansk-neuroIngeman
onkologisk-register/
http://webcache.googleusercontent
At KCKS West, Data
http://dpcg.gicancer.dk/Default.aspx?pI .com/search?q=cache:http://www.r
Manager: Jan Nielsen D=10
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
Dansk Sarcome Gruppe http://www.ortopaedi.dk/index.php?id=
.com/search?q=cache:http://www.r
Tlf: 23 67 90 47,
24
kkp.dk/om-rkkp/[email protected]
kvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerTlf.: +45 8942 4800 ·
http://www.dtdb.dk/
Strategier/Documents/Rapport_fra
[email protected]
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
Hos KCKS-vest:
http://webcache.googleusercontent
http://www.kcks-vest.dk/kliniskeKvalitetskonsulent
.com/search?q=cache:http://www.r
kvalitetsdatabaser/hoftenaereAnnette Ingeman
kkp.dk/om-rkkp/de-kliniskelaerbensbrud/
[email protected]
kvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
tlf: 38633103 mail:
olitikker-Planerhttps://danbio-online.dk/
databasen@danbioStrategier/Documents/Rapport_fra
online.dk
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
Peter Nørgård Larsen,
Rigshospitalet
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
http://www.kcks-vest.dk/kliniskeData Manager Pia
.com/search?q=cache:http://www.r
Andersen, KCKS, West kvalitetsdatabaser/livmoderhalskraefts kkp.dk/om-rkkp/de-kliniskecreening/
kvalitetsdatabaser/
KCKS, west:
Quality Consultant Lea http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/livmoderhalskraefts
Grey Haller :
creening/
[email protected]
Competence Centre
for Epidemiology
and Biostatistics,
North & Competence Data Manager: Lasse
Pirk
Centre for Clinical
Quality and Health
Informatics, West.
Peter Ingeholm, Tlf: +45
38 68 14 03
Email:
peter.ingeholm.01@regi https://www.regionh.dk/kliniskedatabas
RegionH
onh.dk
er/nationale-databaser/Sider/DanskKontaktperson i KCKS- Kolorektal-Cancer-Database.aspx
Øst:
Mette Roed Eriksen,
specialkonsulent
Scientific Research RegionH
Scientific Research Statens Institut for
Folkesundhed
Scientific Research Regionshospitalet
Horsens
DDDDVDD
DDD?
Diabase
LYFO
LYFO
DDD-Danish Adult Diabetes
Database
DDD-Diabase - The nationwide
clinical database for screening of
diabetic retinopathy and
maculopathy
The Hematologic Common
Database - Acute leukemia
The Hematologic Common
Database - Chronic myeloid
disorders
The national schizophrenia
database
Danish Kidney Cancer Committee
Landsdækkende kliniske databaser /
DDD-Dansk Voksen Diabetes Database
National Clinical Database
DDD-Den landsdækkende klinisk
Landsdækkende kliniske databaser / kvalitetsdatabase for screening af
National Clinical Database
diabetisk retinopati og maculopati
Landsdækkende kliniske databaser / Den Hæmatologiske Fællesdatabase National Clinical Database
Lymfom
Landsdækkende kliniske databaser / Den Hæmatologiske Fællesdatabase National Clinical Database
Myelomatose
Condition,
Diabetes
Blood, Cancer, Landsdækkende kliniske databaser / Den Hæmatologiske Fællesdatabase Condition
National Clinical Database
Akut leukæmi
Landsdækkende kliniske databaser / Den Hæmatologiske Fællesdatabase National Clinical Database
Kroniske myeloide sygdomme
Condition,
Diabetes
Blood,
Condition
Blood,
Condition
Blood,
Condition
Orthopaedic
Orthopaedic
Orthopaedic
Orthopaedic
Diabetes
Condition, Mind Landsdækkende kliniske databaser / Det nationale skizofrenidatabase
National Clinical Database
Landsdækkende kliniske databaser /
Kidneycancer
Cancer, nephro National Clinical Database
38
39
40
41
42
43
44
45
46
47
48
49
50
DOF
DOF
NDR
Landsdækkende kliniske databaser / Den ortopædiske fællesdatabase - Dansk The united orthopedics database National Clinical Database
korsbåndsregister
Danish cruciate ligament register
The united orthopedics database Landsdækkende kliniske databaser / Den ortopædiske fællesdatabase - Dansk
Danish shoulder arthroplasty
National Clinical Database
skulderalloplastik register
Register
Landsdækkende kliniske databaser /
Det Nationale Diabetesregisteret
National Clinical Database
UOFDAREN
CA
DOF
Landsdækkende kliniske databaser / Den ortopædiske fællesdatabase - Dansk The united orthopedics database National Clinical Database
knæalloplastik Register
Danish knee arthroplasty Register
Diabetes register
DOF
LYFO
Landsdækkende kliniske databaser / Den ortopædiske fællesdatabase - Dansk The united orthopedics database National Clinical Database
hoftealloplastik Register
Danish hip arthroplasty Register
The Hematologic Common
Database - Multiple myeloma
LYFO
DDD- Danish Register of Child and
DSBD
Adolescent Diabetes.
Landsdækkende kliniske databaser / DDD-Dansk Register for børne- og
Child, Diabetes National Clinical Database
ungdomsdiabetes
37
The Hematologic Common
Database - Lymphoma
The database for Asthma in Denmark
Landsdækkende kliniske databaser / Databasen for Astma i Danmark
National Clinical Database
Condition,
Respiration
36
1996->
2005->
2005->
2005->
2005->
2005->
2005->
2005->
2005->
1999->
1996->
2015->
1990->
Database for chronical kidney
failure
Landsdækkende kliniske databaser / Database for kronisk nyresvigt
National Clinical Database
Condition,
Nephrology
?
35
DIPSY
Data for clinical quality in
psychiatric treatment
Landsdækkende kliniske databaser / Database for klinisk kvalitet i psykiatrisk
National Clinical Database
behandling
Psychiatry
34
Region H
Region H
Region H
Region H
RegionH
RegionH
RegionH
RegionH
Danish Regions
Danish Regions
Danish Regions
Region H Kompetencecenter
Syd
Clinical quality
Clinical quality
Danish Regions
Region H , KCKS
Vest
Statens Serum
Scientific Research Institut
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Clinical quality
Monitor, treatment
quality
Monitor, treatment
quality
Clinical quality
Monitor, treatment
quality
Clinical quality
Region H
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DenHaematologiske-Faellesdatabase.aspx
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DenHaematologiske-Faellesdatabase.aspx
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DenHaematologiske-Faellesdatabase.aspx
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DenHaematologiske-Faellesdatabase.aspx
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/diabase/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/skulderalloplastikregister/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/korsbaendsregister/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/knaealloplastikregister/
http://www.ssi.dk/Sundhedsdataogit/Re
Mette Kramer Pedersen gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
, Tlf.: 3268 5142 ,
/De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
[email protected]
/Sygdomme%20leagemidler%20behan docname=10765412.PDF
dlinger/Diabetesregisteret.aspx
https://www.regionh.dk/Sundhed/P
KCKS, vest:
olitikker-PlanerKvalitetskonsulent Lene http://www.kcks-vest.dk/kliniskeStrategier/Documents/Rapport_fra
Korshøj kvalitetsdatabaser/skizofreni/
_arbejdsgruppen_vedr_klinisk_kval
[email protected]
itet_final.pdf
Anne Nakano KCKShttp://webcache.googleusercontent
West,
.com/search?q=cache:http://www.r
[email protected]. http://www.uofdatabase.dk/
kkp.dk/om-rkkp/de-kliniskedk
kvalitetsdatabaser/
Anne Hjelm, KCKS
West. E-mail:
[email protected]
k , tel 7841 3987
Anne Hjelm, KCKS
West. E-mail:
[email protected]
k , tel 7841 3988
Anne Hjelm, KCKS
West. E-mail:
[email protected]
k , tel 7841 3989
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
https://www.regionh.dk/kliniskedatabas .com/search?q=cache:http://www.r
er/nationale-databaser/Sider/Danskkkp.dk/om-rkkp/de-kliniskeDiabetes-Database.aspx
kvalitetsdatabaser/
Anne Hjelm, KCKS
http://www.kcks-vest.dk/kliniskeWest. E-mail:
[email protected] kvalitetsdatabaser/hoftealloplastikregister/
k , tel 7841 3986
Peter de Nully Brown,
[email protected]
h.dk
Tel: +45 3545-1128
Sofia Kyndesen
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk
"Peter de Nully Brown,
[email protected]
h.dk,Tel: +45 35451128
Sofia Kyndesen,
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk"
Peter de Nully Brown,
[email protected]
h.dk,Tel: +45 35451128
Sofia Kyndesen,
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk
Peter de Nully Brown,
[email protected]
h.dk
Tel: +45 3545-1128
Sofia Kyndesen
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk
KCKS-Vest:Katrine
Abildtrup Nielsen
[email protected]
KCKS-Vest:Katrine
Abildtrup Nielsen
[email protected]
KCKS-Vest:Katrine
Abildtrup Nielsen
[email protected]
Selskabsecretary@nep http://www.nephrology.dk/
hrology.dk
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
Nationwide database of Geriatrics
Nationwide Clinical Database of
Contact Allergy
The Danish Vascular Registry
Landsdækkende kliniske databaser /
Landsdækkende database for Geriatri
National Clinical Database
Landsdækkende kliniske databaser / Landsdækkende Klinisk Database for
National Clinical Database
Kontaktallergi
Landsdækkende kliniske databaser / Landsregisteret Karbase / Karbase
National Clinical Database
Landsregister
Specific
Procedure,
Elderly
Condition
Cardio
53
54
55
The schlerosis treatment register
Danish Cancer of the testis
Committee
Landsdækkende kliniske databaser / Register uro-onkologisk fællesdatabase
National Clinical Database
Landsdækkende kliniske databaser / Sclerosebehandlingsregistret
National Clinical Database
Landsdækkende kliniske databaser /
Testiscancer
National Clinical Database
Biobank
Cancer
Condition,
Schlerosis
Cancer, Men
Condition
60
61
62
63
64
65
Orthopaedic
70
71
Sagsbehandling
Admin/ Case
Registration,
Hospital
69
Statistik
Statistik
Sagsbehandling
68
Patientinformati
Patientinformation
on
Admin/ Case
Registration,
Sagsbehandling
Hospital
National Indikator Project NIP
Biobank
Admin/ Case
Registration,
Hospital
67
66
UOFDanish Prostate Cancer Committee DAPRO
CA
Landsdækkende kliniske databaser /
Cancer,
Prostatacancer
Prostrate, Men National Clinical Database
59
Danmarks Statistics
Bevægelsesregisteret
Ordinationer af kopipligtige lægemidler
Autorisationsregisteret
Administration af udleveringstilladelser
Ventetider venteinfo.dk
Akut mave-tarm kirurgi databasen
Vævsanvendelsesregisteret
Denmarks Statistics
Movement Register
Authorization Register
Waiting Time
Danish Urological Cancer Group
The Tissue Register
Danish Penis Cancer Committee
AUT
NIP
UOFDATECA
DMSG
UoF
VAR
Danish benign Prostatic
Hyperplasia Database
Prostrate, Men Landsdækkende kliniske databaser / Prosbase
National Clinical Database
58
Landsdækkende kliniske databaser /
Peniscancer
National Clinical Database
Cancer,Men
57
Organ Donation Database
Cancer
Specific
Procedure,
UOFDAPEC
A
GER
?
2004->
April 2010 - >
1993->
2004->
KOL /
DRKOL ?
56
Monitroing of pathways for cancer
Chronic obstructive pulmonary
disease
Landsdækkende kliniske databaser /
Kronisk obstruktiv lungesygdom
National Clinical Database
Condition,
Respiratory
52
Landsdækkende kliniske databaser / Monitorering af pakkeforløb for kræft
National Clinical Database
Landsdækkende kliniske databaser / Organdonationsdatabasen
National Clinical Database
Clinical vein database
Landsdækkende kliniske databaser / Klinisk vene database
National Clinical Database
Blood
51
RegionH
Region H - Det
nationale
Indikatorprojekt
Danish Regions
Danish Regions
RegionH
Administrative
Administrative
Treatment quality
Clinical quality
Clinical quality
Clinical quality
Statens Serum
Institut
Region H - Det
nationale
Indikatorprojekt
Danish Regions
Region H Kompetencecenter
Nord
Danish Regions
Statens Serum
Scientific Research Institut
Clinical quality
Clinical quality
Quality Assessment
Clinical quality
Scientific Research RegionH
Clinical quality
Clinical quality
Region H Kompetencecenter
Øst
https://www.regionh.dk/kliniskedatabas
er/nationaledatabaser/Sider/LandsregistretKarbase.aspx
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/Kliniskdatabase-for-Kontaktallergi.aspx
https://www.regionh.dk/kliniskedatabas
er/nationaledatabaser/Sider/Landsdaekkendedatabase-for-Geriatri.aspx
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/sclerose/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
ssi.dk
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre http://www.laeger.dk/portal/pls/port
Hanna Joensen, Tlf.:
/Personoplysninger%20sundhedsfaglig al/!PORTAL.wwpob_page.show?_
3268 5133, [email protected] %20beskeaftigelse/Autorisationsregist
docname=10765412.PDF
eret.aspx,
http://sundhedsstyrelsen.dk/da/ds/opsl
agautreg
Anne Nakano KCKSWest,
http://www.uofdatabase.dk/
[email protected].
dk
dk
Anne Nakano KCKSWest,
[email protected]. http://www.uofdatabase.dk/
dk
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
Linda Saabye
Kongerslev, Tlf.: 3268 /De%20nationale%20sundhedsregistre
/Dodsaarsager%20biologisk%20materi
5138, [email protected]
ale/Vaevsanvendelsesregisteret.aspx
Anne Nakano KCKSWest,
http://www.uofdatabase.dk/
[email protected].
Tlf: 78 45 09 50, E-mail:
[email protected]
Anne Nakano KCKSWest,
[email protected]. http://www.uofdatabase.dk/
dk
Kirsten Vinding,
Kirsten.Laila.Vinding@r
syd.dk
Thor Schmidt,
[email protected]
k
Jeanne Duus
Johansen,
[email protected]
Monika Madsen,
monika.madsen.01@re
gionh.dk
Nikolaj Eldrup MD
Ph.D., Tlf. 3092 2346,
[email protected]
Katrine Roos
Prechtkatrine.roos.prec
[email protected]
http://www.kcks-vest.dk/kliniskeKatrine Abildtrup
Nielsen [email protected] kvalitetsdatabaser/kol/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
Admin, hospital
Admin,Hospital Statistik
Admin,Hospital Statistik
Admin,Hospital Statistik
Women
76
77
78
79
80
Cancer
Cancer
84
85
Treatment
quality
Psychiatry
87
88
86
Cancer
83
82
Reflecting
Registers
Reflecting
Registers
Hospital
75
81
Hospital
74
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Statistik
Statistik
Statistik
Hospital
73
Statistik
Hospital
72
National Patient Register Radiological services
GP Register (doctors, dentists,
fysiotherapists etc.)
DUSAS (Danes treated at foreign
hospitals)
Landspatientregisteret - Radiologiske
ydelser
Yderregisteret (doctors, dentists,
fysiotherapists etc.)
Register over danskere behandlet på
udenlandske sygehuse og aktivitet i
speciallægepraksis.
Danish Patient Safety Database
The Central Psychiatric treatments
register
Det Psykiatriske Centrale
Behandlingsregister
Waiting time in Danish pharmacies
1943->
Cancer register - New occurences
of cancer
1943->
1973-1994 &
2006->
1943->
DPSD
ABR
DUSAS 2002->
1995->
1976->
1976->
1976->
1976->
Cancer register - Cancer survival
Cancer register - Other neoplasias
Register for Work Hazards
Abortion Register
Dansk Patient Sikkerheds Database
Ventetid på danske apoteker
Cancerregisteret - Nye kræfttilfælde
Cancerregisteret - Kræftoverlevelse
Cancerregisteret - Andre neoplasier
Bivikrningsovervågning
Arbejdssskaderegister
Abortregisteret
Statistikbanken REGR31, Regionernes
regnskaber efter område, funktion, dranst Regional Accounts & finances
og art
Sundhedsstyrelsens elektroniske stillings Electronic position and vacancy
og vakancetælling
counting*
LPR
National Patient Register Operations
Landspatientregisteret - Operationer
LPR
LPR
National Patient Register - Activity
on diagnosis level
Landspatientregisteret - Aktivitet på
diagnoseniveau
LPR
National Patient Register - Activity
on diagnosis group
Landspatientregisteret - Aktivitet på
diagnosegruppe
Statens Serum
Institut
Statens Serum
Institut
Statens Serum
Institut
Statens Serum
Institut
Statens Serum
Institut
Statens Serum
Institut
Statens Serum
Institut
Statens Serum
Scientific Research Institut
Danmark
Scientific Research Apotekerforening
Scientific Research Statens Serum
Institut
Scientific Research Statens Serum
Institut
Scientific Research Statens Serum
Institut
Administrative
Administrative
Administrative
Administrative
Administrative
Administrative
Administrative
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Landspatientregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Landspatientregisteret.aspx,
http://www.esundhed.dk/sundhedsregi
stre/LPR/Sider/LPR01_Tabel.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Landspatientregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Landspatientregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Personoplysninger%20sundhedsfaglig
%20beskeaftigelse/Yderregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sundhedsokonomi%20finansiering/DU
SAS.aspx
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
https://data.digitaliser.dk/alle?svco
mr=20.00.00.00
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
/De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
/Sygdomme%20leagemidler%20behan docname=10765412.PDF
dlinger/Cancerregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Cancerregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Cancerregisteret.aspx
Patientombuddet
[email protected] /
http://www.dpsd.dk/
lekontor@patientombudd
et.dk
Milan Fajber, Tlf:3268
5143, [email protected]
Margit Rasted, Tlf: 3268
5153, [email protected]
Maya Christel Milter,
Tlf: 3268 5141,
[email protected]
Helle Rejnhold
Sørensen, Tlf.: 3268
5210, [email protected]
Milan Fajber, Tlf:3268
5143, [email protected]
Margit Rasted, Tlf: 3268
5153, [email protected]
Maya Christel Milter,
Tlf: 3268 5141,
[email protected]
Helle Rejnhold
Sørensen, Tlf.: 3268
5210, [email protected]
Milan Fajber , Tlf:3268
5143, [email protected]
Margit Rasted, Tlf: 3268
5153, [email protected]
Maya Christel Milter,
Tlf: 3268 5141,
[email protected]
Helle Rejnhold
Sørensen, Tlf.: 3268
5210, [email protected]
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Christian Theodor
Ulrich, Tlf.: 3268 9065, /De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
/Graviditet%20fodsler%20born/Abortre docname=10765412.PDF
[email protected]
gisteret.aspx
Kristian Nielsen, Tlf.:
3268 5135, [email protected]
Christian Theodor
Ulrich, Tlf.: 3268 9065,
[email protected]
Kristian Nielsen,
Tel:3268 5135,
[email protected]
Erik Villadsen , Tel.:
3268 5131, [email protected]
Kristian Nielsen,
Tel:3268 5135,
[email protected]
Erik Villadsen , Tel.:
3268 5131, [email protected]
Kristian Nielsen,
Tel:3268 5135,
[email protected]
Erik Villadsen , Tel.:
3268 5131, [email protected]
Kristian Nielsen,
Tel:3268 5135,
[email protected]
Erik Villadsen , Tel.:
3268 5131, [email protected]
Ulykkeregisteret
Medicinsk
fødselsregister/Fødselsregisteret
Sundhedsovervågning
Treatment,
Apotek
Diagnosis
Accident
Birth, Child,
Women
93
94
95
96
Psychiatry
99
Cancer
Danish Head and Neck Cancer
Group
Cancer database
DAHANCA (Danish Head and Neck
Cancer Group)
106
Cancerdatabase
108
Admin
105
The Child Database (Children's
health) - Early and late primary
school (BMI, height & weight)
Børnedatabasen (Børns helbred) Indskoling og Udskoling (BMI, højde &
vægt)
DAGS (Danish Ambulant Grouping
system)
Cancer
104
The Child Database (Children's
health) - First living year
Børnedatabasen (Børns helbred) - First
living year
DAGS (Dansk Ambulant
Grupperingssystem)
Child
103
Blood spots from all newborn
Danes since 1976
Blood spots from all newborn Danes
since 1976
107
Child
102
Alcohol treatment register
Alkoholbehandlingsregisteret
The Health Agency's Central Dental
SCOR
Register
Sundhedsstyrelsens Centrale
Odontologiske Register (SCOR),
CPR (The central person register)
Birth, child
101
Sundhedsovervågning
Administrative
Statens Serum
Institut
Serum
Scientific Research Statens
Institut
2009->
2009->
1976->
2005->
1999->
1970->
Statens Serum
Institut
Statens Serum
Institut
Clinical quality
Administrative
Administrative
Administrative
Administrative
Scientific Research
Danish Regions
Statens Serum
Institut
Region H Kompetencecenter
Nord
Statens Serum
Institut
Statens Serum
Institut
Danish Biobank
Registry
Statens Serum
Scientific Research
Institut
Scientific Research
Administrative
Statens Serum
Institut
Center for
Scientific Research Ulykkesforskning
1973-1995.
After 1995
through
Administrative
landspatientregi
steret
1990->
1970->, but not
covering the
Statens Serum
whole country Scientific Research Institut
until 1997->
1994->
1994-2005
manual register. Scientific Research Statens Serum
2005-> digitally
Institut
registered
1970->
DAHAN 2002->
CA
CPR
DECV
NAB
SEI
Coercive Psychiatry Register
Register over anvendelse af Tvang i
psykiatri
PKU
MFR
LRP
LSR
IVF
Cause of Death Register - Stillborn DAR
The Neonatal Screening Biobank
Medical Birth Register
The Accident Register
Pathology register
Medicines Register
IVF-register (fertility)
DAR
Register for dødefødte
PKU Registret
Landsdækkende register for Patologi
Lægemiddelstatistikregisteret
IVF-registeret (fertilitet)
Pregnancy Screening Register
Cause of Death Register - Table
CPR (Det centrale personregister)
Therapy ,
Addiction
100
Sundhedsovervågning
Death, child
98
Sundhedsovervågning
Sundhedsovervågning
97
Sundhedsovervågning
Sundhedsovervågning
Sundhedsovervågning
Women
92
Gravid Screeningsregistret
Epidemiologisk overvågning
Sundhedsovervågning
Dødsårsagsregisteret
Sundhedsovervågning
Sundhedsovervågning
91
Death
90
89
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Graviditet%20fodsler%20born/IVFregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Laegemiddelstatistikregisteret.a
spx
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
Thomas Tjørnelund
Nielsen, Tlf.: 3268
5162, [email protected]
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Graviditet%20fodsler%20born/Borned
atabasen.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
Thomas Tjørnelund
/De%20nationale%20sundhedsregistre ssi.dk
Nielsen, Tlf.: 3268
/Graviditet%20fodsler%20born/Borned
5162, [email protected]
atabasen.aspx
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Maya Christel Milter,
/De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
Tlf: 3268 9082,
/Personoplysninger%20sundhedsfaglig docname=10765412.PDF
[email protected]
%20beskeaftigelse/CPRregisteret.aspx
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://webcache.googleusercontent
Dahanca Secretariat,
.com/search?q=cache:http://www.r
+45 7846
https://www.dahanca.oncology.dk/
kkp.dk/om-rkkp/de-kliniske2620,DAHANCA@onco
kvalitetsdatabaser/
logy.dk
k
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Claudia Ranneries, Tlf.: /De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
32685128, [email protected] /Sygdomme%20leagemidler%20behan docname=10765412.PDF
dlinger/Alkoholbehandlingsregister.asp
x
Danish National
Biobank
Tel: 3268 5199 / 3268 http://www.biobankdenmark.dk/Danish
%20Biobank%20Register/Biobanks%2
9163,
[email protected] 0in%20the%20register.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
Claudia Ranneries, Tlf.:
/De%20nationale%20sundhedsregistre
32685128, [email protected] /Dodsaarsager%20biologisk%20materi
ale/Dodsaarsagsregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Emil Nygaard
/De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
Jørgensen,
[email protected], Tlf.: 2230 /Sygdomme%20leagemidler%20behan docname=10765412.PDF
dlinger/Tvang%20i%20psykiatrien.asp
7904
x
Bjarne Laursen or
Hanne Møller,
65507777,
http://www.sifolkesundhed.dk/Forskning/Sygdomme
%20og%20tilskadekomst/Ulykker/Ulyk
kesregisteret.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
Christian Theodor
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Ulrich, Tlf.: 3268 9065, /De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
[email protected]
/Graviditet%20fodsler%20born/Fodsels docname=10765412.PDF
register.aspx
Milan Fajber, Tlf.: 3268
5143, [email protected]
Tlf.: 3268 5125,
[email protected]
Maya Christel Milter,
Tlf: 3268 9082,
[email protected]
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Claudia Ranneries, Tlf.:
32685128, [email protected] /De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
/Dodsaarsager%20biologisk%20materi docname=10765412.PDF
ale/Dodsaarsagsregisteret.aspx
Elderly
Child, Diabetes
Cancer
Women
Apotek
Admin
Heart
Condition
Death, Child
Respiratory
Elderly
116
117
118
119
120
121
122
123
124
125
126
Demensdatabasen
Databasen for Astma (under etablering)
Fælles Medicinkort
United Medicine card
Joint Emergency Databasen
DRG (diagnosis related groups)
The dementia database
Children's death by accident
register
Database over børns dødsfald efter
ulykker
Database for atrial fibriliation
Database for Atrieflimren (under
etablering)
Database for chronic hepatitis B &
C
Health status of Danes (Numbers
fra the National Health Profile)
Danskernes sundhed (Tal fra den
nationale sundhedsprofil)
Database for kronisk hepatitis B og C
Danish medicin prices
Danske medicinpriser
Dansk urogynækologisk database
FMK
-
DANHE
P
Danish Regions
Scientific Research RegionH
Scientific Research RegionH
Scientific Research RegionH
Scientific Research RegionH
Clinical quality
Scientific Research RegionH
Region H Kompetencecenter
Øst
Statistik,
Reimbursement,
Danish Regions
Quality of treatment
2013->
1975-2009
Region H Kompetencecenter
Syd
Danish Regions
Statens Institut for
Folkesundhed
Region H Kompetencecenter
Øst
Danish Regions
Statens Institut for
Folkesundhed
Administrative
Clinical quality
Administrative
Danish Regions
Scientific Research RegionH
Clinical quality
Scientific Research
Clinical quality
Scientific research
Danmark
Scientific Research Apotekerforening
Clinical quality
Currently being
Scientific Research RegionH
established
1996->
2010->
1985->
DUGAB
Danish urogynaecological databse ase
2006->
DTS
Danish Bowel Cancer Screening
Database
Dansk Tarmkræftscreening Database
DRBU
Danish register for child and youth
diabetes
Dansk Register for Børne- og
Ungdomsdiabetes
DPD
DMD
DDD
DAMD
Danish Palliative Database
Cross-sectoral Rehabilitation
Database
Danish Melanoma Database
Danish Diabetes database
Danish bladder cancer register
The Danish General Medicine
Database
Dansk Palliativ Database
Tværsektoriel Rehabiliteringsdatabase
Admin
Therapy
115
Dansk Melanom Database
129
Cancer, Skin
114
Dansk kvalitetsdatabase for biologisk
behandling af kroniske inflammatoriske
tarmsygdomme (under etablering)
Fælles akutdatabasen
Condition
113
Dansk Diabetes Database
Emergency
Diabetes
112
Dansk blærecancer Register
128
Cancer, Urinary
111
Dansk almenmedicinsk database
Danish Cytogenetic Register
DRG (diagnoserelaterede grupper)
GP
110
Screening
127
Gene
109
Peter Johannsen, Tlf
3545 6702
[email protected]
gionh.dk
Birgitte
Rühmann,birgitte.ruhma
[email protected]
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://www.sundhedsprofil2010.dk/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/falles-akutdatabasen/
https://www.regionh.dk/kliniskedatabas
er/regionhdatabaser/Sider/DemensDatabasen.as
px
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/databasen-forastma-i-danmark/
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://www.apotekerforeningen.dk/anal
http://dst.dk/da/Statistik/emner/sun
yser-ogdhed#
fakta/analyser/medicinpriser.aspx
http://dugabase.dk/
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/KliniskVene-Database.aspx
www.DSBD.dk
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DanskPalliativ-Database.aspx
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DanskGalde-Database-DGD.aspx
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/DanskMelanom-Database.aspx
http://www.siBjarne Laursen, bla@si- folkesundhed.dk/Forskning/Sygdomme
folkesundhed.dk
%20og%20tilskadekomst/Ulykker/B%C
3%B8rned%C3%B8dsdatabase.aspx
Lene Korshøj Tel +45
78 41 39 89
[email protected]
Mette Roed Eriksen,
Region H
Lisbet Rosenkrantz
Hölmich, Klinisk
forskningslektor
KCKS-Øst, Sofia
Kyndesen
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk
Monika Madsen,
monika.madsen.01@re
gionh.dk
Mogens Grønvold,
Bispebjerg Hospital
[email protected], Tlf:
3531 3524
Maiken Bang Hansen,
[email protected]
h.dk
Tlf 3531 2082
Jannet
Svensson,JSVE0041@
heh.regionh.dk
Voksen, Susanne
https://www.regionh.dk/kliniskedatabas
Stenkær,
er/nationale-databaser/Sider/DanskSusanne.Stenkaer@sta
Diabetes-Database.aspx
b.rm.dk
Dansk Almenmedicinsk
http://www.dak-e.dk/
KvalitetsEnhed, Tlf.
6550 3054
Birth, child
Therapy
Therapy
134
135
136
137
Rehabilitation Register - Services
on hospital
Femoral fractures
Interaction Database
Genoptræningsregisteret - Ydelser på
sygehus
Hjerteinsufficiens
Hoftenære frakturer
Interaktionsdatabasen (brug af
lægemidler, naturlægemidler, stærke
vitaminer, mineraler og grapefrugtjuice)
Therapy
Condition,
Cardio
Accidents
Pharmacology
Cardio
138
139
140
141
142
Region H - Det
nationale
Indikatorprojekt
Region H - Det
nationale
Indikatorprojekt
Statens Serum
Institut
Scientific Research RegionH
Rapid Response System Database
(RSS database)
National database for Søvnapnø
Nyrecancer
Emergency
Condition
Nephrology,
cancer
146
147
148
Mobilt Akut System Databasen (MAS)
Scientific Research Sundhedsstyrelsen
Medicine combination
Medicinkombination (samtidig brug af
lægemidler, naturlægemidler, stærke
vitaminer, mineraler og grapefrugtjuice)
Pharmacology
145
Kidney Cancer
DAREN
CA
National database for Sleep Apnea NDOSA 2010->
Clinical quality
Clinical quality
Clinical quality
Clinical database for non
melanoma skin cancer
Klinisk database for Non-melanom
hudkræft
Cancer
144
NMSCC
Clinical database for child & youth
psychiatry
Klinisk database for børne- og
ungdomspsykiatri
Child,
Psychiatry
143
Danish Regions
RegionH
Danish Regions
Region H Kompetencecenter
Syd
Danish Regions
Clinical quality
Kardiologisk fællesdatabase - Dansk
hjertesvigtdatabase
Danish Regions
Sundhedsstyrelsen,
[email protected],
Tlf.nr 44 88 97 57
Inger Gillesberg, Tlf.
38682482
E-mail
Inger.Gillesberg@Regio
nh.dk
Birgitte Rühmann ,
birgitte.ruhmann@regio
nh.dk
Poul Jørgen
Jennum,poul.joergen.je
[email protected]
Thor Schmidt,
[email protected]
k,Tlf: 4044 7480
Sundhedsstyrelsen,
[email protected],
Tlf.nr 44 88 97 57
Thomas Tjørnelund
Nielsen, Tlf.: 3268
5162, [email protected]
Thomas Tjørnelund
Nielsen, Tlf.: 3268
5162, [email protected]
Statens Serum
Institut
Scientific Research Sundhedsstyrelsen
Administrative
Administrative
Cardio
2007->
2007->
Clinical quality
BupBase
GES
GES
Thomas Tjørnelund
Nielsen, Tlf.: 3268
5162, [email protected]
Statens Serum
Institut
Region H - Det
nationale
Indikatorprojekt
Region H - Det
nationale
Indikatorprojekt
Region H - Det
nationale
Indikatorprojekt
Kardiologisk fællesdatabase - Dansk
hjerterehabiliteringsdatabase
Heart insufficiency
Rehabilitation Register - Plans
Administrative
2007->
Rehabilitation Register - All
services
GES
Administrative
Administrative
Administrative
Scientific Research
Births register - New born
Genoptræningsregisteret - Planer
Genoptræningsregisteret - Alle ydelser
Fødselsregisteret - Fødte
Births register - Births and
complications
Birth,child
133
Fødselsregisteret - Fødsler og
komplikationer
Birth, child
132
Family database
Births register - Births
Familiedatabasen
?
131
Fødselsregisteret - Fødsler
Familieambulatoriet
130
https://www.regionh.dk/kliniskedatabas
er/nationale-databaser/Sider/Nationaldatabase-for-SoevnapnoeNDOSA.aspx
https://www.regionh.dk/kliniskedatabas
er/regionh-databaser/Sider/Mobilt-akutsystem-databasen-i-RegionHovedstaden.aspx
http://www.medicinkombination.dk/
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
http://www.kcks-vest.dk/kliniske.com/search?q=cache:http://www.r
kvalitetsdatabaser/hjerterehabilitering/ kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://webcache.googleusercontent
http://www.kcks-vest.dk/kliniske.com/search?q=cache:http://www.r
kvalitetsdatabaser/hjertesvigt/
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://webcache.googleusercontent
.com/search?q=cache:http://www.r
kkp.dk/om-rkkp/de-kliniskekvalitetsdatabaser/
http://www.interaktionsdatabasen.dk/
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Genoptraening.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
/De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
/Sygdomme%20leagemidler%20behan docname=10765412.PDF
dlinger/Genoptraening.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser
/De%20nationale%20sundhedsregistre
/Sygdomme%20leagemidler%20behan
dlinger/Genoptraening.aspx
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/foedsler/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/foedsler/
http://www.kcks-vest.dk/kliniskekvalitetsdatabaser/foedsler/
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
Cancer, Men
Psychiatry
Treatment
Birth, child
Army
Admin
150
151
152
153
154
155
Women
162
Early Pregnancy and Abortion
Quality Database
Tidlig Graviditet og Abort
Kvalitetsdatabase
Online eye-sight
Eye Oncology Group
The new DNB biobank at
Rigshospitalet
The new DNB biobank at Rigshospitalet
The Danish Cancer Society’s
project biobank “Kost, kræft og
helbred”
The Danish Cancer Society’s project
biobank “Kost, kræft og helbred”
Websyn
Biobank
161
Eyes
Cancer
160
The Cancer biobanks (de Kliniske
Kræftbiobanker)
The Cancer biobanks (de Kliniske
Kræftbiobanker)
164
Cancer
159
Health Insurance Register
Sygesikringsregisteret
Tumorer i øjne
Admin
158
SER
RAB
CPOP
DOOG
Ti-Gr-ab
Drug addicts in treatment Register SIB
Statistics over treatment with blood
pressure devices
Statistik over behandling med
blodtryksmidler
Stofmisbrugere i Behandling
Family tree & data
Slægt og data
The Army Register
Samples from the Danish National
Birth Cohort
Samples from the Danish National Birth
Cohort
Sessionsregister
Registered Alternative Therapist
Psychiatric Research Register
The prosdatabase
Registreret Alternativ Behandler
Psykiatriske Forskningsregister
Prosdatabasen
Program for Cerebral
Opfølgningsprogram for Cerebral Parese Follow-up
Palsy
163
Therapy,
Addiction
157
156
Cerebral Palsy,
child
149
Multiple
databases,
earliest from
1946.
1990->
1996->
2005->
2010->
Sundhedsstyrelsen
og
Sundhedsministeriet
http://www.rab-behandlere.dk/cm1/
https://www.regionh.dk/Sundhed/P
olitikker-PlanerStrategier/Documents/Rapport_fra
_arbejdsgruppen_vedr_klinisk_kval
itet_final.pdf
http://www.laeger.dk/portal/pls/port
al/!PORTAL.wwpob_page.show?_
docname=10765412.PDF
https://www.regionh.dk/kliniskedata
baser/nationaledatabaser/Sider/Opf%C3%B8lgnin
gsprogram-for-Cerebral-Parese(CPOP).aspx
Danish National
Biobank
http://www.biobankdenmark.dk/Danish
Danish
Biobank
Tel: 3268 5199 / 3268
Scientific Research Registry
%20Biobank%20Register/Biobanks%2
9163,
0in%20the%20register.aspx
[email protected]
k
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Statens
Serum
/De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
Scientific Research Institut
Tlf.: 2230 7904
/Personoplysninger%20sundhedsfaglig docname=10765412.PDF
%20beskeaftigelse/Sessionsregisteret.
aspx
DIS-Danmark | Rylevej
DIS-Danmark
8, Bro | 5464 Brenderup https://www.slaegtogdata.dk/kilder
(private)
| Danmark
https://digitaliser.dk/resource/3941
Lægemiddelstyrelse
Scientific Research n
?
62
http://www.ssi.dk/Sundhedsdataogit/Re
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Statens Serum
Claudia Ranneries, Tlf.: /De%20nationale%20sundhedsregistre
al/!PORTAL.wwpob_page.show?_
Administrative
Institut
32685128, [email protected] /Sygdomme%20leagemidler%20behan docname=10765412.PDF
dlinger/Stofmisbrugere%20i%20behan
dling.aspx
http://www.ssi.dk/Sundhedsdataogit/Re
Christian
Theodor
gistre%20og%20kliniske%20databaser http://www.laeger.dk/portal/pls/port
Statens Serum
Administrative
Ulrich, Tlf.: 3268 9065, /De%20nationale%20sundhedsregistre al/!PORTAL.wwpob_page.show?_
Institut
[email protected]
/Sundhedsokonomi%20finansiering/Sy docname=10765412.PDF
gesikringsregister.aspx
Danish National
Biobank
Biobank
Tel: 3268 5199 / 3268 http://www.biobankdenmark.dk/Danish
Scientific Research Danish
%20Biobank%20Register/Biobanks%2
Registry
9163,
[email protected] 0in%20the%20register.aspx
k
Danish National
Biobank
Biobank
Tel: 3268 5199 / 3268 http://www.biobankdenmark.dk/Danish
Scientific Research Danish
%20Biobank%20Register/Biobanks%2
Registry
9163,
[email protected] 0in%20the%20register.aspx
k
Danish National
Biobank
Biobank
Tel: 3268 5199 / 3268 http://www.biobankdenmark.dk/Danish
Scientific Research Danish
%20Biobank%20Register/Biobanks%2
Registry
9163,
0in%20the%20register.aspx
[email protected]
k
Oejvind Lidegaard,
https://www.regionh.dk/kliniskedata
[email protected]
baser/nationaleScientific Research RegionH
http://www.tigrab.dk/
k,Tlf.: 3545 0950
databaser/Sider/Tidlig-graviditetKatrine Roos Precht
og-abort-kvalitetsdatabase.aspx
http://webcache.googleusercontent
Jens Overgaard Tel:
.com/search?q=cache:http://www.r
http://doog.dk/
Clinical quality
Danish Regions
89492629,
kkp.dk/om-rkkp/[email protected]
kvalitetsdatabaser/
Erik Kann,
[email protected]
https://www.regionh.dk/kliniskedatabas
Scientific Research RegionH
Birgitte Rühmann,
er/nationalebirgitte.ruhmann@regio databaser/Sider/Websyn.aspx
nh.dk
Scientific Research
Region H Kompetencecenter
Nord
Scientific Research RegionH
Niels Wisbech
Pedersen,
Niels.W.Pedersen@rsy
d.dk
Helle Mätzke
Rasmussen,
www.cpop.dk
[email protected]
Sofia Kyndesen
sofia.mi.jin.spaabaek.m
oeller.kyndesen@regio
nh.dk
TAG
Sygehusbenyttelse - Befolkningen efter diagnosegruppe, nøgletal, alder og køn
Indlæggelser efter område, diagnose (99 gruppering), alder og køn
Indlæggelser efter område, diagnose (23 gruppering), alder og køn
Indlæggelser, sengedage og indlagte patienter efter område, alder og køn
Indlæggelser, sengedage og indlagte patienter efter område, diagnose (99), alder og køn
Indlæggelser, sengedage og indlagte patienter efter område, antal sengedage, alder og kø IND05
Indlagte patienter efter område, dominderende diagnose(99 gruppering) alder og køn
Indlagte patienter efter område, diagnose (99 gruppering), alder og køn
Indeks for indlæggelser efter familietype, alder og køn
Indeks for indlæggelser af voksne efter indekstype, socioøkonomisk status, alder og køn
Indeks for indlæggelser af voksne efter uddannelse, alder og køn
Indeks for indlæggelser af børn efter familiens uddannelse, alder og køn
Indeks for indlæggelser efter område, alder og køn
Indeks for indlæggelser efter herkomst, alder og køn
Indeks for indlæggelser efter boligtype, alder og køn
Hospital usage - Population - diagnosis group, key figures, age and gender
Hospitalizations after area, diagnosis (99 grouping), age and gender
Hospitalizations after area, diagnosis (23 grouping), age and gender
Hospitalizations, bed days, patients after area, age and gender
Hospitalizations, bed days, patients after area, diagnosis(99), age and gender
Hospitalizations, bed days, patients after area, number of bed days, age and gender
Hospitalized patients after area, dominant diagnosis (99), age and gender
Hospitalized patients after area, diagnosis (99), age and gender
Index for hospitalizations after family type, age and gender
Index for hospitalizations of adults after index type, socio-economical status, age and gender
Index for hospitalizations of adults after education, age and gender
Index for hospitalizations of children after the family's education, age and gender
Index for hospitalizations after area, age and gender
Index for hospitalizations after origin, age and gender
Index for hospitalizations after housing type, age and gender
INDAMP01
AMB01
Ambulante behandlinger efter område, diagnose (99 gruppering), alder og køn
Ambulante behandlinger efter område, diagnose (23 gruppering), alder og køn
Ambulante behandlinger og ambulante patienter efter område, alder og køn
Ambulante behandlinger og ambulante patienter efter område, diagnose (99), alder og køn AMB04
Ambulante behandlinger og ambulante patienter efter område, antal behandlinger, alder og AMB05
Ambulante patienter efter område, dominerende diagnose (99 gruppering), alder og køn
Ambulante patienter efter område, diagnose (99 gruppering), alder og køn
Indeks for ambulante behandlinger efter familietype, alder og køn
Ambulant treatments after area, diagnosis (99 grouping), age and gender
Ambulant treatments after area, diagnosis (23 grouping), age and gender
Ambulant treatments and ambulant patients after area, age and gender
Ambulant treatments and ambulant patients after area, diagnosis (99), age and gender
Ambulant treatments and ambulant patients after area, number of treatments, age and gender
Ambulant patients after area, dominant diagnosis (99 grouping), age and gender
Ambulant patients after area, diagnosis (99 grouping), age and gender
Index for ambulant treatments after family type, age and gender
Open/Closed
Scientific Research Open
Indeks for ambulante behandlinger af voksne efter uddannelse, alder og køn
Indeks for ambulante behandlinger af børn efter familiens uddannelse, alder og køn
Index for ambulant treatments of adults after education, age and gender
Index for ambulant treatments of children after the family's education, age and gender
AMBP06
Scientific Research Open
Scientific Research Open
Index for ambulant treatments of adults after index type, socio-economical status, age and gend Indeks for ambulante behandlinger af voksne efter indekstype, socioøkonomisk status, ald AMBP04
AMBP05
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Scientific Research Open
Purpose
AMBP03
AMBP02
AMBP01
AMB03
AMB02
INDP10
Index for hospitalizations of children after index type, socio-economical status, age and gender Indeks for indlæggelser af børn efter indekstype, socioøkonomisk status, alder og køn
INDP09
INDP08
INDP07
INDP06
INDP05
INDP04
INDP03
INDP02
INDP01
IND04
IND03
IND02
IND01
INDAMP03
INDAMP02
Sygehusbenyttelse - Befolkningen efter område, persongruppe, nøgletal, alder og køn
Sygehusbenyttelse - Befolkningen efter område, diagnosegruppe, nøgletal, alder og køn
Hospital usage - Population after person group, area, key figures, age and gender
Abreviation
Data source (Danish)
Hospital usage - Population after diagnosis group, area, key figures, age and gender
Data source (English)
Examples of aggregated healthcare data from Statistics Denmark
Data collected
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Danmarks Stati 2006-2013
Data owner
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
http://www.statistikbanken.dk/statbank5a/default.asp?w=1920
Link
CEBI
WJC
Center for Experimental Bio Informatics
Center for GeoGenetics
Centre for Gene Regulation and Plasticity of
Neuro-endocrine Network
Wilhelm Johannsen Centre for Functional Genome
Research
2001
http://www.wjc.ku.dk/
http://www.ku.dk/
geogenetics.ku.dk/
mrnp.au.dk
PlaCe
Center for Molecular Plant Physiology
DTU
Instituional support
Eske Willerslev
Matthias Mann
Birger Lindberg Møller
Henriette Giese
Ole Lund
Person
Torben Heick Jensen
Kristian Helin
University of Copenhagen
Aarhus University
Niels Tommerup,
[email protected]
University of Copenhagen
The Royal Veterinary and A Lars-Inge Larsson
http://www.natlab.dtu.dk RISØ National Laboratory
/
The Royal Veterinary and
http://www.ku.dk/
Agricultural University.
University of Southern
www.cebi.sdu.dk/
Denmark
http://www.cbs.dtu.dk/
Centre for mRNP Biogenesis and Metaolism
CPMS
Center for Plant-Microbe Symbiosis
1993
Website
epigenetics.ku.dk
CBS
Center for Biological Sequence Analysis
Formed
Centre for Epigenetics
Abbreviation
Institute
List of Genome Research Centers
Report prepared by Leapcraft ApS
Contact
Vinay Venkatraman
CEO, Leapcraft
Strandgade 54
1401 Copenhagen K
www.leapcraft.dk / [email protected]