Towards an Integrated
Health Information System
in the Netherlands

Towards an Integrated
Health Information System
in the Netherlands

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Please cite this publication as:
OECD (2022), Towards an Integrated Health Information System in the Netherlands, OECD Publishing, Paris,
https://doi.org/10.1787/a1568975-en.

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3

Foreword

OECD countries are increasingly concerned with having the right data infrastructure in place for producing
health statistics and measuring health care quality and outcomes. This relates to information gathered
through registries, administrative data, EHRs, and other sources – and concerns data linkage between
settings and levels of care, and mechanisms to generate and use timely, actionable data. Interest in
strengthening health information systems has grown since the COVID-19 pandemic has brought into sharp
focus the importance of reliable, up-to-date information for decision making.
The OECD launched country reviews of health information systems in January 2021 to support countries
in developing health information systems for the digital age. Country reviews follow a method where OECD
and national experts jointly undertake a process of uncovering the barriers and facilitators to each country’s
progress toward a 21st Century health information system. With a common core of content, the reviews
can be compared across participating countries, furthering the value of the project to all countries.
The framework for the evaluation of each health information system is the OECD Council Recommendation
on Health Data Governance which calls for National Health Data Governance Frameworks and sets out
the key principles of such frameworks. All countries are encouraged to adhere to this Recommendation
which provides guidance for building national governance frameworks that enable personal health data to
be both protected and used towards public policy goals. The Recommendation:


Encourages the availability and use of personal health data, to the extent that this enables
significant improvements in health, health care quality and performance and, thereby, the
development of healthy societies while, at the same time, continuing to promote and protect the
fundamental values of privacy and individual liberties;



Promotes the use of personal health data for health-related public policy objectives, while
maintaining public trust and confidence that any risks to privacy and security are minimised and
appropriately managed; and



Supports greater harmonisation among the health data governance frameworks of Adherents so
that more countries can benefit from statistical and research uses of data in which there is a public
interest, and so that more countries can participate in multi-country statistical and research
projects, while protecting privacy and data security.

The first country review undertaken was of the health information infrastructure of the Netherlands in 2021.
The Netherlands’ Ministry of Health, Welfare and Sport commissioned the review to support the country in
reforming a fragmented data landscape into an integrated health information system that would meet the
needs of Dutch society in the digital age. This review supports the Netherlands as it embarks on reforms
to safely use health data to power integrated, patient-centred, services and foster medical and health R&D.

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

4

Acknowledgements

This report is part of a series of country reviews of health information systems that was launched by the
OECD Working Party on Health Care Quality and Outcomes (HCQO) and is part of the 2021/22 programme
of work of the OECD Health Committee. The OECD thanks the experts within the Netherlands that gave
of their time to participate in interviews and focus groups. The OECD acknowledges Herko Coomans for
his support in co-ordinating the study in the Netherlands. The report was authored by Jillian Oderkirk, Luke
Slawomirski and Véronique Bos with input and guidance from Niek Klazinga and David Morgan, and
assistance from Ricardo Sanchez Torres. Thanks are extended to Francesca Colombo and Frederico
Guanais for their comments on a preliminary draft.

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

5

Table of contents

Foreword

3

Acknowledgements

4

Executive summary

7

1 Key findings and recommendations

10

An integrated health information system for the 21st century
References
Notes

2 The structure and governance of the Dutch health information system in
comparison with OECD countries

11
19
19

20

The Dutch health system is fragmented by design
21
Modern health systems (and societies) rely on integrated data and information
24
EMR interoperability is critical with success characterised by co-ordination and leadership at the
national level
39
References
58
Notes
59

3 The strengths and weaknesses of the current Dutch way of managing health and
social care data
Several strengths and advantages will enable creating an integrated health information system
Data custodians in the Netherlands adopt different approaches to health data governance and
exchange
Legislation, regulations and their interpretation can hinder data exchange
Collaboration and data exchange are limited for other reasons
The Netherlands risks being left behind on research and innovation
References
Notes

4 Towards an integrated health information system in the Netherlands
Steps toward an integrated HIS
A unified, national strategy is needed
Institutional functions to develop, implement and oversee an integrated health information
system
Implementation will hinge on governance, policy as well as trust
References

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60
61
62
65
70
72
74
75

76
77
78
82
85
88

6
Notes

88

Annex A. Consultation with experts

89

Annex B. OECD Recommendation on Health Data Governance

91

FIGURES
Figure 1.1. Four main types of data in the Netherlands
Figure 2.1. Four key types of health data in the Netherlands
Figure 4.1. New Zealand Digital Health Strategic Framework

13
22
79

TABLES
Table 2.1. National health data governance elements
Table 2.2. National organisation responsible for EHR system and its role
Table 2.3. National organisation has a multidisciplinary governing body
Table 2.4. Interoperability standards
Table 2.5. Global collaborations for exchange and terminology standards
Table 2.6. Laws or regulations require standards for EHR interoperability
Table 2.7. Certification requirements of vendors of EHR system software
Table 2.8. Auditing clinical records for quality
Table 2.9. Laws or regulations requiring adoption and standardisation of electronic health records
Table 2.10. Certification requirements of EHR software vendors
Table 2.11. Incentives or penalties to install EHR systems from a certified vendor, to keep standards up-todate and to meet national interoperability requirements
Table 2.12. Patient access to and interaction with their own EHR through a secure Internet portal
Table 2.13. Regular secondary analysis of EHR system data
Table 2.14. Machine learning, artificial intelligence and analytics with EHR system data
Table 3.1. Custodians of the Netherlands key national health datasets
Table 3.2. Sharing and access to de-identified data varies by health dataset custodian
Table 3.3. Data protection and security policies and practices vary by dataset custodian

31
40
43
45
46
48
49
50
51
52

Table A A.1. Experts interviewed about the health information system in the Netherlands

89

53
55
56
57
63
63
64

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7

Executive summary

Twenty-first century health systems have to be built around data and information. An integrated health
information system enables the secure exchange and flow of data to where they can be used to create
information and knowledge that advances policy objectives. In the Netherlands, an integrated health
information system is needed to support developing, delivering and monitoring integrated health care
delivery; offering integrated public health monitoring and management, including of the COVID-19
pandemic; capitalising on recent innovations in health information; and fostering research and innovation
in technologies and treatments that improve health and health care.
A range of data assets is relevant for these policy objectives. This includes data generated during
acute- and long-term health care and data on public health and social care. The integrated health
information system should cover the health system as a whole, as well as on other relevant data sources
such as social, economic and environmental data.
Countries making progress toward an integrated health information system appreciate that data are a nonrivalrous asset and that each data point can and should have many uses. Data have many of the features
of a public good, and should be harnessed to generate maximum social benefit. To do this, all data must
be coded according to agreed technical and semantic formats. It is only in this way that data can be
meaningfully exchanged, sent to where they are needed, or analysed.
The OECD reviewed the health information infrastructure in the Netherlands using the OECD Council
Recommendation on Health Data Governance as the analytical framework. It drew information from
interviews and focus groups with Dutch experts from academia, business, and government and from
OECD and other surveys and reports monitoring health data development, use and governance.
This report describes the requirements and the benefits of an integrated health information system; outlines
the current situation in the Netherlands in the context of progress across OECD countries; and
recommends legal, policy and operational changes to overcome barriers to the efficient exchange and
sharing of health data and to establish an integrated health information system.

Challenges and opportunities of the 21st Century require a new approach
The Dutch health system has many strengths that can be harnessed to develop a world-class health data
infrastructure and information system, including strong patient engagement and leadership of patient
groups toward data interoperability; progress in developing data exchange standards; universities and
institutions that are leading good practice in common data models and technologies enabling large-scale
research on distributed data; and a unique ‘can-do’ culture.
However, the Dutch system also has several fundamental barriers that need to be overcome. One of these
is health system fragmentation, a design feature that enables competition and market mechanisms to work
but also presents an institutional barrier to data sharing and exchange. Fragmentation has particularly
affected electronic medical data, where despite efforts toward data exchange, the data remain
underdeveloped, siloed and underused. Lack of alignment and a common interpretation of legislation and
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8
regulations also present a challenge to advancing secure health data sharing, accessibility and use.
Overall, this review found that while there are many strong organisations developing data in silos, there
are few incentives from government or from the private sector to integrate the silos into a whole health
information system.
The Dutch health system has served the country very well in the 20th century. But the challenges and
opportunities of the 21st century are different, and the increasing quantity of generated health data call for
a political choice, legislative guidance and fitting strategic action in order to facilitate ethical and optimal
use of this rapidly expanding resource.
Creating an integrated health information system that meets the needs and opportunities of the 21st
century will require a unified national strategy and a new set of institutional functions to develop, implement
and oversee a health data infrastructure and integrated information system. Successful implementation
will require good governance that builds trust among all stakeholders.

Development of a national strategy toward an integrated health information
system
The Ministerie van Volksgezondheid, Welzijn en Sport would lead the development of a National Strategy
in the form of a strategic plan that considers the data assets and information infrastructure already in place
and builds forward from them. Developing the plan requires working with stakeholders to determine the
objectives of the strategy and the values that the stakeholders want to uphold.
It is essential that the strategy is sufficiently broad and deep. Breadth refers to incorporating the four main
data types: health care, public health, social care and long-term care data. Depth ensures that all data are
included, and that they can be linked at the individual level to enable better care integration as well as
more precision and scope in secondary uses. An important accompaniment to the digital strategy is a set
of roadmaps for each strategic objective, particularly those that will be challenging to achieve, such as data
interoperability.
To lead the development of the national strategy it is recommended that the Ministry:


Builds trust and support for the strategy through consultation with governmental and nongovernmental stakeholders on needs for information, analytics and information products.



Builds public trust through a public information campaign, public consultations and other avenues
in order to include inputs from the public into the strategy and provide a website to share information
about the development process and its outcome.



Considers developing a broad digital strategy encompassing the health data strategy and ensuring
full alignment.



Develops the draft high-level IT architecture/infrastructure for an integrated health information
system that meets the information needs of key stakeholders, including global standards for data
exchange and semantic interoperability, privacy-by-design protections and interoperability in
analytics, information and knowledge.



Develops the policy tools and financial incentives to realise the strategy.

It is also recommended that the ministry further develop and strengthen the national health data
governance legislative framework to support the national strategy. The framework should specify how to
ensure uniform data and interoperability standards, enable the exchange, access to and use of data to
serve the health-related public interest, support ‘privacy by design’, and align with EU regulations.

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9

A national agency to implement and oversee the health information system
A single agency will be needed to co-develop and implement the national strategy with the ministry and to
oversee and maintain the resulting integrated health information system. This could be done by
‘strengthening’ or combining expertise of existing organisations or creating a new agency.
It is recommended that the ministry develop the role and legal mandate to launch the agency and to ensure
that the governance of the agency provides a formal involvement of key stakeholders in the health
information system.
It is recommended that the national agency take responsibility for four key activities that are essential for
an integrated health information system:
1) Agreeing (or developing) and maintaining consistent national standards for terminology
(semantics), data exchange (electronic messaging), analytics, data accessibility and sharing
and harmonisation of data privacy and security policies and practices.
2) Certification including for vendors of IT solutions and digital tools for compliance with national
standards; and verifying through quality checks and audits that health care providers and other
information system actors have achieved interoperability standards and are exchanging
useable (quality) data and are not blocking data flow.
3) Building and maintaining a national public data platform for public data exchange, acting as
a hub through which the data flows. The platform should enable effective and secure
processing of personal health data including data integration/linkage; foster adoption of a
common health data model (CDM); manage the approval process for data integration and
access requests involving data from multiple organisations; enable effective and secure
mechanisms for access to personal health data for approved purposes, such as approved
research; improving data quality, including conducting data quality auditing; and reducing
overlapping and duplicative administrative and data processing activities among key
stakeholders within the health information system.
4) Stakeholder engagement and public consultation about the national strategy and its
implementation; and public transparency through clear communication about the national
strategy and the development, exchange, uses and data privacy and security protections of
health data.

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10 

1 Key findings and recommendations

Twenty-first century health systems will be built around data and
information. Their success will depend on secure exchange and movement
of data to create useful information and knowledge that advance public
policy objectives. This chapter brings together the key findings of this
review of how health data are managed and used in the Netherlands and
the recommendations for creating an integrated national health data
infrastructure and health information system. The chapter outlines what is
meant by health data and an integrated health information system, and its
role in advancing health care, social care, long-term care, public health and
biomedical science. It outlines the strengths and challenges of the Dutch
health system in the context of using health data to advance the health and
well-being of individuals and populations. It concludes with a summary of
recommendations to establish a modern, integrated health information
system in the Netherlands.

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 11
In January 2021, the Ministerie van Volksgezondheid, Welzijn en Sport of the Netherlands commissioned
the OECD to gather evidence and recommend legal, policy and organisational reforms to support creating
an integrated health information system to support four key national policy goals:
1. Strengthening integrated health care delivery across settings and sectors (so that an individual’s
relevant health information can be accessed by them as well as their providers ranging from first
responders to general practitioners to hospitals and allied health providers)
2. Enabling comprehensive public health monitoring and management (including of the COVID-19
pandemic)
3. Capitalising on recent innovations in health information infrastructure
4. Fostering research and innovation in technologies and treatments that improve health and health
care.
To understand the strengths and weaknesses of the current health information system and to develop
recommendations, the OECD, through a series of focus groups and interviews, consulted national experts
from academia, business, and government regarding the Netherlands’ health information system in
January to October of 2021 (See Annex A). The discussions focussed on three questions:


Health data interoperability (exchange and sharing): What are the challenges and what are the
policy tools that can address them? i.e. regulations, incentives, standards, certification?



Personal health environment: What are the digital tools that deliver a modern health care
experience, provide data access and allow interactivity?



Organisation and governance: What national institutions and governance mechanisms support a
strong and trustworthy national health information system?

The information gathered through consultations with experts was complemented with information on the
Netherlands and other OECD countries collected through the OECD’s regular monitoring countries’ health
information systems including: 1. Survey of National Health Data Development, Use and Governance
(2019-20), and 2. Survey of Electronic Health Record System Development, Data Use and Governance
(2021).
This is the final report and recommendations from the OECD review. The report comprises four chapters.
This chapter (Chapter 1) summarises the key findings and recommendations. Chapter 2 outlines the Dutch
health system with regard to how its structure, organisation and governance influence the way health and
social care data are generated, managed and used to advance the four objectives listed above. It also
describes the requirements and the benefits of an integrated health information system where data can be
accessed efficiently and securely by actors who need them and those who can generate valuable
information and knowledge by using them. It also outlines the current situation in the Netherlands in the
context of progress across OECD countries. Chapter 3 examines the main strengths and shortcomings of
current arrangements in the Netherlands to manage health and social care data including legislation and
policies, health information infrastructure and health data interoperability. Chapter 4 outlines legal, policy
and operational changes to establish an integrated health information system. It sets out the requirements
to take advantage of strengths and to address the problems uncovered in this study.

An integrated health information system for the 21st century
Twenty-first century health systems will be built around data and information. In simple terms, an integrated
health information system enables the secure exchange and movement of data to where they can be used
to create information and knowledge that advances policy objectives. Integrated health information
systems require a strong data infrastructure made up of the relevant data assets, technology, agencies
and institutions needed for the collection, storage, maintenance, distribution and (re)use of data by the

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12 
different end users. While infrastructure is a key element, an information system also includes the capacity
to convert raw data into usable information and knowledge. A useful analogy is an integrated transportation
network, which allows passengers to move safely and securely across regional boundaries around the
entire country using various transport types. While the physical and technical infrastructure is an essential
component, such a system also requires people and institutions to ensure it operates effectively, efficiently,
and predictably.

Every data point has several potential uses
An integrated health information system would help the Netherlands directly improve care quality,
outcomes and patient empowerment by enabling patients and their health care providers to access health
information (primary data use). The importance of this was recently highlighted in the Dutch media,1 which
reported difficulties with transferring COVID-19 patients between hospitals because their medical
information cannot be exchanged electronically. This results in not only delays and inefficiencies – with
busy clinicians having to manually transcribe patients’ data from the local electronic record to a CD to send
with the patient – but also the risk of subsequent medical errors that manual transcribing of information
entails.
An integrated health information system would also raise the country’s capacity to use these data for other
important purposes (secondary data use) including:


Managing health system performance on national, regional and network levels,



Public health monitoring and surveillance,



Opening new communications channels with patients to improve patient-centred care such as the
active use of patient-reported metrics (PROMs and PREMs),



Introduction of new digital services such as e-prescriptions or telehealth,



Better targeting of reimbursement for services to reward value,



Biomedical research and development, and



Innovation such as big data analytics and artificial intelligence that will enhance knowledge-based
decisions for patient care and health system governance.

This would enable better public health policies and interventions, and health system management. It would
enable biotechnology innovation and enable the Netherlands to participate in global health efforts and
make the country an attractive destination for capital investment.
A range of data assets is relevant for these purposes. For the Netherlands, this implies data generated
during acute- and long-term health care as well as data on public health (publieke gezondheid) and social
care (sociale domein) (Figure 1.1). The integrated health information system should cover the health
system as a whole as well as drawing on other relevant data sources such as social, economic and
environmental data where necessary.

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 13

Figure 1.1. Four main types of data in the Netherlands

Public health data:

Health Care Data:

Long-term care data:

Social Care Data:

Births and Deaths

Hospital care

Nursing home care

Support to live at home

Demographics

Primary care

Home care

Transport services

Environment

Emergency care

Allied health

Home adaptations

Genomics

Prescribed medicines

Prescribed medicines

Equipment

Vaccinations

Pathology & imaging

Pathology & imaging

Behavioural factors

Patient reported data

Patient reported data

Socio-economic factors

Image credits: © Shutterstock.com/Moab Republic, Shutterstock.com/Cube 29, Shutterstock.com/Millering, Shutterstock.com/Qualit Design.

Interoperability and governance enable efficient and secure exchange of data
Countries making progress in this regard appreciate that data are a non-rivalrous asset and that each data
point can and should have many uses. Data have many of the features of a public good, and should be
harnessed to generated maximum social benefit. To do this, all data must be coded according to agreed
technical and semantic formats. Only this way can data be meaningfully exchanged, sent to where they
are needed, or analysed. Standardisation is especially important in a highly fragmented and disaggregated
health system like the Netherlands.
It is important to stress that an integrated health information system does not require all data of a certain
type to be kept in a single location. It is quite possible to achieve the key objectives outlined above without
central storage or even aggregation. A unified and co-ordinated approach to national data governance can
enable smooth information exchange and use for a range of purposes without compromising privacy,
security and ownership of data. In fact, a federated approach to data (which is more compatible with the
Dutch health system’s structure and governance) can be more secure.
Ensuring that data can be exchanged across national borders into Europe and beyond can amplify the
benefits of data analytics and research in, for example, the context of public health, rare diseases,
pharmacovigilance and precision medicine. An information system that follows international data standards
facilitates within-country and cross-border health care delivery and business opportunities for the
Netherland’s research and technology sectors; and is better prepared to participate in and adapt to
European regulations and initiatives.
For secondary uses of data (statistics and research etc.) an intermediary solution to improve health data
interoperability is a Common Data Model (CDM). A CDM maps data from multiple organisations that use
different standards to a standardised structure that makes it possible for data to be used for analytical
applications, allowing for efficient data pooling and data integration for health statistics and research.
However a CDM is not a practical solution for most primary uses of data such as enabling the smooth
exchange of data between health care providers for direct patient care or the development of a patient
portal.

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14 
A well-designed, integrated health information system requires a data governance framework that avoids
the over-use of consent to authorise data exchange, in favour of legal authorisation and an approach that
protects privacy and ensures data security while enabling data to be exchanged and used for legitimate
purposes. The OECD Council Recommendation on Health Data Governance sets out the elements for a
national health data governance framework and fosters a ‘privacy-by-design’2 approach that is consistent
with emerging transnational requirements such as those set out in the EU General Data Protection
Regulation (GDPR) (See Annex B).

Clinical data play a key role
Clinical data are a key component of any health information system looking to improve care quality as well
as enable research and innovation. OECD countries that are making progress with their integrated health
information systems have:


Established a national organisation that is responsible for setting national clinical terminology
and electronic messaging (exchange) standards;



Created a multidisciplinary governing body for the national organisation that represents key
stakeholders;



Use unique identification of patients and health care providers;



Adopted international terminology standards for diagnoses, medications, laboratory tests and
medical images;



Adopted the HL7 FHIR standard for data exchange (electronic messaging); and participate in
global collaborative projects to improve international data standards.

Most countries have one country-wide electronic health record system and are exchanging EHRs at
the national level including data sharing among physician offices and hospitals about patients’ treatment,
medication use, laboratory tests and images.
Most countries have a Patient Internet Portal where patients can access their own medical records from
all of their current health care providers. Many countries are also utilising EHRs for other secondary
purposes including public health monitoring, health system performance monitoring, patient safety
surveillance and health and medical research. Some are also developing big data analytics including
machine learning, artificial intelligence algorithms with EHRs.
OECD countries have reported in a recent OECD survey several levers to improve the spread and
interoperability of their electronic clinical data.


a legal requirement for health care providers to meet national standards for EHR interoperability.
Thirteen countries reported to have a legal requirement for health care providers to adopt an
electronic health record system (software) that conformed with national standards for both clinical
terminology and electronic messaging (exchange).



a certification of eHR system (software) vendors that required them to adopt national standards
for both clinical terminology and electronic messaging. Again, 13 have a certification that requires
software vendors to meet requirements for national EHR interoperability.



financial incentives (or penalties) for health care providers to install an EHR system that meets
national standards and requirements for national EHR interoperability. Nine countries report
incentives for health care providers to keep their EHR system up-to-date as clinical terminology
and electronic messaging standards change over time; and 8 report incentives for health care
providers to install and EHR system from a certified software vendor.

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 15

Building on strengths while addressing existing barriers
The Dutch health system has many strengths that can be harnessed to develop a world-class health data
infrastructure and information system: strong patient engagement and leadership of patient groups toward
data interoperability; progress in developing data exchange standards; Dutch universities and institutions
are leading good practice in common data models and technologies enabling large-scale research on
distributed data; and a unique ‘can-do’ culture. In the Centraal Bureau voor de Statistiek (CBS), the country
has an agency with the capacity and experience in a privacy-by-design approach to data development,
linkage, sharing and accessibility that is secure and privacy-protective (see Box 1.1).
However, the Dutch system also has several fundamental barriers that need to be overcome. One of these
is the fragmentation – a design feature that enables competition and market mechanisms to work but that
also presents an institutional block to data sharing and exchange. The current Dutch health data landscape
is characterised by the highest number of data custodians reported in the OECD. This fragmented structure
does not preclude being able to leverage available data to achieve the objectives listed earlier. It does,
however, create greater challenges to data sharing and integration than in other countries.

Laws and regulations need to be aligned with policy objectives
Lack of alignment and a common interpretation of legislation and regulations also present a challenge.
Data custodians have varying interpretations of laws and regulations such as the EU General Data
Protection Regulation (GDPR) for example. A fragmented approach to health data management creates
(a) missed opportunities to generate improvements in health and other desirable outcomes, and
(b) heightened risk of personal health data being compromised. Both a national health data governance
framework and guidance on the implementation of the GDPR would help to overcome different legal
interpretations that are limiting data sharing in the Netherlands.
A further issue raised by experts in the Netherlands are legacy legislations that precede the GDPR and
that may create unnecessary obstacles to the exchange and use of health data. In particular, the Medical
Treatment Contracts Act (Wgbo) requires doctors to obtain patient consent to share data with third parties.
Third parties include quality standards/registers. Under Wgbo, patients are required to provide explicit
consent for their records to be included within the Landelijk Schakel Punt (LSP). As a result, the exchange
is missing data on non-consenting patients and for patients whose health care provider did not ask them
to provide consent. This limits the reliability of the data for direct care or secondary uses.
A new framework law (Wegiz) introduced in 2021 aiming to improve health data interoperability takes a
cautious and incremental approach, raising concerns among experts interviewed that full health data
interoperability would not be achieved in the medium term. The framework law will likely require additional
follow-on administrative orders to authorise the new standards called for by professional groups. Experts
interviewed are concerned that the process could be slow and potentially result in conflicting and
incomplete sets of standards. However, a recent letter from Minister De Jonge to parliament (15 October
2021) outlines ways in which implementation of the Wegiz is being expedited.
The Wegiz requires that apart from the technical information standards, (addressing the how) a
complementary set of clinical content oriented quality standards (addressing the what) are developed and
included in the National Quality Standards Register held by Zorginstituut Nederland (ZiN). To evaluate and
adopt these different types of standards seems a complex undertaking. Before recommending standards,
it will be necessary to evaluate whether health care providers and organisations could conform to new
requirements and the evaluation will necessitate acquiring knowledge about the various IT architectures
and software in current use including the different structured terminology standards and uses of free text
(unstructured data).

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Box 1.1. Dutch health information infrastructures with beneficial features
While there are many health data custodians in the Netherlands, three research infrastructures have
emerged whose aims and purpose align with those envisaged for the developing EU Health Data
Spaces.
The Health Research Infrastructure initiative (Health-RI) aims to establish an interconnected data
infrastructure for Dutch personalised medicine and health research. Experts interviewed indicate that
Health-RI would like to access data within hospital and GP electronic health record systems for
approved research projects in real time and use distributed analytics to protect privacy and data security
(personal health train).
ODISSEI (Open Data Infrastructure for Social Science and Economic Innovations) provides
researchers with access to the data holdings of the CBS, including the micro-data in-flowing to CBS
from Dutch Hospitals, GPs, health insurers and research institutes as well as health survey data and
information on the health care industry and follows ‘privacy-by-design’ practices to offer secure data
linkage and access to data as well as advanced computing and analytics.
Netherlands leads the EU EHDEN (European Health Data and Evidence Network) project. Participating
organisations re-code their health and clinical data to the OMOP Common Data Model. Participating
organisations are part of a federated network with a ‘privacy-by-design’ approach where data remain at
all times in the custody of the organisations holding them and network researchers submit queries and
programs (distributed analytics) without accessing or visualising the personal health data. Code is
shared through GitHub, supporting interoperability of data analytics as well as of data.
Source: Dutch Tech Centre for Life Sciences (2021[1]), “Health-RI”, https://www.dtls.nl/large-scale-research-infrastructures/health-ri/;
ODISSEI (2021[2]), https://odissei-data.nl/en/; EHDEN (2021[3]), https://www.ehden.eu/.

Many data assets are fragmented and not easily exchanged
The Dutch approach to electronic medical data is perhaps the most striking example of fragmentation.
While notable initiatives such as MedMij and LSP are trying to address this, the lack of co-ordination and
steering is evident. Experts interviewed described that most health care organisations have engaged
software vendors to develop bespoke EHR platforms to specifications that suit their requirements and
priorities. In most cases, and in the absence of an overarching national data strategy and governance
framework, little attention has been paid to exchanging data. Experts described that many providers are
locked into agreements with their vendors, who either limit or charge large sums to retrofit interoperability
and exchange capability into their systems.
The situation is likely to continue without legislation, certification and financial incentives to prevent
information blocking by software vendors and to encourage software vendors to provide modern IT
architectures that support data exchange and analytical uses of data that are in the public interest. This
can, in fact, create a level playing field for competition and the market to thrive while advancing public
policy objectives.
Meanwhile, information standards developed by either the Nationaal ICT Instituut in de Zorg (Nictiz) or
MedMij are voluntary and participation in a data exchange is voluntary. Moreover, multiple institutes are
funded by the government to collect data on aspects of health or parts of the health care system. However,
funding is not contingent upon collaboration among them and data interoperability among them is not
required. Similarly, ‘hoofdlijnakkoorden’ (outline agreements) between the government and specific
sectors such as medical specialists, include agreements on finances and quality but not on data

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 17
interoperability. As a result, sectors continue to operate in silos. While the government provides financial
incentives to physicians and hospitals to become MedMij certified; certification does not include verification
that the data within MedMiJ are interoperable, nor verification that the user experience for patients would
meet reasonable expectations. For example, verification of how well health information is integrated and
presented to the patient is not included.
In the near term, standardisation of health data could support health care quality measurement and
information by mapping/re-coding data from the diverse array of information systems in the Netherlands to
a common data model (CDM). While this may not be feasible for health organisations with the most
customised and irregular IT systems, it may be possible for most health care providers and organisations
holding health data to have their existing data mapped/re-coded to a CDM.
Experts also raised concern about incentives. In the absence of financial incentives for data
interoperability, the benefits of data interoperability and integration mainly accrue to government,
researchers and health insurers; while the costs of improving the interoperability of health information
systems are mainly borne by health care providers. Government leadership and legislative and policy tools
are needed to create the right environment for information exchange and collaboration.
While many countries are gearing up to use data, including health data, as the fuel to power research and
innovation, the Netherlands risks being left behind in this regard unless current deficiencies in data
governance, interoperability and exchange are addressed. A recent Open Data Institute report put the
Netherlands in the ‘limited vision’ category for advancing the secondary use of health data when compared
with other EU countries (Boyd M, 2021[4]).

The way forward: A cohesive strategy, concerted governance, and strong
leadership
The Dutch health system has served the country very well in the 20th century. But the challenges and
opportunities of the 21st century are different, and the increasing quantity of generated health data calls
for a political choice, legislative guidance and fitting strategic action in order to facilitate ethical and optimal
use of this rapidly expanding resource.
The first thing to say is that radical overhaul of the entire health system is not required. However, creating
an integrated health information system that meets the needs and opportunities of the 21st century will
require a unified national strategy (preferably aligned with a broader national digital / data strategy). It will
require a new set of institutional functions to develop, implement and oversee a health data infrastructure
and integrated information system, either through a new national agency or by consolidating and
strengthening the remit, function, and competencies of existing agencies. Successful implementation will
require good governance, policy, and trust among all stakeholders.
The following is a summary of recommended actions to develop an integrated health information system
in the Netherlands that are set out more fully in Chapter 4.

Develop a national strategy for an integrated health information system
The Ministerie van Volksgezondheid, Welzijn en Sport would lead the development of a National
Strategy in the form of a strategic plan that considers the data assets and information infrastructure
already in place and builds forward from them to develop the tracks and signals that are missing.
Developing the plan requires working with stakeholders to determine the objectives of the strategy and the
values that the stakeholders want to uphold.
It is essential that the strategy is sufficiently broad and deep. Breadth refers to incorporating the four
main data types: health care, public health, social care and long-term care data. Depth ensures that
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18 
all data are included, and that they can be linked at the individual level to enable better care integration as
well as more precision and scope in secondary uses. An important accompaniment to the digital strategy
is a set of roadmaps for each strategic objective, particularly those that will be challenging to achieve,
such as data interoperability.
To lead the development of the national strategy it is recommended that the Ministry:


Builds trust and support for the strategy through consultation with governmental and nongovernmental stakeholders on needs for information, analytics and information products



Builds public trust through a public information campaign, public consultations and other avenues
for public input into the strategy and provide a website to share information about the development
process and its outcome.



Considers developments in the Netherlands toward a broader digital strategy and ensure that
the strategy for health data will be in alignment with them.



Develops the draft high-level IT architecture/infrastructure for an integrated health information
system that meets the information needs of key stakeholders including global standards for data
exchange and semantic interoperability, privacy-by-design protections and interoperability in
analytics, information and knowledge.



Develops the policy tools and financial incentives to realise the strategy.

The ministry is recommended to further develop and strengthen the national health data governance
legislative framework to support the national strategy. The framework should specify how to ensure
uniform data and interoperability standards, enable the exchange, access to and use of data to serve the
health-related public interest, protect privacy by design and align with EU regulations.

A national agency to implement and oversee the health information system
A single agency will be needed to co-develop and implement the national strategy with the Ministerie
van Volksgezondheid, Welzijn en Sport (VWS) and oversee and maintain the resulting health information
system. This could be done by ‘strengthening’ or combining expertise of existing organisations or creating
a new agency.
The ministry is recommended to develop the role and legal mandate to launch the agency and to ensure
that the governance of the agency provides a formal involvement of key stakeholders in the health
information system.
1) It is recommended that the national agency take responsibility for four key activities that are
essential to an integrated health information system:
2) Agreeing (or developing) and maintaining consistent national standards for terminology
(semantics), data exchange (electronic messaging), analytics, data accessibility and sharing and
harmonisation of data privacy and security policies and practices.
3) Certification including for vendors of IT solutions and digital tools for compliance with national
standards; and verifying through quality checks and audits that health care providers and other
information system actors have achieved interoperability standards and are exchanging useable
(quality) data and are not blocking data flow.
4) Building and maintaining a national public data platform for public data exchange, acting as a
hub through which the data flows. The platform should enable effective and secure processing of
personal health data including data integration/linkage; foster adoption of a common health data
model (CDM); manage the approval process for data integration and access requests involving
data from multiple organisations; enable effective and secure mechanisms for access to personal
health data for approved purposes, such as approved research; improving data quality, including

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 19
conducting data quality auditing; and reducing overlapping and duplicative administrative and data
processing activities among key stakeholders within the health information system.
5) Stakeholder engagement and public consultation about the national strategy and its
implementation; and public transparency about the national strategy and the development,
exchange, uses and data privacy and security protections of health data.

References
Boyd M, Z. (2021), Secondary Use of Health Data in Europe, Open Data Institute,
http://theodi.org/wp-content/uploads/2021/09/Secondary-use-of-Health-Data-In-Europe-ODIRoche-Report-2021-5.pdf.

[4]

Dutch Tech Centre for Life Sciences (2021), Health-RI, https://www.dtls.nl/large-scale-researchinfrastructures/health-ri/.

[1]

EHDEN (2021), European Health Data and Evidence Network, https://www.ehden.eu/.

[3]

ODISSEI (2021), Open Data Infrastructure for Social Science and Economic Innovations,
https://odissei-data.nl/en/.

[2]

Notes
1

https://eenvandaag.avrotros.nl/item/gegevens-op-de-fax-of-een-dvd-bij-verplaatsing-vancoronapatienten-wordt-gemis-van-elektronisch-patientendossier-wel-heel-duidelijk/.
2

Privacy-by-design involves designing IT systems in a way that pro-actively anticipates and addresses
risks to data privacy and security so they may be mitigated. In such approaches, the privacy of all
individuals whose data is within the system is protected by default. The protection of individuals’ privacy
and data security is embedded within the architecture and functionality of the IT system. At the same time,
the IT system supports all uses and re-uses of data that are in the public interest.

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20 

2 The structure and governance of the
Dutch health information system in
comparison with OECD countries

This chapter describes the relationship between the structure and
organisation of the Dutch health system and the management, use and
sharing of health data to improve health outcomes and achieve public
policy objectives. The four fundamental laws that govern the four domains
of the Dutch health system are discussed (public health, social care,
curative care, and long-term care), which determine not only the health
system’s architecture but also how data are exchanged within it. The
chapter then describes in more detail the concepts of health data
infrastructure, data governance and an integrated health information
system; the key components of an integrated health information system;
and how it can help countries to advance policy objectives. Examples from
across OECD countries illustrating the development of health data
governance frameworks and interoperable electronic health record systems
are presented to inform the review of the current situation in the
Netherlands.

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 21
This chapter first outlines the key features of the Dutch health system in terms of its structure and
organisation, and how these influence the generation, management and use of data. The scope includes
the four laws that govern four domains of the Dutch health system: 1. public health, 2. social care,
3. curative care, and 4. long-term care. These laws lay the foundation for not only the overall structure of
the health system but also how data flow between the various stakeholders and organisations within it.
The result is a fragmented and heterogeneous health information landscape.
The second part of the chapter describes what is meant by a health data infrastructure and an integrated
health information system, its key components, and how it can help countries advance policy objectives.
Progress across OECD countries in the development of health data governance frameworks and in the
development and governance of interoperable electronic health record systems are presented to inform
the review of the current situation in the Netherlands.

The Dutch health system is fragmented by design
The Dutch health system (defined here as the overall approach to promote individual and population health
through social, preventative and curative means) is a combination of managed competition where
individuals, health care purchasers and providers determine price, quality and service based on supply
and demand within policy and regulatory parameters set by the government (Van Driesden G, 2021[1]).
The system is perhaps best viewed in terms of the laws that govern public health, social care, curative
care and long-term care:

1. Public Health Act:
a) Regulates public health interventions such as population-level screening and control
of infectious disease
b) Stipulates the remit of local governments in promoting public health and well-being.

2. Social Support Act:
a) Stipulates that local governments are responsible for social support, informal care,
and volunteer work
b) Governs the provision of domestic help, day centres, support, and short-term stays at
health facilities
c) Requires sheltered accommodation for people with psychosocial problems.

3. Health insurance Act:
a) Provides for basic entitlements to health care through the funding of basic health
insurance
b) Requires that individuals purchase basic health insurance
c) Stipulates that health care providers may not exclude anyone from basic health
insurance.

4. Long-term Care Act:
a) Regulates health care for people who require 24-hour care and permanent supervision
b) Provides that people who have received a special-needs assessment are entitled to
care either at home or in a designated facility
c) Requires that health care administrative offices procure sufficient care or provide
personal budgets.
This arrangement creates the basic architecture for how Dutch health and social care data are collected,
stored and managed (Figure 2.1). 1

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22 

Figure 2.1. Four key types of health data in the Netherlands

Public health data:

Health Care Data:

Long-term care data:

Social Care Data:

Births and Deaths

Hospital care

Nursing home care

Support to live at home

Demographics

Primary care

Home care

Transport services

Environment

Emergency care

Allied health

Home adaptations

Genomics

Prescribed medicines

Prescribed medicines

Equipment

Vaccinations

Pathology & imaging

Pathology & imaging

Behavioural factors

Patient reported data

Patient reported data

Socio-economic factors

Image credits: © Shutterstock.com/Moab Republic, Shutterstock.com/Cube 29, Shutterstock.com/Millering, Shutterstock.com/Qualit Design.

In addition, the Dutch system works largely on a mixture of competition and market mechanisms, and it
relies heavily on the private (not-for profit) sector. It has limited government involvement on a national level
(health care) and substantive involvement on municipal level (social care). While it has performed very well
in comparison to other OECD countries. It is highly fragmented across health settings and sectors –
exemplified by the separate approaches toward managing and using public health data, health care data
and social care data.
Fragmentation in health systems is certainly not unique. However, in contrast to other most countries where
it is a result of either legacy factors or unintended policy consequences, it is a design feature in the
Netherlands to ensure market mechanisms can function as intended. For example, the competition law
explicitly prohibits exchange of information between providers in order to maintain the market mechanisms.
However, an exchange of data can lead to actions that benefit public health, a role allocated to the
government via the constitution law. This illustrates the need for some legal reform on data exchange for
the benefit of public health.
Fragmentation and the consequent high number of data custodians – does not ipso facto impede nationwide co-operation, co-ordination, and data standardisation, but it makes indispensable co-ordinated,
national policies, legislations, incentives, and governance mechanisms to support and encourage actors
toward the common goal of optimising the use of existing data.

Many institutional actors characterise the regulatory landscape of Dutch health and
social care
Fragmentation characterises not only Dutch health system provision but also its regulation and
governance. A high number of institutional actors and organisations have a stake in governance and
regulation, data creation and processing, and data interoperability and exchange.

Governance and regulation
The key regulatory institutions, the Nederlandse Zorgauthoriteit (NZa), the Dutch Health Institute, the
Inspection of health care and youth, and the Authority for Consumers and Markets, all have part of

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 23
the mandate in data governance and part access to the data. Municipalities, health insurers and
zorgkantoren have siloed mandates for financing of health and social care.
The central government, meanwhile, is advised by different (independent) committees like the
Gezondheidsraad, Sociaal en Cultureel Planbureau, Wetenschappenlijke Raad voor het
regeringsbeleid, Raad voor Volksgezondheid en samenleving (curative care, long-term care, social
care, and public health), Zorginstituut Nederland (curative care, long-term care), Rijksinstituut voor
Volksgezondheid en milieu (RIVM), and the GGD (public health). The Informatieberaad Zorg (IB) is the
(informal)advisory body in which parties come together to work towards safe exchange of information,
however their focus is on curative care and primary uses of information.
The Dutch system also relies on input from confederations and representatives’ organisations like the
Verbond van Nederlandse Ondernemingen en het Nederlands Christelijke Werkgeversverbond
(VNO-NCW), the Federatie Medisch Specialisten, Beroepsvereninging Verzorgenden Verpleegkundigen
(V&VN), Jeugdzorg Nederlan (JN), Nederlandse Vereniging van Ziekenhuizen (NVZ), the
Nederlandse Federatie van Universitaire Medische Centra (NFU), and the Patiënten-federatie
Nederland.

Generating data, data processing and analytics capacity
Together, health and social care providers generate an immense amount of data but these data are most
commonly kept within the organisation/sector. Some providers have realised the potential of integrating
data with other providers and multiple initiatives to exchange data have started for example between
collaborating hospital groups (Santeon group), regional health and social care provider alliances (Beter
Samen in Noord), and municipalities and health insurers (gemeentezorgspiegel). However, not all
providers have the capacity to do so, some are not able to access the data they generate for secondary
purposes, due to a lack of human capital (skills) or financial resources for EHR data processing and
analytics tools.
There is sharing of de-identified personal health data for secondary purposes, for example GP’s sharing
data with an academic network for primary care, is done within sector specific research organisations such
as Nivel (health care), Vilans (long term care and social care), and Trimbos (mental health and addiction).
The Centraal Bureau voor de Statistiek (CBS) has a lot of experience in data processing, linkage and
analytics. However, its mandate is limited in the health arena. The) in co-operation with CBS and the
Ministry of internal affairs are trying to standardise data collection and use on a national level for all
municipalities working with a diverse range of data from living conditions, education, economy, public
health and social care. Noting that most individual municipalities, as most individual health and social care
providers, do not have the capacity for data processing and analytics for secondary purposes.

Standard-setting for data content and exchange
Dutch claims data are well standardised and have clear custodianship. The Nederlandse Zorgauthoriteit
(NZa) collects hospital activity data (DRG), Vektis collects reimbursement data, and the Zorginstituut
Nederland (ZiN) collects data to enable risk equalisation among the many insurers in the Dutch health
care market and public reporting on providers as part of the existing accountability mechanism.
Data on the quality of specialised care is most often managed through Quality Registries by professional
networks and collected via private data custodians in specialised registries (e.g. DICA, DHD, Dutch
cancer registry). Data generated by individual providers and health care professionals are less
standardised as individual providers and provider organisations have different preferred tools (including
indicators), EMR vendors (including some organisations with different content within the ‘same’ EMR
system) and priorities in data standardisation. The TWIIN initiative co-ordinated by the Vereniging van
Zorgaanbieders voor Zorgcommunicatie (VZVZ) and RSO Nederland has the overarching goal to lay the
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24 
foundation of rules and infrastructure for these disparate entities to exchange data. The ambition is to
create a data infrastructure with nationally co-ordinated authorisation and privacy design through:
1) exchange of medical images between health care providers, 2) exchanging laboratory results with
pharmacies, and 3) exchange of data in perinatal health care. This initiative is not structurally funded but
received start- up funding from Zorgverzekeraars Nederland (ZN), an umbrella organisation for Dutch
health insurers.
The Nederlands Normalisatie-Instituut (NEN) is a non-for-profit private company and the Dutch
collaborating partner with the European EN-norms and the international ISO-norms. Ministerie van
Volksgezondheid, Welzijn en Sport has asked NEN to develop standards and certification schemes for
electronic data exchange in health care together with the health care sector.
Nictiz is one of the important organisations developing standards for health data exchange in the
Netherlands. Together with input from other parties that develop standards, like the Zorginsituut
Nederlands, they have built up a library of standards on all five levels of interoperability 1) organisational,
2) process, 3) information, 4) application, and 5) IT-infrastructure.
There are initiatives to facilitate data exchange in health care. Medmij is a standard for the exchange of
health care data between the care professional and the patient. Vendors of personal health environments
can acquire the MedMij label to showcase safe and trustworthy data exchange practices. This initiative
from the Informatieberaad Zorg and the Patiëntenfederatie Nederland is voluntary for vendors of personal
health environments.
The LSP, co-ordinated by the VZVZ, is a platform in which patients/clients can authorise certain health
care providers to share their data when needed. This platform started to facilitate access for health
providers to patients’ medication in emergency situations. It is an opt-in system and therefore does not
cover the whole population. A proposal was recently heard in the senate that an opt-out system for health
care data exchange would still maintain the right to choose and would be more fitting for the needs of
patients.

Modern health systems (and societies) rely on integrated data and information
Twenty-first Century health systems will be built around information: the right information reaching the right
person at the right time. This enables providing high-quality integrated care to all people in need, as well
as better public health practice, health system management, and research and innovation. While health
systems will continue to be structured, funded and organised differently, success – in terms of better care,
public health, system management and research – will be characterised by a comprehensive, coherent,
standardised and integrated approach to managing (electronic) health data.

A data infrastructure and information system
Any endeavour whose goal is social and economic advancement relies on infrastructure. Putting data to
work successfully is no exception. Data infrastructure comprises data assets supported by people,
processes and technology (Open Data Institute, n.d.[2]). It includes the bodies or institutions that create,
maintain and manage the data as well as the institutions, policies and rules that guide their use. A data
infrastructure can be seen as an ecosystem of technology, processes and actors/organisations needed
for the collection, storage, maintenance, distribution and (re)use of data by the different end users. As an
analogy, a rail infrastructure includes not only the tracks and trains but also the resources, people and
equipment to maintain them, regulations and traffic control rules, as well as ticketing and other
passenger services. A strong data infrastructure enhances the efficiency and productivity of using data.
It is necessary to distinguish between data and information. Data are raw figures and facts and, in and of
themselves, may not be very valuable. Information, on the other hand, is meaning and insights that are
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 25
obtained from the analysis of data. Thus, this report focusses on obtaining value from health data within
the Netherlands by developing a system that yields information. A data infrastructure is the foundation. A
health information system not only collects, manages, compiles standardises and exchanges data it also
derives meaning and information from health data through analysis and review. It is a system because the
focus is on data exchange and integration of information across different stakeholders. This requires
supportive laws, policies, governance, hardware and software, expertise and analytical models as well as
public communication channels, strategic planning, implementation guidelines, and audit and evaluation
mechanisms.
An integrated health information system means that electronic data are FAIR (findable, accessible,
interoperable, reusable), and can be exchanged and securely used by other actors and institutions that
serve the public interest. The result is that data can flow, safely and securely, to where information can be
extracted from them to create knowledge that advances human health and well-being.

Individual-level data are needed for both primary and secondary uses
An integrated health information system can help not only directly improve care quality, outcomes and
patient empowerment by enabling patients and their health care providers to access important information,
it would also raise the country’s capacity to use these data for other important purposes including:


Managing health system performance on national, regional and network level



Public health monitoring and surveillance



Opening new communications channels with patients to improve patient-centred care such as the
active use of patient-reported metrics (PROMs and PREMs)



Introduction of new digital services such as e-prescriptions or telehealth



Better targeting of reimbursement for services to reward value



Biomedical research and development



Innovation such as big data analytics and artificial intelligence that will enhance knowledge-based
decisions for patient care and health system governance.

Every data point should serve many uses, from informing a physician caring for a patient to helping patients
manage their care, to health care quality monitoring indicators, value-based payments, real-world
evaluation of the effectiveness of therapies and contributing to clinical decision support tools (artificial
intelligence). Recent advances include that individuals’ data are now used to inform decisions about their
care and the care of others. The distinction between using data for primary purposes (direct patient care)
and secondary purposes (e.g. research, public health monitoring) is therefore increasingly blurred.
For this reason, health data today cannot be easily categorised as personal or non-personal when the data
pertain to individuals. A simple data processing step, such as removing personal identifying information
like names, addresses, health insurance numbers and birth dates from a data set, does not yield
anonymous data because it is increasingly easy to re-match the data to other datasets and re-identify
individuals with some probability of success. More complex manipulations or aggregations of data to try to
guarantee anonymity may destroy the quality, validity and usefulness of the data to produce valid
information and research results.
Even the simple data processing step of removing personal identifying information must be carefully
considered, as the linkage of datasets may require this information, for example to link hospital inpatients
to mortality data to find out how many patients died in the weeks following a procedure. Mechanisms that
allow re-identification for approved data uses, such as investing in pseudonymisation and secure storage
of re-identification keys, are recommended by the OECD (see Annex B).
The key elements of an integrated system that enables primary and secondary uses of data are:
approaching health data as a public good; implementing standardised data terminologies and formats (a
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26 
single ‘language’); a common data model and standardised analytics; and comprehensive data
governance that uses a ‘privacy-by-design’ approach. These are outlined next, followed by a section on
the interoperability of electronic medical records.

Approaching data as a public good
Countries making strides in putting their data to work have recognised that data are a valuable resource
that should be used to generate public benefits. Significant public investment in health and health care are
a key reason why health data are a public good – this includes public investment in health care provision,
in health data development and in funding health research.
But there is also an economic argument for seeing data as a public good in the modern era of Big Data,
high performance computing and modern analytical techniques including machine learning and artificial
intelligence. Data represent immense value both because of the information they potentially contain and
because they can be used and re-used ad infinitum. Their use by one actor does not preclude their use by
others. More importantly, like other public goods such laws or language, data are instrumental in building
social value through knowledge and information. Their exclusivity is not intrinsic, but is imposed by manmade laws, conventions, and institutions. In net terms, their commodification hampers human
development.
Moreover, the social and economic value of data increase exponentially with their size. For example, a
researcher looking for biomarkers that will uncover a precision therapy will find a single dataset comprising
10 million records is much more valuable than 100 separate datasets of 100 000 patients that cannot be
linked or analysed as a whole (such as via the personal data train). In the private sector, forward-looking
firms have realised that even a small slice of analytics on a huge data pool can generate far greater returns
than hoarding much smaller puddles of data for proprietary use.
But to fulfil their potential in secondary uses as well as the primary objectives of improving patients’ care,
experience and outcomes, data held in various places by different custodians must be coded in formats
and languages that enable them to be exchanged and linked.

Data must be standardised to common technical and semantic formats
The main reason why health data are not put to work is a lack interoperability. This happens when the
information systems of data holders have been developed without the use of common standards which
prevent data from being exchanged or when data are exchanged, make it very difficult for the data to be
interpreted or integrated with other data. Without the ability to share and interpret data easily, every data
exchange becomes a costly and time-consuming data integration project.
Data standards in health and health care include the methods, protocols, terminologies, and specifications
for the collection, exchange, storage, and retrieval of health data from many different sources such as
electronic medical records, insurance claims, laboratory test results, prescription medicine dispensing
records, vaccination and public health records, population surveys and more (see Box 2.1).
Therefore, the most efficient solution to maximise the value of data held in silos is to agree on and adopt
common standards for data terminology and exchange. Increasingly, such standards are becoming global,
enabling multi-country collaboration in the development of IT systems and tools, cross-border access to
clinical information for travellers who fall ill, as well as in undertaking multi-country medical and health
research.
An intermediary solution exists to improve health data interoperability – mapping data from multiple
organisations that use different data standards to a Common Data Model (CDM). A CDM organises data
into a standard structure that makes it possible for data and the meaning of data to be shared for analytical
applications, allowing for efficient data pooling and data integration for health statistics and research. The

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 27
CDM is not, however, a practical solution for all situations where interoperability is needed such as the
exchange of data among health care providers for direct patient care or the development of a patient portal.
It should be stressed that an integrated health information system does not require all data to be stored in
a single location. It is quite possible to achieve the key objectives outlined earlier in this report without
central storage or even aggregation. A unified and co-ordinated approach to national data governance can
enable smooth information exchange and use for a range of purposes without compromising privacy,
security and ownership of data. In fact, in some ways data protection can be enhanced under a federated
data structure.
Further, ensuring that data can be exchanged across national borders into Europe and beyond can amplify
the benefits of data analytics and research in, for example, the context of public health, rare diseases,
pharmacovigilance, and precision medicine (see next section). An information system that follows
international data standards facilitates within-country and cross-border health care delivery and business
opportunities for the Netherland’s research and technology sectors; and is better prepared to participate
in and adapt to European regulations and initiatives.

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28 

Box 2.1. Data standards in health and health care
Data standards in health and health care describe the methods, protocols, terminologies, and
specifications for the collection, exchange, storage, and retrieval of health data from many different
sources including electronic medical records, insurance claims, laboratory test results, prescription
medicine dispensing records, vaccination and public health records, population surveys and more.
Standardisation can be summarised as a three-step process. The first step is to specify and define data
elements. Examples of data elements are a lab test result, a particular medicine, and a patient’s name,
age and allergies.
The next step is to associate data types with the data elements. Types include dates, time, counts,
units (weights and measures) and codes that rely on formats and terminologies. For data to be
exchanged and used for many purposes it is essential that the data types are universal and used
consistently. A simple example is recording the time something occurred in a 24- or 12-hour format.
Many data elements are defined by terminologies and their associated codes. For example, SNOMED
CT or SNOMED Clinical Terms is a systematically organised computer processable collection of
medical terms providing codes, terms, synonyms and definitions used in clinical documentation and
reporting. Standards for syntax are also required which specify how terms should be combined to be
interpretable.
The third step is determining how to encode the data elements as an electronic message to exchange
the data within the health information system. Message format standards include common encoding
specifications, information models for defining relationships between data elements, and document
architectures and clinical templates for structuring data as they are exchanged. A widely used standard
for clinical record exchange is Health Level 7 (HL7).
Information models describe how elements and codes should be contextualised with additional
information about data subjects. For example, the terminology and code for fever may be insufficient
without also including information about the process for measuring the fever.
Document architectures are standards for classifying, capturing and revising clinical notes. Clinical
templates impose constraints on an information model. For example, a message format for a laboratory
test may have a clinical template that requires certain data elements to be included.
In addition to standards for data terminology and exchange, standards are also necessary for user
interfaces, record linkage, and data privacy and security protections.

Standards should be accompanied by use cases.
A use case describes a particular instance of exchanging health data and includes the standardised
data to be exchanged as well as the stakeholders involved and the legal framework supporting the data
exchange.
Developing standards requires consideration of the data needs of all of the key stakeholders within the
information system, including stakeholders requiring data for primary (direct care) and secondary
(statistics and research) uses. Developing use cases alongside the development of data standards is a
mechanism for ensuring that the standards will support the different uses of the data that will be needed.
Source: Institute of Medicine (2004[3]) “Health Care Data Standards”, in Patient Safety: Achieving a New Standard for Care,
https://doi.org/10.17226/; Schulz S., Stegwee R., Chronaki C. (2018[4]), “Standards in Healthcare Data”, in Fundamentals of Clinical Data
Science, https://doi.org/10.1007/978-3-319-99713-1_3.

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 29
The EU Health Data Space to help the region capitalise on the potential of health data
The considerable potential to advance health and welfare as well as providing commercial opportunities
for European companies are the motivation to create an EU Health Data Space as part of the EU Digital
Health Strategy (EC, 2021[5]). A new regulation is proposed to support Data Spaces in key economic
sectors to create a single market for data, where data from public bodies, businesses and citizens can be
used safely and fairly for the common good. An EU Health Data Space is proposed to “promote better
exchange and access to different types of health data (electronic health records, genomics data, data from
patient registries etc.), not only to support health care delivery (so-called primary use of data) but also for
health research and health policy making purposes (so-called secondary use of data)” (EC, 2021a[6]).
Three pillars to support the Health Data Space are proposed:
1. Developing a health data governance framework for EU member states that provides guidance
toward secure and privacy protective primary and secondary uses of health data that foster the
accessibility and sharing of data. Such guidance would support greater harmonisation of the
implementation of EU GDPR requirements in practice.
2. Data quality and interoperability including technical and semantic (terminology) interoperability
between the different infrastructures and IT systems and ensuring health data in Europe are FAIR
(Findable, Accessibly, Interoperable and Re-Usable).
3. Technical infrastructure that builds upon and scales up EU infrastructure, including the eHealth
Digital Service Infrastructure, the European Reference Networks and the Genomics Project.
The technical and semantic interoperability standards for the Health Data Space are expected to include
international standards for data exchange and terminology and favour exchange standards that support
protection of health data privacy and security. For example, a 2021 policy report of the Standing Committee
of European Doctors which represents medical associations across Europe, calls for the Health Data
Spaces to adopt the HL7 FHIR standard for data exchange and the SNOMED CT clinical terminology
standard (CPME, 2021[7]).
In alignment with the EU Health Data Space, the European Medicines Agency (EMA) is developing the
DARWIN (Data Analysis and Real-World Interrogation Network) (EMA, 2021[8]). DARWIN will be a
co-ordination centre to provide timely and reliable evidence on the use, safety and effectiveness of
medicines for human use, including vaccines, from real world health care databases across the European
Union (EU). The 2021 call for tender for DARWIN requires all bidders to implement a common data model
(CDM).
New national bodies in France and Finland have characteristics and functions that are similar to the health
data spaces envisaged by the EU. France introduced the Health Data Hub in 2019 and Finland launched
FinData in 2020 to provide a unique entry point for secure and privacy-protective data linkage services and
access to health microdata that are EU GDPR compliant (see next section for descriptions of FinData and
the Health Data Hub).

Privacy by design and a national data governance framework are essential
A key component of a well-functioning health information system is data governance that avoids the overuse of consent to authorise data exchange, in favour of legal authorisation and requirements for an
approach that protects privacy, ensures data security while enabling data to be exchanged and used for
legitimate purposes. The OECD Council Recommendation on Health Data Governance sets out the
elements for a national health data governance framework and fosters a ‘privacy-by-design’ approach that
is consistent with emerging transnational requirements such as those set out in the EU General Data
Protection Regulation (GDPR) (See Annex B).

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30 
Privacy-by-design involves designing IT systems in a way that pro-actively anticipates and addresses risks
to data privacy and security so they may be mitigated. In such approaches, the privacy of all individuals
whose data is within the system is protected by default. The protection of individuals’ privacy and data
security is embedded within the architecture and functionality of the IT system. At the same time, the IT
system supports all uses and re-uses of data that are in the public interest (Cavoukian, 2006[9]).
Privacy-by-design is important because health data are often personal and sensitive, particularly health
micro-data where there is a data record for each individual. The EU Data Protection Regulation (GDPR)
[Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016] places
personal health data in a special category with the highest standards of protection.
The OECD Recommendation on Health Data Governance responds to the growing need for a consensus
about the framework conditions within which health data can be appropriately governed to enable health
data processing to take place both domestically and transnationally. Such health data governance
frameworks require a whole of government approach; given that the public interests served span the
domains of health, justice, industry, science, innovation and finance. The OECD Council Recommendation
on Health Data Governance is compliant with the EU GDPR and encourages ‘privacy-by-design’.
The OECD Recommendation on Health Data Governance was adopted by the OECD Council on
13 December 2016 and was welcomed by OECD Health Ministers at their meeting in Paris on 17 January
2017. The Recommendation provides policy guidance to:


Encourage the availability and use of personal health information, to the extent that this enables
significant improvements in health, health care quality and performance and, thereby, the
development of healthy societies while, at the same time, continuing to promote and protect the
fundamental values of privacy and individual liberties;



Promote the use of personal health data for public policy objectives, while maintaining public trust
and confidence that any risks to privacy and security are minimised and appropriately managed;
and



Support greater harmonisation among the health data governance frameworks of Adherents so
that more countries can benefit from statistical and research uses of data in which there is a public
interest, and so that more countries can participate in multi-country statistical and research
projects, while protecting privacy and data security.

Governments adhering to the Recommendation will establish and implement a national health data
governance framework to encourage the availability and use of personal health data to serve health-related
public interest purposes while promoting the protection of privacy, personal health data and data security.
The Recommendation sets out 12 key elements of the development and implementation of national health
data governance frameworks. The elements encourage greater cross-country harmonisation of data
governance frameworks so that more countries can use health data for research, statistics and health care
quality improvement.
The 2019/20 Survey of Health Data and Governance measured implementation of national health data
governance frameworks and related regulations and policies. The 23 respondents to the 2019/20 survey
were officials of national health ministries or national health data authorities.
A national health data governance framework can encourage the availability and use of personal health
data to serve health-related public interest purposes while promoting the protection of privacy, personal
health data and data security. Overall, 17 of 23 respondents reported that a national health data
governance framework is established or is being established (Table 2.1).
Most respondents reported health data falling under a national health data privacy legislation; other data
used in health studies falling under a national privacy legislation; and certain health datasets or health data
programmes falling under other legislations governing ministries, data collections or registries. Some
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 31
countries have legislations at different levels of government. Overall, 21 of 23 respondents reported that a
national law or regulation exists that speaks to the protection of health information privacy and/or to the
protection and use of electronic clinical records.
European Union (EU) member states implement the European Union (EU) Data Protection Regulation
(GDPR) [Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016]. The
GDPR places personal health data in a special category with the highest standards of protection.
Compliance requires that personal health data are very well organised and portable. For example,
organisations must have data systems that allow them to fulfil individuals’ rights to access their own
personal data, to rectify or restrict their processing and to request data portability from one organisation to
another; as well as to assure data are correctly categorised and demonstrate compliance with the
regulation. In addition to national privacy laws compliant with the GDPR, most EU member states reported
other national legislations with provisions specific to the protection of health data such as laws regarding
patient rights, the collection and management of health information, the provision of medical care and
health care organisations, electronic clinical record systems and health research.

Table 2.1. National health data governance elements
Respondent

A national health data
governance
framework is
established or is being
established

Public consultation has
occurred or is planned
about the elements of the
national health data
governance framework

National law or regulation exists
that speaks to the protection of
health information privacy
and/or to the protection and use
of electronic clinical records

A central authority for the
approval of requests to
process personal health
data is established or
planned

Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Estonia
Finland
France
Germany
Ireland
Israel
Japan
Korea
Latvia
Luxembourg
Netherlands
Norway
Singapore (nonAdherent)
Slovenia
Sweden
United Kingdom
(Scotland)
United States
Total Yes

Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
n.r.
No

Yes
Yes
No
Yes
Yes
No
No
No
No1
No
Yes
Yes
No
Yes
Yes
Yes
Yes
n.r.
Yes

Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
No
No
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No

Yes
Yes
Yes

Yes
No
Yes

Yes
Yes
n.r.

Yes
n.r.
Yes

Yes
17

Yes
14

Yes
21

Yes
17

Note: Note: n.r.: not reported.
1. Mission of the Health Data Hub is to elaborate a citizens and patients charter in collaboration with patient associations.
Source: Oderkirk (2021[10]) “Survey results: National health data infrastructure and governance”, https://doi.org/10.1787/55d24b5d-en.

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32 
Six respondents reported that their health data governance framework is set out in law (Austria, the
Czech Republic, Denmark, Finland, France, Germany). In Austria, there are elements of data governance
within legislation governing health telematics, documentation and research organisation. In the
Czech Republic, the National Health Information System and its governance are defined in the Act on
Health Services. Finland’s health data governance framework is set out in legislation regarding digitisation
and management of client and patient information as well as in regulations and guidelines of the health
ministry (THL) (Box 2.2). Health data governance requirements, including GDPR requirements, are set out
in federal and state laws in Germany.

Box 2.2. Finland – FinData
Findata is authorised by law to support the secondary uses of health and social data in Finland for
projects that contribute to the public interest. Findata is the only authority that can issue permits for the
secondary use of health and social data when the data is compiled from more than one data custodian.
Findata provides for the secure linkage and research access to publicly funded datasets and registries
including the data holdings of the Finnish Institute for Health and Welfare (THL), the Social Insurance
Institution of Finland (Kela), the Population Register Centre, the Finnish Centre for Pensions and
Statistics Finland. From 2021, Findata will expand to include data within the national EHR system
(Kanta).
Findata is a centralised system issuing permits and a one-stop shop for the secondary use of health
and social care data in Finland. It grants data use permits when data are requested from multiple
registries or from the private sector; collects, links and prepares the data; provides the data in a secure
IT-environment for data users; offers electronic tools for data permit applications; offers a help desk for
data users; and works in collaboration with the controllers of the data.
Findata is not a permanent data repository, but a hub in which the data flows. It exists to streamline and
secure the secondary use of health and social care data for four main purposes: 1) enabling effective
and safe processing and access to data; 2) enhancing data protection and security; 3) eliminating
overlapping administrative burden; and 4) improving data quality.
The Act on the Secondary Use of Health and Social Data (enacted in May 2019) gives Findata the
authority to grant secondary use for research within Finland. It is noteworthy that this is made possible
due to Finland’s personal identification code that remains unchanged throughout an individual’s life and
is the key to linking personal information from various registries.
As a rule, the data are always disclosed to Findata’s secure operating environment. However, the Act
empowers Findata to make the data available in another environment as well, if it is necessary for the
research purpose. These other environments will be audited for compliance with the regulation.
Source: Magazanik (forthcoming[11]), “Supporting Health Innovation With Fair Information Practice Principles: Key issues emerging from the
OECD-Israel Workshop of 19-20 January 2021”.

In France, principles of data governance are set out in an Act on the Modernisation of the Health Care
System which unified the governance of administrative health data in the custody of three organisations
and enabled dataset linkages and set out principles and procedures for data access. The 2019 Act on the
Organisation and Transformation of the Health System broadened the definition of the national health data
system to include additional datasets and their custodians and set out data sharing principles among these
custodians. A Health Data Hub is defining the elements of shared data governance with stakeholders. The
Health Data Hub (HDH) was launched in 2019 to support France in becoming a leader in Artificial
Intelligence in health and to overcome barriers to the re-use of health data for research (Box 2.3).

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 33

Box 2.3. France: Health Data Hub
The HDH is a public interest group that was authorised by law and funded by the government to expand
upon the existing national health data system (SNDS) to encompass all existing databases concerning
publicly funded health activities (e.g. hospital electronic health records warehouses, cohorts, and
registries). HDH was built on the infrastructure of the SNDS, the French administrative health care
database that covers 99% of the population. The HDH catalogue uniﬁes a collection of pseudonymised
databases which the HDH is authorised to make available for research.
HDH’s primary goal is to support research and innovation in health and health care by providing a
unique entry point for secure and privacy-protective data linkage services and access to health
microdata for research projects that contribute to the public interest, while respecting patient rights and
ensuring transparency with civil society. The second goal was to design a state-of-the-art platform at
the highest level of security, offering data storage, computing, risk mitigation and analysis capabilities.
Finally, the third goal was to create a documented data catalogue built in a progressive manner to make
priority data known to the scientific community.
The legal reform that launched the HDH aims to allow better visibility of common data assets for the
entire ecosystem and to harmonise data access rules. Access to data is regulated and is carried out
with respect for the rights of individuals. There is no obligation to process health data in France within
the technological platform of the HDH and it is still possible to conduct research in other partnerships.
HDH has so far launched 27 pilot projects, 9 of them COVID-19 related, after HDH received a specific
mandate to accommodate COVID-19 related projects.
Permanent access to the HDH is granted to health authorities by decree of the French Ministry of
Health. Other research requests for data are submitted to the “access team” that conducts a scientific
and ethical assessment. If the request is found eligible, it is sent to the independent Scientific and
Ethical Committee (CESREES). CESREES verifies that the purpose of the study is relevant and of
public interest, that the data requested are in line with the study objective and that the proposed
methodology is robust. If found positive, the project is submitted for authorisation of the French Data
Protection Authority.
HDH consults with civil society by carrying out studies and consultations on the relationship that citizens
have with health data and on their perceptions, needs and expectations. This knowledge is necessary
to orient and adapt public communications, and to evaluate them and ensure they are clear. HDH also
contributes to the implementation of a “health data culture” by providing educational tools to enable
citizens to understand the data and to learn how to use them and how to carry out projects with them.
(CNIL).
Source: Magazanik (forthcoming[11]), “Supporting Health Innovation With Fair Information Practice Principles: Key issues emerging from the
OECD-Israel Workshop of 19-20 January 2021”.

In the Netherlands, the Informatieberaad Zorg works on the development and sustainability of national
health information and includes health care organisations and the Ministry of Health. The Council has four
information system development goals: data to monitor the safety of prescription medicines; citizen access
to their own medical data and the ability to link their own health and medical data; digitisation and exchange
of data between health care professionals; and that data is recorded once and reused. A sub-group of the
Council is the Community of Data Experts which advises the Council about the secondary use of health
data for statistics, research and health and health care policy. Several laws include rules that make it
mandatory to keep a medical record, to provide patients with digital access to their medical records and

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34 
regarding system quality. A new framework law that passed the parliament in 2021 requires the electronic
exchange of medical records among health care providers.
In Korea, the Ministry of Health established a health data governance framework in 2018 and set up a
Healthcare Big Data Policy Deliberation Committee which is responsible for data development, use and
dataset linkages. The COVID-19 pandemic has inspired an expansion of health data under a “Digital New
Deal” which allows for the expansion and linkage of national health insurance data with other relevant data
and for the accessibility of data for global research (Box 2.4). Latvia developed a Health System
Performance Assessment Framework in 2019 (including health care quality, patient safety and efficiency
indicators). Within this framework, principles and procedures for data provision, data linkage, health data
protection, and access to data for research are set out.

Box 2.4. Korea: Digital New Deal
In Korea, the National Health Insurance (NHI) Database was established many years ago and
organisations have been required to submit data to the NHI Program to obtain reimbursement. Korea
already has real-time data at the national level across the continuum of health care services from
insurance claims and these data are routinely linked for statistics and research.
The COVID-19 pandemic, however, has inspired an expansion of health data under a “Digital New
Deal” that is being developed now. Under the New Deal, real-time insurance claims data can be linked
with real-time clinical data. For example, Korea is developing the capability to monitor adverse events
from the COVID-19 vaccination in real time. The Ministry of Health and Welfare and Health Insurance
and Review Assessment Agency (HIRA) have been authorised to share COVID-19 data with the
international community to find an effective response to COVID-19.
In order to further promote health data sharing for research, Korea has prepared legislation to establish
a national data lake that will allow public bodies and private companies to have access to health data.
Korea aims to link additional repositories to this national initiative. Under this new law (anticipated in
2021), Korea plans to maintain the data lake after the pandemic ends so it may continue to support
international researchers’ access to updated COVID-19 patient data.
De-identification techniques such as pseudonymisation are being used as a safeguard, and qualified
organisations will perform data preparation. Engagement with the data lake is by application to qualified
agencies.
Source: Magazanik (forthcoming[11]), “Supporting Health Innovation With Fair Information Practice Principles: Key issues emerging from the
OECD-Israel Workshop of 19-20 January 2021”.

The United States Department of Health and Human Services proposed in 2020 a new rule within the 21st
Century Cures Act to support seamless and secure access, exchange and use of electronic health records
(Box 2.5). The rule aims to increase innovation and competition by giving patients and their health care
providers secure access to health information; allowing more choice in care and treatment. A provision in
the rule requires that patients can electronically access all their electronic health information (both
structured and unstructured data) at no cost and deters blocking authorised access to and exchange of
data. It calls on the health care industry to adopt standardised application programming interfaces (APIs)
to allow individuals to securely and easily access structured electronic clinical data using smartphone
applications.
The Department of Health and Human Services and the Office of the National Co-ordinator have also
released a Trusted Exchange and Common Agreement (TEFCA) which sets out principles, terms and
conditions for a common agreement to enable nationwide exchange of electronic health information across

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 35
disparate health information networks. It aims to ensure that health information networks, health care
providers, health plans, individuals and other stakeholders can have secure access to their electronic
health information when and where it is needed.

Box 2.5. United States: New rule promoting access to data
In the United States, each state manages their own public health reporting programs, and these
practices are regulated by state law. Each individual hospital system may have their own network –
which can include thousands of payer systems. This fragmentation impedes patients’ access to their
complete records, as well as the availability of health data for research. To address this, the Department
of Health and Human Services (HHS) proposed a new rule within the 21st Century Cures Act to support
the seamless and secure exchange and use of electronic health records. The rule asks the health care
industry to utilise Application Programming Interfaces (APIs) and to adopt the HL7 Fast Healthcare
Interoperability Resources (FHIR) standard for health data exchange. Further, a Trusted Exchange and
Common Agreement (TEFCA) sets out principles, terms and conditions to enable the nationwide
exchange of electronic health information across disparate health information networks.
Standardisation of the data sources is required for health data to be exchanged across all networks,
not just the major networks like Medicare. The Office of the National Co-ordinator of Health IT (ONC)
plans to introduce a the United States Core Data for Interoperability Standard, that will be the content
and vocabulary baseline for health data, beginning 24 months after the publication of the final rule. This
standard includes new data classes and data elements, such as provenance, clinical notes, paediatric
vital signs, addresses, email addresses and phone numbers. These data pieces were not universally
exchanged before – but are essential for patient matching and identifying risk factors. Leveraging this
data allows better demographic information to be available to health care providers so that they can
evaluate patients’ risks and needs.
ONC has several pathways for public engagement and input into these data interoperability standards
including a federal advisory committee made up of representatives from health care, health IT, and
patient advocacy organisations. It publishes proposals for public comment and conducts targeted
listening sessions with different groups. Finally, on the technical aspects, it works closely with the
standards organisations which include public input and consensus- based balloting processes.
Generally, there isn’t financial support to all stakeholders to invest in this, but there is some support for
states to implement these capabilities in their networks. For health care providers, there was previously
a programme that provided incentive payments for adoption of an electronic health record system, but
there has not been new funding approved by Congress to continue support. However, there are
requirements for hospital systems that are paid under the Medicare (National) programme to adopt and
use technology that is certified to certain standards and functionalities. ONC has added these new
requirements to the existing programme requirements. There is also a programme that requires the
payers (the plans that administer Medicare and Medicaid) to build Application Programming Interfaces
(APIs, as well to allow the data they hold to also be accessible. And finally, ONC requires technology
developers, through a certification programme, to make this technology available to their customers.
Source: Magazanik (forthcoming[11]), “Supporting Health Innovation With Fair Information Practice Principles: Key issues emerging from the
OECD-Israel Workshop of 19-20 January 2021”.

In Australia, governmental responsibility for national health datasets is shared between Federal and
State/Territorial jurisdictions. At each level of government, there are a range of agencies with responsibility
for specific datasets and there is no overarching health data governance framework. However, all
jurisdictions have signed the 2020-25 National Health Reform Agreement which includes an action to scale
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36 
up a national approach to data governance arrangements, structures and processes, to facilitate clear and
efficient mechanisms for sharing and developing data in a sustainable, purpose-based and safe way. There
is an Australian data governance framework for electronic clinical data exchanged as part of the My Health
Record System. A Data Availability and Transparency Bill was introduced in 2020 to implement a scheme
to authorise and regulate access to Australian Government data (Box 2.6).

Box 2.6. Australia: Data Availability and Transparency Reform including the new Dataplace
Varying legislative requirements across the Commonwealth, States and Territories, particularly for
privacy and permitted uses of data, have historically made data sharing more complex. Challenges to
effective and efficient sharing and use of data are not limited to legislation. Technical, data availability
and data quality challenges have affected the application of data from both new and well-established
data assets to respond to the needs of the health system and the different needs Commonwealth, State
and Territory data users.
The Office of the National Data Commissioner (ONDC) in Australia has been tasked with developing a
new data sharing and release framework, and overseeing the integrity of data sharing and release
activities of Australian Government agencies. The ONDC released its first guidance in 2019 – the Best
Practice Guide to Applying Data Sharing Principles – which provides general guidance to assist
agencies in adopting international best practices in data sharing.
The Australian Government introduced the Data Availability and Transparency Bill 2020 (DAT Bill) into
the Commonwealth Parliament in late 2020. Once passed, the Bill will establish a new scheme to safely
share Australian Government data. To support the implementation of the new data sharing scheme,
ONDC is establishing digital services (known as Dataplace) to manage: the accreditation process under
the scheme; the submission of data requests to data custodians; and the negotiation, registration and
management of data sharing agreements.
It is intended that Dataplace will eventually support the sharing of Australian Government data both
under the new data sharing scheme and through other data sharing mechanisms.
The ONDC is also preparing to implement a Data Inventories Pilot Program to develop individual data
inventories for Australian Government agencies using common standards and then to aggregate these
inventories into an Australian Government Data Catalogue. The Pilot will initially cover about 20% of
Australian Government entities. The Pilot will support greater transparency of government data holdings,
facilitate data sharing and assist the Australian Government to respond quickly in emergencies.
An Intergovernmental Agreement on data sharing, agreed by the National Cabinet on 9 July 2021,
committed the Commonwealth, State and Territory Governments to share public sector data (including
health data) as a default position, where it can be done securely, safely, lawfully and ethically. The
principles-based agreement recognises data as a shared national asset and aims to maximise the value
of data to deliver outstanding policies and services for Australians. National effort will also be focussed on
specific time-limited national priority data areas, under the Intergovernmental Agreement’s National Data
Sharing Work Program.
The 2020-25 Addendum to the National Health Reform Agreement has committed to a series of national
action to enhance health data to enable long term health reform and harness data and analytics to drive
meaningful improvements in the health system. This includes: establishing a national approach to govern
the creation, access and sharing of data from all Australian Governments and progressing mechanisms
and interoperable systems for secure and comprehensive integration of data across patient journeys.
Source: OECD Questionnaire on Health data and governance changes during the COVID-19 pandemic, 2021.

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 37
Ireland’s Department of Health is currently working on a national health information strategy. In this
strategy, Ireland is planning a National Health Observatory which would be authorised by law and include
the development of a national health data governance framework.
In Israel, responsibilities for national health data governance are shared between the Ministry of Health
and the Israel Innovation Authority. Israel’s government has been working on designing a policy framework
for secondary use of health data for research to enable collaborative data research initiatives. This
framework is not yet finalised. As a result of the COVID-19 pandemic, the government has been
accelerating work toward data sharing and access (Box 2.7).

Box 2.7. Israel: COVID-19 Data Lake
The Ministry of Health is working on an initiative to form a ‘Data Lake’ that will include Israel’s digital
health data from hospitals as well as HMO’s and the Ministry of Health itself. On a national level, Israel
has a rich and well computerised health data ecosystem consisting of 30 years of central public health
care provided within HMOs serving 95% of patients. There is value in bringing all of this data together
to accelerate COVID-19 related research. The ‘Data Lake’ policy framework consists of IRB certificate
mechanisms, transparency, de-identification mechanisms, secure environment, user controls, opt-out
mechanisms, and data use agreements.
The public interest in making the data available for research allows for an opt-out mechanism. Israel
communicated with the public about the creation of the data lake via a text message to all persons.
Strengthening the argument supporting the decision to offer an opt-out mechanism were previous
decisions regarding the National Patient File (summary health record). The National Patient File
requires all providers in Israel to use the same central system for data management, so that they can
easily communicate with each other. There were discussions in the Ministry of Health to determine if
this system should have an opt-in or opt-out structure. An opt-out structure was chosen because there
was strong evidence that having all of the data available for patient care provides for more accurate
findings and better health care services; and allows for more effective decisions to be made, which in
turn allows costs to decrease and is in the public’s best interest.
The COVID-19 Data Lake is only available for pure research with no collaboration with industry. There
remain concerns that providing researchers access to the data lake may diminish public trust. In order
to streamline the application process to the Data Lake, Israel is preparing one formal agreement for
researchers that want to access the data, since this data is needed in a timely manner due to COVID-19.
Further, Israel is considering new technologies for privacy enhancement that support researchers’
ability to access complete records (raw data).
Source: Magazanik (forthcoming[11]), “Supporting Health Innovation With Fair Information Practice Principles: Key issues emerging from the
OECD-Israel Workshop of 19-20 January 2021”.

The Government of Canada, together with provinces and territories, is leading the development of a PanCanadian Health Data Strategy to improve Canada’s collection, sharing and use of health data while
protecting privacy. An Expert Advisory Group (EAG) was established in December 2020 to provide advice
and guidance as work on the Pan-Canadian Health Data Strategy evolves.
Slovenia began developing a national health data governance framework in 2019. Luxembourg is planning
a National Health Observatory which will be authorised by law and will support the development of a
national health data governance framework. Belgium reported an intention to increase co-operation among
several federal health administrations (Federal Public Service Health (FPS Health), RIZIV-INAMI, FAGG)
regarding data policy.

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38 
The United Kingdom (Scotland) has an information governance framework for personal data, within which
is a Public Benefit and Privacy Panel (PBPP) for health and social care data. The PBPP is a patient
advocacy panel which scrutinises applications for access to NHS Scotland health data for secondary
purposes with respect to the public benefit and privacy implications of proposed projects.

Legal or policy restrictions to public authorities extracting data from electronic health
records
While many countries are extracting data from electronic clinical records to develop their key national
datasets and for research (as will be discussed in the next section), 10 survey respondents in a 2019-20
survey on health data governance reported barriers to doing so.
In Luxembourg, data extraction from electronic clinical records for secondary uses is only lawful with the
prior written consent of patients. Similarly, in Canada, electronic medical records in primary health care
are in the custody and control of care providers who have no obligation and sometimes, depending on the
jurisdiction, no legal authority to share data with public authorities, without express consent. As in Canada,
the federal structure of Germany leads to different legal frameworks at the state level (state data protection
laws, state hospital laws) that govern whether data may be extracted for secondary purposes. In Australia,
data extraction is restricted by a number of legislative, privacy, secrecy and confidentiality requirements
and medical records can be disclosed with consent, or in specified circumstances where authorised by
law.
In France, extracting data from the electronic health record or DMP (dossier médical partagé) for the
purposes of sharing and linking data is legally prohibited. France reports the legal prohibition came about
because the national health insurance fund (CNAM) provides operational management of the linked health
care administrative database and patients’ associations sought a guarantee that clinical data within the
DMP would not be accessible to the insurer. It is, however, legally possible to create a dataset of
anonymised data from DMP records.
In Japan, there is no national electronic health record system within which data might be contributed by
each medical institution. Further, medical institutions require patient consent for each research or statistical
project where data would be extracted and shared from their electronic records.
In Korea, it is legally possible to extract data from electronic health records for secondary uses but the
interpretation of the law is strict so doing so is difficult in practice. In Belgium there is no real policy about
the extraction of data from electronic records for secondary uses. In Latvia, there is no experience yet with
data extraction as the implementation of the national e-health system has only started recently. In Ireland,
most health records remain paper-based in acute care hospitals.
Concerns were further echoed by respondents to the 2021 EHR survey. In 2021, 15 respondents reported
that problems with the quality of data within electronic clinical record system created a barrier to developing
national health datasets from this data source. The most common concern was with unstructured (free
text) data within EHRs that need to be structured following common terminology standards to be readily
useable for statistics and research. Thirteen respondents also reported legal or policy barriers to public
authorities extracting data from within EHRs to develop national health datasets.
Perhaps the most difficult barrier is in Switzerland, where the law which authorises the creation of electronic
clinical records did not foresee the use of data from within this information system for national statistics or
research and, as a result there is a total ban on utilising this information resource for any purpose within
the public interest other than directly caring for an individual patient. Similarly, in Korea, the law authorising
the Information Exchange Program only authorised the exchange of EHR records for direct patient care
and there is no legal basis for the secondary use of EHR data.

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 39
In Sweden, whether data can be extracted from EHRs for a statistical purpose is limited to the legal
authorisation of the specific use. Statistics and research uses that have not been already foreseen and
legally authorised are restricted. Similarly, Finland’s law authorising the EHR system did not specify that
health care quality monitoring could be undertaken with data from within the EHR system and are facing
restrictions to this activity which is within the public interest. In Iceland, health data registries (datasets) are
each authorised by a separate legislation. If a new registry (dataset) is needed, then it is necessary to pass
a new legislation to authorise it. Similarly, Portugal reports a lack of legal authorisation to extract data for
statistical purposes.
Japan and Turkey report concerns that the national data privacy law restricts their ability to extract data
from within their EHR systems to build national datasets that are within the public interest. Canada reports
the challenge of having different data protection laws within its 13 provinces and territories.
EU Members are also reporting challenges implementing the EU General Data Protection Regulation
(GDPR). Italy reports that the GDPR provisions are complex and require the involvement of the data
protection authority to develop effective solutions that support extraction of data from EHRs for statistical
purposes. Similarly, Slovenia reports that the national legislation is very sophisticated and restrictive which
limits their ability to extract data for statistical purposes.
In the Netherlands, problems have arisen following the introduction of the EU GDPR. Dutch health datasets
are in the custody of various public sector organisations (such as the Dutch Hospital Data institute, and
the Perined (child birth data) institute). Among the custodians of health data, there are different
interpretations of the EU GDPR and some have determined that past data exchange arrangements are no
longer legally permitted. To clarify that data exchange is lawful, some organisations and institutes are
asking government for legislation authorising the exchange of electronic clinical data (see Chapter 3 for
further discussion).

EMR interoperability is critical with success characterised by co-ordination and
leadership at the national level
Clinical data are a key component of any health information system looking to improve care quality as well
as enabling research and innovation. This section outlines the current situation in OECD countries
regarding the exchange and interoperability of electronic health records data, and the key elements of
successful integration.

Exchange of clinical data at the national level
Most OECD countries, 21 of 27 countries surveyed in 2021, are exchanging electronic clinical records
among physicians, medical specialists and hospitals for the direct care of patients. Sixteen countries report
one country-wide EHR system is in place. Thirteen countries reported that a nationally standardised patient
summary is exchanged among health care providers at a national level, and a broader array of patient data
are exchanged among health care providers at the sub-national (state, regional) level. In three countries,
Belgium, Canada and the Czech Republic, patient data is exchanged among health care providers only at
the sub-national (regional, state) level.

A single authority to oversee EHR development and interoperability
In 2021, the OECD surveyed countries regarding the readiness of their electronic health record systems
to contribute to national information and research. Twenty-three of 27 countries reported a national
organisation with primary responsibility for national EHR infrastructure development. Twenty countries

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40 
reported that their national organisation is responsible for setting national standards for both clinical
terminology within EHRs and standards for data exchange (electronic messaging).

Table 2.2. National organisation responsible for EHR system and its role
Country

National
organisation
with primary
responsibility
for national
EHR
infrastructure
development

Name of the
organisation

National
organisation
sets
standards
for clinical
terminology
in Electronic
Health
Records

National
organisation
sets
standards
for
electronic
messaging

Other major responsibilities of this national organisation

Australia

Yes

Australian
Digital Health
Agency (ADHA)

Yes

No5

Coordinates and reviews Australia’s National Digital Health
Strategy.

Belgium

Yes

eHealth Platform
and FPS Health

Yes

Yes

National eHealth services

Canada

Yes1

Canada Health
Infoway

Yes

Yes

Accelerates the development, adoption and effective use of digital
health solutions. Independent, not-for-profit organisation
established in 2001 and funded by the federal government.

Costa Rica

No

n.a

n.a

Czech Republic

Yes

Ministry of
Health,
Department of
Informatics and
Electronic
Healthcare
(ITEZ)

Yes6

Yes6

Focuses on the e-health strategy and maintenance of national
information standards. Implementation of the infrastructure is
provided by UZIS.

Denmark

Yes

Danish Health
Data Authority

Yes

Yes

National registries, secondary use of data, statistics in health and
reimbursement schemes

Estonia

Yes

Centre of Health
and Welfare
Information
Systems

Yes

Yes

Organises and co-ordinates the administration of ICT
development and management of strategies, development plans
and budgets. Role includes strategic planning of information
systems and e-services; advise to government; responsibility for
information systems and databases; improvement of the
interoperability and exchange of information of e-solutions;
integrated management of the IT architecture; development and
management of cross-border data exchange services; services,
software and information systems procurement; implementation
of best practices for the protection of personal data;
implementation of the information security policy; monitors the
use and security of information systems and compliance
information security regulations; inspections, as necessary of
information systems, data integrity and security. Responsible for
ICT under the MoH including infrastructure, data communications,
data security, backup, systems administration; software support
for ICT, ICT governance and development, systems integration,
maintenance and computer support, and user support services.
data transmission formats, data control rules and data
transmission systems related to information systems,
development and management of classifications; management of
technical data quality related to information systems; creates and
manages a data warehouse which enables to fulfill the tasks
assigned to the processor authorised by legislation

Finland

Yes

Social Insurance
Institution (Kela)

Yes

Yes

National rules and mandatory requirements for systems

Germany

Yes

Gematik GmbH

n.r.

n.r.

Hungary

Yes

Ministry of
Health and
Director General

n.r.

n.r.

General country-wide responsibility for health care systems

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 41
Country

National
organisation
with primary
responsibility
for national
EHR
infrastructure
development

Name of the
organisation

National
organisation
sets
standards
for clinical
terminology
in Electronic
Health
Records

National
organisation
sets
standards
for
electronic
messaging

Other major responsibilities of this national organisation

of National
Hospitals
(OKFO)
Iceland

Yes

Directorate of
Health, National
Centre for
eHealth Unit

Yes

Yes

Development and implementation of national digital solutions in
health care, including the integrated electronic health record and
the national patient portal, eHealth strategies, clinical terminology
standards and the Icelandic HealthNet.

Israel

No2

Ministry of
Health

Yes

Yes

Italy

Yes

Ministry of
Economy,
SOGEI (inhouse system
integrator)

Yes

Yes

Sets strategic objectives, evaluates the ongoing activities and
results, and defines the functional and technical specifications for
EHR documents.

Japan

Yes

Health
Insurance
Claims Review
and
Reimbursement
Services and
All-Japan
Federation of
National Health
Insurance
Organisations

Yes

Yes

Payments of medical fees, system implementation supports, etc.

Korea

Yes

Korean Health
Information
Service (KHIS)

Yes

Yes

Department responsible for developing EHR infrastructure
including standardisation, personal health records (PHR), health
information data exchange, and certification (criteria
development, business, education). A separate department is
established for EHR data utilisation.

Lithuania

Yes

Ministry of
Health and State
Enterprise
Centre of
Registers

Yes

Yes

Formulates state policy, organises, co-ordinates and controls its
implementation, including digitisation of health care sector and is
the controller of the State Electronic Health Services and
Co-operation Infrastructure
Information System (ESPBI IS)

Luxembourg

Yes

Agence eSanté

Yes

Yes

Set up and operate a national electronic platform for the
exchange and sharing of health date; promote interoperability and
security in health information systems; establish and maintain
roadmap for health information systems; assist regulators and
authorities on strategic choices related to health information
systems; and disseminate information on operational procedures
and security measures.

Mexico

n.r.

n.r.

n.r.

Netherlands

Yes

n.r.

Yes

Yes

National Health Information Council (Informatieberaad zorg). In
that council both health care organisations and the Ministry of
Health work on the sustainability of the information framework in
health care. Four goals are: 1) safety of prescribing, 2) citizens
can see their own medical data and link these to their own health
data, 3) digital and standardised transfer of data between health
professionals, 4) data is recorded once and then reused.

Norway

Yes

Norsk Helsenett

No7

No7

Develop, manage and operate national e-health solutions, core
journal and e-prescription, as well as basic data in various
registers and provide the national infrastructure for electronic
communication in the health sector.

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42 
Country

National
organisation
with primary
responsibility
for national
EHR
infrastructure
development

Name of the
organisation

National
organisation
sets
standards
for clinical
terminology
in Electronic
Health
Records

National
organisation
sets
standards
for
electronic
messaging

Other major responsibilities of this national organisation

Portugal

Yes

SPMS (Shared
Services for the
Ministry of
Health, EPE)

Yes

Yes

Russian
Federation

Yes

Ministry of
Health
and Ministry of
Digital
Development,
Communications
and Mass Media

Yes

Yes

Slovenia

Yes

National Institute
of Public Health
(NIJZ)

Yes

Yes

Public health authority

Sweden

Yes and No3

Multiple
agencies
involved at
national and
regional levels

Yes

Yes

Coordination of eHealth initiatives among regional health
authorities

Switzerland

Yes

eHealth Suisse

Yes

Yes

Creation and update of the conceptual basis for the EHR
certification process; creation and update of the requirements of
the central components / services necessary for a running EHR
(metadata index, community portal index services, HP index
service and others /run by the Federal Office of Information
Technology, Systems and Telecommunication FOITT; and EHR
information and co-ordination

Turkey

Yes

Ministry of
Health

Yes

Yes

United States

No4

n.a.

n.a.

Public enterprise created in 2010 under the guardianship of the
Ministries of Health and Finance. Provides shared services to
health organisations: ICT, purchasing and logistics, financial
services and human resources and centralises the procurement
of goods and services within the NHS. SPMS is a corporate legal
entity with administrative and financial autonomy and its own
assets. SPMS is a Competence Centre with the main
responsibility of implementation and operation of Health
Information Systems to be used in the Portuguese Health System
and it is the national authority for eHealth cross border
co-operation. SPMS promotes the definition and use of
standards, methodologies and requirements that guarantee
interoperability and interconnection of health information systems
with each other and with cross-sectional information systems of
the Public Administration. It works with other EU countries to
share knowledge and to align and adopt common standards (e. g.
HL7 and IHE).

Notes: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Canada Health was in a lead role for the development and implementation but it is managed by each jurisdiction.
2. EHR are regulated by the Ministry of Health.
3. Some aspects are co-ordinated between a few authorities.
4. US Department of Health and Human Services adopts national standards and regulates the certification of EHR products. Governance of the
exchange infrastructure is currently being defined.
5. ADHA specifies which messaging standards are required to allow other clinical systems and mobile applications to connect with the My Health
Record System.
6. MoH recommends standards. Legislation is in preparation to create a legal mandate to enforce e-Health related standards.
7. Norwegian Directorate for e-health is responsible to set standards for clinical terminology and data exchange.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

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 43
Fourteen countries reported in 2021 that the national organisation responsible for EHR infrastructure
development had a multidisciplinary governing body with representation from various stakeholder groups.
Multi-disciplinary governance supports the development of standards that meet the needs of different
stakeholders in the health information system.

Table 2.3. National organisation has a multidisciplinary governing body
Country

Governing
body of the
national
organisation
is multidisciplinary
with
representation
from various
stakeholder
groups

Stakeholder groups represented within the governing body of the national organisation

Australia

Yes

Governed by a Board and a person is eligible for appointment as a Board member only if the Health Minister is
satisfied that the person has skills, experience or knowledge in at least one of the following fields: medical practice;
health informatics, health technology standards and information management in large scale health settings; health
care delivery; delivery of private health services; consumer health advocacy; designing, developing and delivering
innovative uses of technology; developing, implementing and managing national digital health policies, strategies and
services; developing, implementing and operating clinically safe work practices, methods and patient safety solutions
in relation to digital health services; financial management; providing legal services and advice; managing and
delivering digital health systems in State and Territory health facilities; and leadership and management in the
delivery of traditional and digital health services that are managed, operated or provided by a State or
Territory Government.

Belgium

Yes

Involves all health stakeholders: health care providers and organisations, patients, mutual funds, public institutions,
Communities and Regions, etc.

Canada

No

Membership of Infoway is Deputy Ministers of Health for the Federal, Provincial and Territorial Governments. Infoway
is responsible for engaging a wide variety of stakeholders (clinicians, patients, governments, vendors, academia, etc.)

Costa Rica

n.a

Czech Republic

n.r.

Denmark

No

Estonia

No

Finland

Yes

THL and Kela have, to some extent, a multi-disciplinary employee base and have multi-disciplinary stakeholder
groups and steering mechanisms.

Germany

Yes

Shareholders are the Federal Ministry of Health (BMG), the Federal Medical Association (BÄK), the
Bundeszahnärztekammer (BZÄK), the German Association of Pharmacists (DAV), the German Hospital Association
(DKG), the Central Association of Statutory Health Insurance Institutions (GKV-SV), the Federal Association of
Statutory Health Insurance Physicians (KBV), the Association of Statutory Dentists (KZBV) and the Private Health
Insurance Association (PKV).

Hungary

No

Iceland

Yes

Israel

Yes

Italy

Yes

Japan

No

Korea

No

Lithuania

No

Luxembourg

Yes

Health professionals and relevant stakeholder groups are contacted to form working groups to work on different
eHealth projects. Moreover, health professional surveys and citizen surveys are conducted on a regular basis.
Representatives of the institutions (different Ministries and Regions) and stakeholders: doctors, nurses and
apothecaries associations, and municipalities associations.

Agence eSanté GIE is established in the form of an Economic Interest Grouping which counts as members the major
health care related stakeholders, namely: Luxembourg State represented by the Ministry of Health and the Ministry of
Social Security; National Health Fund (Caisse Nationale de Santé); Social Security Office (Centre Commun de la
Sécurité Sociale); Association of Doctors and Dentists (Association des Médecins et Médecins-Dentistes);
Luxembourg Hospital Federation (Fédération des Hôpitaux Luxembourgeois); Confederation of long term and home
care providers (Confédération des organismes prestataires d’aides et de soins; Luxembourg federation of laboratories
(Fédération Luxembourgeoise des Laboratoires d’Analyses Médicales); the association of Pharmacists (Syndicat des

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44 
Country

Governing
body of the
national
organisation
is multidisciplinary
with
representation
from various
stakeholder
groups

Stakeholder groups represented within the governing body of the national organisation

Pharmaciens Luxembourgeois); Association for the Defence of Patients’ Interests (Patientevertriedung).
Mexico

n.r.

Netherlands

Yes

Norway

Yes

Portugal

Yes

Russian
Federation

No

Slovenia

No

It is a public institution, appointed by the Ministry of Heatlh. Other stakeholders are involved indirectly.

Sweden

Yes

Coordination of eHealth initiatives among regional health authorities

Switzerland

Yes

All relevant stakeholders groups included such as political authorities (federal level and cantons), physicians, other
HPs associations, hospitals, insurances and so on.

Turkey

Yes

Personnel of the health care system that is developed and managed by Ministry of Health.

United States

n.a.

It includes several workgroups including stakeholders.

Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

Convergence towards specific standards is occurring
Global consensus regarding terminology standards for key clinical terms has not been reached yet. There
are, however, a few international terminology standards that are used by a significant share of countries.
In 2021, 18 respondents reported using the International Statistical Classification of Diseases and Related
Health Problems, 10th Revision (ICD-10) for diagnostic terms; 16 respondents reported the Anatomical
Therapeutic Chemical (ATC) Classification System for medication terms; 13 respondents reported the
Logical Observation Identifiers Names and Codes (LOINC) for laboratory test terms; and 10 respondents
reported DICOM standards for medical image terms. These results for 2021 are a small improvement from
2016, as the number of respondents adopting the ICD-10 diagnostic terms and ATC medication terms has
grown by a few countries.
Twelve respondents reported adopting the Systematised Nomenclature of Medicine-Clinical Terms
(SNOMED CT) for at least one key term within their EHR. SNOMED CT is a comprehensive set of
terminology standards covering key terms within EHR records. The cost of deployment; however, is a
barrier to widespread adoption and the number of respondents is unchanged from 2016.
However, there remain key terms within clinical records where there is no consensus among countries
about which international standard could apply. These include surgical procedures, vital signs, healthy
behaviours, socio-economic status, clinically relevant cultural and psychosocial characteristics, and patient
reported outcomes and experiences. Further, there are often local standards that have been adopted or,
in some cases, these elements are not coded to a terminology standard but recorded as free text.
The legacy of fragmented deployment of EHRs has resulted in 11 respondents reporting clinical
terminology standards are inconsistent among different networks or regions within their country. While this
remains a significant problem, it has improved from 2016 when 20 respondents reported this issue.
Twenty-one respondents in 2021 reported implementing policies or projects to improve the interoperability
of data within electronic health record systems (EHRs). Seventeen respondents are adopting the HL7 Fast

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 45
Healthcare Interoperability (Resource) standard and a further two respondents are considering adoption.
The HL7 FHIR standard supports web-based applications in health care as they exist for other sectors
such as for e-commerce, banking, and travel booking; and utilises commonly used web development tools
which allow for a larger pool of developers and faster development.
Twelve respondents are also adopting SMART on FHIR standards (or similar) and a further 4 respondents
are considering adopting SMART on FHIR. Substitutable Medical Applications and Reusable Technologies
(SMART) is a standard used on top of FHIR to develop web-browser and mobile/smartphone apps that
can be connected to/interact with any EHR system. For example, an app to assist patients with managing
their medications or an app for secure communication with a health care provider.
Fourteen respondents reported developing public application programming interfaces (APIs) and an
additional respondent is considering adopting this standard. Application programming interfaces (APIs)
allow data sharing among different EHR software and Health Information Technologies, overcoming
blockages to data interoperability.

Table 2.4. Interoperability standards
Respondent

Implementing
policies or projects
to improve EHR
interoperability

Developing public application
programming interfaces (APIs)

Adopting HL7 Fast Healthcare
Interoperability Resource (FHIR)
standard

Adopting SMART
on FHIR standards

Australia
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total Yes

Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
n.r.
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
n.r.
Yes
Yes
No
n.r.
Yes
Yes
Yes
No
Yes
21

Yes
Yes
Yes
No
n.r.
Yes
No
Yes1
n.r.
Yes
Yes
No
No
No
Yes
No
Yes
n.r.
Yes
Yes
Yes
n.r.
n.r.
Yes
No2
Yes
No
14

Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
n.r.
No
Yes
Yes
Yes
No2
Yes
Yes
Yes
n.r.
Yes
Yes
No
Yes
No
Yes
No2
No
No
17

Yes
Yes
No
No
Yes
No
Yes
Yes
n.r.
No
No2
No2
No
No2
Yes
Yes
No
n.r.
Yes
Yes
n.r.
Yes
n.r.
Yes
No2
Yes
No
12

Notes: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. May not be open (public).
2. In consideration for adoption.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.
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46 
Global collaboration towards common standards
Encouragingly, respondents reported participation in global collaborative work toward agreed international
standards for clinical terminology and data exchange (electronic messaging). In 2021, 15 respondents
reported participating in the Integrating the Healthcare Enterprise International collaboration and 10
respondents reported participating in the Global Digital Health Partnership.
There is extensive work underway within the European Union (EU) toward improving the accessibility,
sharing and use of health data that, if successful, would have an influence on the evolution of global
collaboration in the sharing, use and protection of health data. A key EU project is the eHealth Digital
Service Infrastructure (eHDSI) for cross-border health data exchange under the Connecting Europe Facility
(CEF) that is supporting EHR data exchange at the country level and the provision of core services at the
EU level.
Another key project is the Joint Action Towards the European Health Data Space (TEHDAS). TEHDAS is
developing European principles for the secondary use of health data, building upon successful
development of health data hubs in a few countries, such as France and Finland, and aiming to develop
health data governance and rules for cross-border data exchange, improve data quality and provide strong
technical infrastructure and interoperability (EC, 2021[5]). The European Health Data Space has the
potential to act as a powerful federator between national data hubs, promoting interoperability standards,
best practices for data sharing across the European Union and setting a coherent governance framework.

Table 2.5. Global collaborations for exchange and terminology standards
Respondents

Australia
Austria
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden

IHE (Integrating the
Healthcare
Enterprise)
International

Global Digital Health
Partnership

EU projects to facilitate sharing and utilising EHR data
across EU member states

No
Yes
Yes
n.r.
No
Yes
Yes
Yes
Yes
n.r.
No
No
No
No
Yes
No
Yes
Yes
n.r.
Yes
n.r.
Yes
n.r.
No
Yes

Yes
Yes
No
Yes
No
n.r.
No
Yes
No
n.r.
No
No
No
No
Yes
Yes
No
No
n.r.
Yes
n.r.
Yes
n.r.
No
No

No
Yes
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
No
Yes
Yes
n.r.
Yes
Yes
Yes
n.r.
Yes
Yes

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 47
Respondents

Switzerland
Turkey
United States
Total Yes

IHE (Integrating the
Healthcare
Enterprise)
International

Global Digital Health
Partnership

EU projects to facilitate sharing and utilising EHR data
across EU member states

Yes
Yes
Yes
15

Yes
No
Yes
10

No
Yes
No
18

Notes: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

The 2021 survey also asked respondents about the coding of health data to CDMs which facilitate within
country statistical and research projects. In 2021, five respondents reported coding data within their EHR
systems to a CDM. When the common data model is international in scope, such as the OMOP
(Observational Medical Outcomes Partnership) CDM, such coding efforts support internationally
comparable data for a wide array of research and statistical uses. There were some applications of the
OMOP CDM reported by Australia and Israel in 2021. The Health Insurance Review and Assessment
Agency (HIRA) in Korea coded linked health data to the OMOP CDM, including HIRA’s national insurance
claims data, for the purposes of encouraging secure access to timely data for global COVID-19 research
as part of the OHDSI project. France is coding data within the Health Data Hub to the OMOP CDM as part
of the EU EHDEN project which is affiliated with OHDSI.

Approaches to data storage and management vary
Surprisingly, given the mounting volume of data created, only 8 of 26 respondents in 2021 reported that
EHR data are stored or processed using Cloud Computing services (Australia, Israel, Japan, Korea,
Luxembourg, the Netherlands, Portugal and the United States). The majority of respondents are still
managing EHR data on dedicated servers.
Essential to data security, integration and patient safety are unique identifiers. In 2021, 24 of 27 countries
reported that they have a unique national number that identifies patients to build and electronic health
record. Further, 23 countries reported having a unique national number that identifies health care providers
or other authorised persons who are entering data into an electronic health record.
Fourteen respondents reported that clinical data are encrypted when they are exchanged to protect privacy
and data security. Nine respondents reported that clinical data are exchanged using a dedicated, secure
network. Security measures for these networks included a digital signature for ID (Denmark), digital
signature with smartcard (Luxembourg, the Netherlands), multi-factor authentication (Canada, Italy, the
Netherlands, Switzerland), digital certificates for ID verification (Japan, Lithuania), virtual safeboxes for
data exchange (Israel), channel encryption (Italy), and IP security and Internet key exchange (Japan). A
few respondents also noted data de-identification and pseudonymisation (Italy) and even data
anonymisation (Costa Rica).
Respondents reported methods they are using to secure EHR data from unauthorised access, hacking
and malware. These include virus scanning, firewalls, controlled access, access logs, audit logs,
automated log-out, timely software updates, network separation, auditing hardware and databases,
physical security for networked hardware, staff training in data security including how to identify phishing
schemes, malware and other malicious programs, penetration tests (ethical hacking), vulnerability
scanning, national authorities supervising cybersecurity among data processors, and business continuity
and disaster recovery planning.

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48 
Legislation requiring adoption of Electronic Health Record Systems that conform to
national standards
In the 2021 survey, 17 respondents reported that there are laws or regulations requiring health care
providers to meet standards for national electronic health record interoperability. Sixteen respondents
reported that laws or regulations require electronic messaging standards and 16 also respondents reported
that laws or regulations require terminology standards.

Table 2.6. Laws or regulations require standards for EHR interoperability
Respondent

Laws or regulations require
clinical terminology standards

Laws or regulations require
electronic messaging standards

Laws or regulations require
health care providers meet
standards for national EHR
interoperability

Australia

No

No

No

Austria

Yes

Yes

Yes

Belgium

No

No

No

Canada

n.r.

n.r.

n.r.

Costa Rica

Yes

Yes

Yes

Czech Republic

n.r.

n.r.

n.r.

Denmark

No

No

Yes

Estonia

Yes

Yes

Yes

Finland

Yes

Yes

Yes

Germany

n.r.

n.r.

n.r.

Hungary

Yes

Yes

Yes

Iceland

Yes

Yes1

Yes

Israel

Yes2

No

No

Italy

Yes

Yes

Yes

Japan

Yes

Yes

Yes

Korea

Yes

Yes

Yes

Lithuania

Yes

Yes

Yes

Luxembourg

No

Yes

Yes

Mexico

n.r.

n.r.

n.r.

Netherlands

Yes

No

No

Norway

n.r.

n.r.

Yes

Portugal

No

Yes

No

Russian Federation
Slovenia

Yes
Yes

Yes
Yes

Yes
Yes

Sweden

n.r.

n.r.

n.r.

Switzerland

Yes

Yes

Yes

Turkey

Yes

Yes

Yes

United States

n.a.

n.a.

n.a.

Total Yes

16

16

17

Notes: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Law recommends the use of EHRs.
2. For diagnosis.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

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 49
Certification of electronic health record system software vendors
In the 2021 EHR survey, 16 respondents reported that they have a certification process for the vendors of
electronic health record system software that requires vendors to conform to particular health information
exchange (electronic messaging) standards. Thirteen respondents reported a certification process that
requires adherence to national standards for clinical terminology and 13 reported certifying vendors for
adherence to requirements or standards for national EHR interoperability.
While not a national certification of software vendors, reimbursement for medical expenditures requires
that providers follow certain terminology and exchange requirements in Israel. In Luxembourg, there is a
national labelling process for software vendors to access the national EHR system. In Italy, there are no
national requirements for certification, but individual regions may impose requirements. In Slovenia,
certification has been legally authorised, but it is not yet implemented due to resource constraints.
However, to connect to the national EHR system in Slovenia, vendors must use nationally standardised
APIs (Application Programming Interfaces).

Table 2.7. Certification requirements of vendors of EHR system software
Respondent
Australia
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total yes

Conform to particular clinical
terminology standards

Conform to particular electronic
messaging standards

Conform to national e-HR
interoperability requirements or
standards

No
Yes
No
No
No
Yes
No
Yes
n.r.
Yes
No
No
No
Yes
Yes
No
No
n.r.
Yes
No
Yes3
Yes
yes
No
Yes2
Yes
Yes4
12

Yes
Yes
Yes
No
No
Yes
No
Yes
n.r.
Yes
No
No
No
Yes
Yes
No
No
n.r.
Yes
No
Yes3
Yes
yes
Yes
Yes2
Yes
Yes4
15

No
Yes
Yes1
No
No
Yes
No
Yes
n.r.
Yes
No
No
No
Yes
Yes
No
No
n.r.
No
No
Yes3
Yes
Yes
No
Yes2
Yes
Yes4
12

Notes: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Optional.
2. Certification of communities using EHR software.
3. E-prescription services are certified.
4. Certification is voluntary but required for reimbursement of medical claims from national insurance programmes (Medicare, Medicaid).
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

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50 
Auditing clinical records for quality
Another mechanism to verify if health data meet national expectations for data quality is to conduct audits
of clinical records. In the 2021 EHR survey, 13 respondents reported that the electronic records of
physicians, medical specialists and hospitals are audited to verify quality. An additional three respondents
indicated that at least one of these three groups are audited to verify quality. In most cases, it is a national
authority that is responsible for undertaking quality audits. In Canada and Sweden, regional authorities
conduct audits. In Switzerland, private sector organisations can be certified to then conduct audits as part
of certifying the compliance of communities to national requirements including auditing clinical records for
quality. Under law in the United States, health care providers are responsible for generating auditing
reports on the quality of their clinical records and ensuring data quality.

Table 2.8. Auditing clinical records for quality
Respondent
Australia
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total yes

Physicians

Medical specialists

Hospitals

All

Yes
No
Yes
Yes
No
Yes
No
n.r.
n.r.
Yes
Yes
Yes
n.r.
n.r.
No
No
No
Yes
Yes
n.r.
Yes
Yes
No
Yes
Yes
Yes
Yes
15

Yes
No
Yes
Yes
No
Yes
No
n.r.
n.r.
Yes
Yes
Yes
n.r.
n.r.
No
No
No
Yes
Yes
n.r.
n.r.
Yes
No
Yes
Yes
Yes
Yes
14

Yes
Yes
Yes
Yes
No
n.r.
No
n.r.
n.r.
Yes
Yes
Yes
n.r.
n.r.
No
No
No
Yes
Yes
n.r.
Yes
Yes
No
Yes
Yes
Yes
Yes
15

Yes
Yes
Yes
Yes
No
Yes
No
n.r.
n.r.
Yes
Yes
Yes
n.r.
n.r.
No
No
No
Yes
Yes
n.r.
n.r.
Yes
No
Yes
Yes
Yes
Yes
13

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

Policy levers used by OECD countries to increase EHR interoperability and data use
In 2021, OECD countries reported several different policy levers supporting EHR interoperability and the
increased use of data from within EHR systems for direct care, patient centred services, research, statistics,
applications development and other uses within the public interest. This section reviews countries use of laws
or regulations requiring data standards; certification of software vendors; and incentive payments.
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 51
In 2021, 13 countries reported implementing laws or regulations that require health care providers to adopt
electronic health record systems that meet national standards for both clinical terminology and electronic
messaging (data exchange).
Sixteen countries reported laws or regulations requiring health care providers to meet standards for
national EHR interoperability. In Iceland, regulations require that health care providers can connect to the
Icelandic HealthNet (national EHR network). In Italy, the law defines a national federated system with a
mandatory, nationwide, interoperability. In Lithuania, data is structured and standardised by law and must
be suitable to be forwarded smoothly to the ESPBI IS (central EHR system). In Luxembourg, connecting
to the DSP (central EHR system) requires meeting legal requirements for data standardisation. In Slovenia,
IHE XDS and OpenEHR standards are required with proprietary modifications that are set out in law. In
Switzerland, certifying communities and software vendors are required to meet national standards
including HL7 FHIR and IHE. In Portugal, by law, health care providers IT systems must conform to a
catalogue of standards to exchange data.

Table 2.9. Laws or regulations requiring adoption and standardisation of electronic health records
Respondent

Australia
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total yes

Laws or regulations require
clinical terminology standards

Laws or regulations require
electronic messaging standards

Laws or regulations require
health care providers meet
standards for national EHR
interoperability

No
No
n.r.
Yes
n.r.
No
Yes
Yes
n.r.
Yes
Yes
Yes2
Yes
Yes
Yes
Yes
No
n.r.
Yes
n.r.
No
Yes
Yes
n.r.
Yes
Yes
n.a.
15

No
No
n.r.
Yes
n.r.
No
Yes
Yes
n.r.
Yes
Yes1
No
Yes
Yes
Yes
Yes
Yes
n.r.
No
n.r.
Yes
Yes
Yes
n.r.
Yes
Yes
n.a.
15

No
No
n.r.
Yes
n.r.
Yes
Yes
Yes
n.r.
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
n.r.
No
Yes
No
Yes
Yes
n.r.
Yes
Yes
n.a.
16

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Law recommends the use of EHRs.
2. For diagnosis.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

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52 
Another policy lever is requiring vendors of electronic health records systems to be certified to be in
conformance with national data standards. Overall, 13 countries have a software vendor certification that
requires vendors to meet national standards for both clinical terminology and electronic messaging.

Table 2.10. Certification requirements of EHR software vendors
Respondent

Australia

Conform to
particular
clinical
terminology
standards
No

Conform to
particular
electronic
messaging
standards
Yes

Conform to
standards or
requirements for
national e-HR
interoperability
No

Belgium

Yes

Yes

Yes

Canada

No

Yes

Yes1

Costa Rica
Czech Republic
Denmark

n.r.
n.r.
Yes

n.r.
n.r.
Yes

n.r.
n.r.
Yes

Estonia
Finland

n.r.
Yes

n.r.
Yes

n.r.
Yes

Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden
Switzerland

n.r.
Yes
n.r.
n.r.
n.r.
Yes
Yes
n.r.
No
n.r.
Yes
n.r.
Yes
Yes
Yes
No
Yes

n.r.
Yes
n.r.
n.r.
n.r.
Yes
Yes
n.r.
No
n.r.
Yes
n.r.
Yes
Yes
Yes
Yes
Yes

n.r.
Yes
n.r.
n.r.
n.r.
Yes
Yes
n.r.
No
n.r.
No
n.r.
Yes
Yes
Yes
No
Yes

Turkey

Yes

Yes

Yes

United States

Yes

Yes

Yes

Total yes

13

16

13

Standards or requirements vendors must meet to be certified

There is a mix of CDA and FHIR capability implemented and moving to use
FHIR predominately
https://www.ehealth.fgov.be/ehealthplatform/fr/service-enregistrement-deslogiciels
https://www.infoway-inforoute.ca/en/our-partners/industry/vendor-certificationservices

National shared document standards with some connection to IHE and HL7
schemas
Detailed specifications, including terminology standards and implementation
guides
EESZT API specification and EESZT-related regulations to join to the EESZT

Japanese standard disease code and lab test code master

National standards to participate in EHR exchange
National agreed standards by SALAR/Inera
https://www.e-health-suisse.ch/technik-semantik/epdprojectathon/programmierhilfen-epd/relevante-spezifikationen.html.
HL7/FHIR/IHE, partly national adaptation of IHE integration profiles.
Semantics: SNOMED CT
Dokuman Online, SKRS, VEM, all are defined by MoH, former two defining
data collection standards while the latter one defines data transfer standard
between products from different vendors
US government’s ONC Health IT Certification Program must conform to the
full scope of the product’s required capabilities, including
regulatory/conformance expectation clarifications and interpretations set forth
in Certification Companion Guides. For a full list of vendor certification criteria
including conformance and standards required by criteria see:
https://www.healthit.gov/topic/certification-ehrs/2015-edition-cures-updatetest-method

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Optional.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

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 53
Finally, 8 countries have incentive payments or penalties for health care providers to install EHR systems
from a certified software vendor, 9 have these payments to health care providers to keep EHR systems
up-to-date regarding changes to national standards over time and 11 have incentives or penalties to meet
national requirements for EHR interoperability.

Table 2.11. Incentives or penalties to install EHR systems from a certified vendor, to keep
standards up-to-date and to meet national interoperability requirements
Respondent

Incentives
or
penalties
to install
electronic
record
systems
from a
certified
vendor

Australia

No

Incentives
or penalties
to keep the
EHR
system upto-date as
terminology
and
electronic
messaging
standards
change
over time
No

Incentives or
penalties to
adopt
standards or
other
requirements
for national
e-HR
interoperability

Description of incentives or penalties

Yes

The Practice Incentives Program eHealth Incentive (ePIP) aims to encourage general
practices to keep up to date with the latest developments in digital health. In order to
meet ePIP requirements, practices are expected to adopt compliant software for secure
messaging and the My Health Record system and make use of e-prescribing and
nationally recognised disease classification or terminology system.
As a general practitioner you are eligible for an integrated premium to support the
practice and the use of E-services (= integrated practice premium). You must then meet
a number of conditions.

Belgium

Yes

Yes

Yes

Canada
Costa Rica
Czech Republic
Denmark

No
No
No
No

No
No
No
No

No
No
No
no

Estonia

No

No

Yes

Finland

Yes

Yes

Yes

Germany
Hungary

n.r.
Yes

n.r.
Yes

n.r.
Yes

Iceland

No

No

No and Yes2

Israel
Italy

No
No

No
Yes

No
Yes

Japan

Yes

Yes

Yes

Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal

No
No
No
n.r.
Yes
No
No

No
No
No1
n.r.
Yes
No
No

No
No
No
n.r.
No
No
No

We have incentives and penalties that are not in use, but yearly economic agreements
regulate the requirements as well as the annual fiscal agreement.
Data exchange between EHNIS and health providers is a mandatory requirement in the
health service reimbursement contract between the Estonian Health Insurance Fund and
health care providers..
Legislation, decrees and rules, referring to more detailed specifications, and mandates
for supervisory authorities (other organisations) to enforce compliance.
The health care provider is bound to fulfill legal rules. National Authority can audit and
investigate the adherence of rules. In cases of non-compliance, consequences can be
warning, penalty or withdrawal of licence.
Primary health care clinics receive a refund based on the usage of the national patient
portal.
Regions receive specific funds in order to implement the EHR according to defined
objectives. Every year Regions are evaluated to verify their performance in providing
health care services within the National Health Service. Among the indicators, the
availability of specific EHR functionalities are included.
Health care providers that introduce a standardised e-HR system can receive a subsidy
from the fund to support digitalisation of medical information. In addition, in the medical
fee system, health care providers are evaluated regarding providing medical information
using the standards.

Financial penalty; no incentives

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54 
Respondent

Incentives
or
penalties
to install
electronic
record
systems
from a
certified
vendor

Russian
Federation
Slovenia

n.r.

Incentives
or penalties
to keep the
EHR
system upto-date as
terminology
and
electronic
messaging
standards
change
over time
n.r.

Incentives or
penalties to
adopt
standards or
other
requirements
for national
e-HR
interoperability

Yes

No

n.r.

Sweden
Switzerland
Turkey
United States

No
No
Yes
Yes

No
Yes
No
Yes

No
Yes
Yes
Yes

Total yes

8

9

11

Description of incentives or penalties

n.r.
Major upgrades of hospital information systems are co-financed, e.g. via joint projects
with software vendors

The US Government has programs such as the Promoting Interoperability Program
which provides incentives to health care providers to adopt certified electronic health
record technology. As previously noted, these incentives are voluntary for providers
participating in the major US public health insurance programs who benefit from
payment incentives as a result of meeting programme requirements regarding the use of
certified health IT. For more information see: https://www.cms.gov/Regulations-andGuidance/Legislation/EHRIncentivePrograms/Basics. Additionally, federal laws penalise
vendors that engage in information blocking practices or fail to comply with certification
programme requirement. Penalties may include decertification and/or civil monetary
penalties. For more information on information blocking requirements see:
https://www.healthit.gov/topic/information-blocking.

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. National terminology referential bases are put in place and maintained by Agence eSanté.
2. Incentive for primary health care clinics to use the national patient portal.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

Patient portal to their own medical records
In most countries, patients have access to and can interact with their own medical records within a secure
Internet portal. ‘Access’ means patients can view information contained in their own record and ‘interact’
means that patients can amend information, upload data or interact with their health care provider. Thirteen
countries reported that 100% of patients have access to their own medical records through an Internet
portal and 12 reported that 100% of patients can interact with their portal. Eighteen countries reported that
patients can view their own records from all of their current health care providers and containing their
current medications, lab tests, and imaging results.

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 55

Table 2.12. Patient access to and interaction with their own EHR through a secure Internet portal
Respondent

Patients can
access their EHR
via a secure
Internet portal
(Patient Portal)

Proportion of
patients who
can access

Patients view their own
records from ALL of their
current health care
providers and containing
their current medications,
laboratory tests, imaging
results within the Patient
Portal

Patients can interact with
the patient Internet Portal

Proportion of
patients who can
interact

Australia
Belgium
Canada1
Costa Rica
Czech Republic5
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian
Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total yes

Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
No
Yes
Yes

90%
80%
27%
33%
15%
100%
100%
100%
100%
40%
100%
100%
100%
100%
n.a.
100%
100%
n.a.
75%
n.a.
25%
100%

Yes4
No
No
No
No
Yes
Yes
No
Yes
Yes
No
Most
Yes
Yes
n.a.
Yes
Yes
n.a
Yes
n.a
No
Yes

Yes
No
d.k.
Yes
Yes
Yes
No
Yes
Yes
No
Yes
No
Yes
No
n.a.
Yes
Yes
n.a
Yes
n.a
Yes
Yes

0%
0%
d.k.
33%
8%
100%
n.a
100%
target: 100%
0%
100%
100%
100%
100%
n.a.
100%
n.a.
n.a
20%
n.a
25%
100%

Yes
Yes
Yes
Yes
Yes
24

5%
100%
n.r
100%
51%

Yes
Yes6
Yes
Yes
No
16

Yes3
Yes
Yes2
Yes
Yes
18

None
100%
100%2
100%
n.a.

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Regional (state/province) level differences.
2. All patients can upload PDF files to the portal.
3. To some extent.
4. When providers upload files to the national system.
5. Two regions and certain hospitals.
6. Some private providers not included.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

Secondary analysis of EHR system data
Most respondents are regularly extracting data from the EHR system for public health monitoring
(16 countries). Such uses have been accelerating in response to the COVID-19 pandemic. Further,
countries have been increasingly depending upon data with EHR systems for their superior timeliness,

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

56 
enabling analysis of the pandemic situation and response in near real time. Ten countries reported
regularly extracting EHR data to monitor the performance of the health system including, treatments, costs
and health outcomes. Twelve countries regularly rely upon EHR data to monitor patient safety, including
post-market surveillance of medications. Ten countries report that EHR data are extracted for health and
medical research to improve patient care, health system efficiency or population health, such as long-term
follow-up studies of patients experiencing different risk factors, health conditions and treatments. Five
countries are regularly relying upon EHR data to facilitate and contribute to clinical trials, such as following
clinical cohorts to measure health outcomes and health care encounters over time. Five countries also
enable physicians to query the data to inform themselves about previous treatments and treatment
outcomes when caring for patients.

Table 2.13. Regular secondary analysis of EHR system data
Respondent

Public
health
monitoring

Monitoring
health system
performance

Monitoring
patient
safety

Facilitating
and
contributing
to clinical
trials

Supporting
physician
treatment
decisions

Research to improve patient
care, health system efficiency or
population health

Australia
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian
Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total yes

No
Yes
No
Yes
Yes
Yes
Yes
Yes
n.r.
Yes
Yes
Yes
No
Yes
No
Yes
No
No
Yes
n.r.
Yes
n.r.

No
Yes
No
Yes
Yes
Yes
No
Yes
n.r.
No
No
No
No
n.r.
No
Yes
No
No
Yes
n.r.
Yes
n.r.

No
Yes
No
Yes
No
Yes
Yes
Yes
n.r.
No
Yes
Yes
No
Yes
No
Yes
No
No
Yes
n.r.
d.k.
n.r.

No
d.k.
No
Yes
No
Yes
No
No
n.r.
No
No
No
No
Yes
No
No
No
No
No
n.r.
No
n.r.

No
No
No
No
No
Yes
No
No
n.r.
No
Yes, partly1
No
No
n.r.
No
No
No
No
Yes
n.r.
No
n.r.

No
Yes
No
Yes
No
Yes
No
Yes
Yes
No
Yes
Yes
No
n.r.
No
No
No
No
Yes
n.r.
No
n.r.

Yes
Yes
No
Yes
No
16

n.r.
Yes
No
Yes
No
10

n.r.
Yes
No
Yes
No
12

n.r.
Yes
No
Yes
No
5

n.r.
Yes
No
Yes
No
5

n.r.
Yes
No
Yes
No
10

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Physicians can query their own data.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

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 57
Development of artificial intelligence algorithms, machine learning and analytics
The Netherlands, Denmark and Israel are the three countries with the most applications of machine
learning, artificial intelligence algorithm development and other more advanced analytics based on EHR
data that were measured in the 2021 survey. Overall, 8 countries reported data mining to find or extract
data from the EHR; 8 countries are using EHRs to develop messages and alerts for patient care or
managerial decision-making; and 7 countries are using EHRs to develop predictive analytics trained on
EHR data for patient care or managerial decision-making. Six countries report national projects to integrate
or link EHR data with genomic, environmental, behavioural, economic or other data. Three countries are
also using natural language processing to convert free text to standardised (coded) data.

Table 2.14. Machine learning, artificial intelligence and analytics with EHR system data
Respondent

Data mining to
find or extract
data from the
EHR system

Natural
language
processing to
convert text
based data to
coded data

Automated
alerts and
messages for
patient care or
managerial
decisionmaking

Predictive
analytics for
patient care or
managerial
decision-making
(trained on EHR
data)

Other
applications of
machine
learning/AI
developed with
EHR system
data

National projects to
integrate or link EHR
data with genomic,
environmental,
behavioural,
economic or other
data

Australia
Belgium
Canada
Costa Rica
Czech Republic
Denmark
Estonia
Finland
Germany
Hungary
Iceland
Israel
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
Norway
Portugal
Russian Federation
Slovenia
Sweden
Switzerland
Turkey
United States
Total yes

No
No
No
Yes
No
Yes
No
Yes
No
No
No
Yes
No
n.r.
No
No
Yes2
No
Yes
n.r.
Yes
n.r.
No
No
No
Yes
No
8

No
No
No
No
No
Yes
No
No
No
No
No
Yes
No
n.r.
No
No
No1
No
Yes
n.r.
No
n.r.
No
No
No
No
No
3

No
No
No
Yes
No
Yes
Yes
Yes
n.r.
No
Yes
Yes
No
n.r.
No
No
No
No
Yes
n.r.
No
n.r.
No
Yes
No
No
No
8

No
No
No
Yes
No
Yes
No
No
No
No
No
Yes
No
n.r.
No
No
Yes2
No
Yes
n.r.
Yes
n.r.
No
Yes
No
No
No
7

No
No
No
No
No
Yes
No
n.r.
n.r.
No
No
Yes
No
n.r.
No
No
No
No
Yes
n.r.
Yes
n.r.
No
No
No
No
No
4

No
Yes
No
No
No
No
Yes
No
Yes
No
No
Yes
Yes
No
No
No
No
No
Yes
n.r.
No
n.r.
No
No
No
No
No
6

Note: n.r. Not Reported // n.a. Not Applicable // d.k. Unknown.
1. Physicians can query their own data.
2. In development as part of the creation of a data lake.
Source: OECD 2021 Survey of Electronic Health Record System Development, Use and Governance.

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

58 
Summary of the situation across the OECD regarding the interoperability of EHR
systems
In 2021, most OECD countries surveyed had: 1. established a national organisation that was responsible
for setting national clinical terminology and electronic messaging (exchange) standards; 2. created a
multidisciplinary governing body for the national organisation that represents key stakeholders; 3. use
unique identification of patients and health care providers; 4. adopted international terminology
standards for diagnoses, medications, laboratory tests and medical images; 5 adopted the HL7 FHIR
standard for data exchange (electronic messaging); and participate in global collaborative projects to
improve international data standards.
Most countries have one country-wide electronic health record system and are exchanging EHRs at
the national level including data sharing among physician offices and hospitals about patients’ treatment,
medication use, laboratory tests and images.
Most countries have a Patient Internet Portal where patients can access their own medical records from
all of their current health care providers. Most are extracting data from their EHR system for public health
monitoring. Many countries are also utilising EHRs for other secondary purposes including health system
performance monitoring, patient safety surveillance and health and medical research. Some are also
developing big data analytics including machine learning, artificial intelligence algorithms with EHRs.
Countries reported several levers to improve the spread and interoperability of their electronic clinical data.


Sixteen had a legal requirement for health care providers to meet national standards for EHR
interoperability and 13 had a legal requirement for health care providers to adopt an electronic
health record system (software) that conformed with national standards for both clinical terminology
and electronic messaging (exchange).



Thirteen countries had a certification of eHR system (software) vendors that required them to
adopt national standards for both clinical terminology and electronic messaging and 13 had a
certification that required software vendors to meet requirements for national EHR interoperability.



Eleven countries had financial incentives (or penalties) for health care providers to install an EHR
system that meets national standards and requirements for national EHR interoperability. Nine
countries report incentives for health care providers to keep their EHR system up-to-date as clinical
terminology and electronic messaging standards change over time; and 8 reported incentives for
health care providers to install and EHR system from a certified software vendor.

References
Cavoukian, A. (2006), Privacy By Design: The Seven Foundational Principles, IAPP Resource
Centre, https://iapp.org/media/pdf/resource_center/pbd_implement_7found_principles.pdf.

[9]

CPME (2021), CPME Policy on the European Health Data Space, CPME 2021/097 FINAL,
https://www.cpme.eu/index.php?downloadunprotected=/uploads/adopted/2021/3/CPME_AD_
Board_20032021_097.FINAL_.CPME_.Policy.on_.EU_.health.data_.space_.pdf.

[7]

EC (2021), European Health Data Space, https://ec.europa.eu/health/ehealth/dataspace_en.

[5]

EC (2021a), e-Health Digital Health and Care - European Health Data Space,
https://ec.europa.eu/health/ehealth/dataspace_en.

[6]

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 59
EMA (2021), DARWIN EU Coordination Centre, Technical specifications for competitive
procedure with negotiation, EMA/128740/2021, https://www.ema.europa.eu/en/about-us/howwe-work/big-data/data-analysis-real-world-interrogation-network-darwin-eu.

[8]

Institute of Medicine (2004), “Health Care Data Standards”, in Patient Safety: Achieving a New
Standard for Care, National Academies Press, Washington, D.C.,
http://dx.doi.org/10.17226/10863.

[3]

Magazanik, L. (forthcoming), Supporting Health Innovation With Fair Information Practice
Principles: Key issues emerging from the OECD-Israel Workshop of 19-20 January 2021,
OECD.

[11]

Oderkirk, J. (2021), “Survey results: National health data infrastructure and governance”, OECD
Health Working Papers, No. 127, OECD Publishing, Paris, https://doi.org/10.1787/55d24b5den.

[10]

Open Data Institute (n.d.), What is data Infrastructure, https://theodi.org/topic/data-infrastructure/.

[2]

Schulz, S., R. Stegwee and C. Chronaki (2018), “Standards in Healthcare Data”, in
Fundamentals of Clinical Data Science, Springer International Publishing, Cham,
http://dx.doi.org/10.1007/978-3-319-99713-1_3.

[4]

Van Driesden G, W. (2021), Quick Guide to Dutch Healthcare, De Argumentenfakriek,
https://www.argumentenfabriek.nl/products/quickguidedutchhealthcare/.

[1]

Notes
1 In addition, the Youth Act, which regulates assistance provided to children, adolescents and their parents

– which is a municipal responsibility. It covers developmental and parenting support for families,
psychosocial and psychiatric problems, supplementing what families cannot do themselves.

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

60 

3 The strengths and weaknesses of

the current Dutch way of managing
health and social care data

This chapter describes the key strengths and limitations of the Dutch health
system in terms of establishing an integrated health information system. It
examines key legislation and policies, health data infrastructure and health
data interoperability for several purposes including direct patient care,
measuring health care quality, developing personal health environments,
and enabling research infrastructures for the life sciences and the social
sciences. Several key strengths and advantages are identified. But the
chapter highlights some of the problems brought about by a fragmented,
market-based system for smooth exchange of, and access to, health data
for various purposes that are in the public interest. The chapter identifies
the need for a generic, co-ordinated policy strategy towards digitalisation
that is under the stewardship of the central government and includes a
broad array of stakeholder groups in its design and implementation.

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 61
The previous chapter outlined the key characteristics of the Dutch health system and how these influence
the management and use of data to achieve policy objectives. It described the main features of an
integrated health information system in normative and positive terms. It also explained how developments
in health data governance and in interoperable electronic health record systems (EHRs) compare across
OECD countries and highlighted related European projects.
This chapter examines the main strengths and shortcomings of current arrangements in the Netherlands
regarding the establishment of an integrated health information system including legislation and policies,
health information infrastructure and health data interoperability. Separate discussions and initiatives are
taking place within the Netherlands about the interoperability of clinical data for direct patient care, for
measuring health care quality, developing of personal health environments, and about the creation of
research infrastructures for the life sciences and the social sciences. But a national effort toward creating
an integrated health information system that could modernise patient experiences, support integrated
health care delivery, improve monitoring of public health, support evidence-based policy making, and
encourage innovations in health technologies and advancements in life sciences and social science
research is still mostly absent.
The importance of such a system has recently been highlighted in the Dutch media,1 which reported
difficulties with transferring COVID-19 patients between hospitals because their medical information cannot
be exchanged electronically. This results in not only delays and inefficiencies – with busy clinicians having
to manually transcribe patients’ data from the local electronic record to a CD to send with the patient – but
also the risk of subsequent medical errors that manual transcribing of information entails.
Before the elections in the Netherlands in March 2021, the majority of political parties expressed the need
for further digitalisation in general and the need to address digitalisation in health care specifically.
Following the acceptance of the new law on interoperability of health care data (WEGIZ) in both chambers,
follow up plans have been published and discussed in parliament (i.e. letter of the minister of health to
parliament of 15 October 2021). The need for a more generic strategy towards digitalisation under the
stewardship of government seems to be broadly supported and will likely result in further steps by a new
cabinet. At the time of writing, coalition talks between the four parties presently comprising the cabinet are
taking place with the intention to reach agreement on programme and composition of a new cabinet.

Several strengths and advantages will enable creating an integrated health
information system
Netherlands performed well compared with OECD countries in many aspects of health data maturity, use
and governance in the 2019-20 OECD survey discussed in Chapter 2. In most cases, the data needed to
achieve an integrated health information system and fulfil the government’s policy objectives exist. All that
is needed are a set of consistent rules to connect actors in the information system together and to enable
access to the right data by the right people at the right time.
Expert consultations revealed other strengths. For example, patient engagement and leadership of patient
groups toward data interoperability is strong in the Netherlands. Significant progress has been made in
developing data exchange standards. The Informatieberaad Zorg (IB) has made good progress in
advancing the case for data exchange for better care delivery, although the IB is a voluntary body with no
legal status or funding and its membership and focus is limited to primary users and use of health data.
The Dutch Erasmus University MC leads the development of an open science federated network of data
providers in Europe called the European Health Data & Evidence Network (EHDEN) that are coding health
and health care data to the global Observational Medical Outcomes Partnership (OMOP) common data
model (EHDEN, 2021[1]). The CBS provides an example of good practice, but its limited remit prevents it

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

62 
from working actively in the health space. Two Dutch initiatives – ODDISSEI and Health RI – exhibit the
right characteristics to promote better data management for secondary purposes.
In addition, the Netherlands has a unique ‘can-do’ culture with a strong tradition of finding solutions to
seemingly intractable problems. This has often relied on striking a balance between individual liberty and the
need for collective action (it is, after all, a country that manages to not only exist but thrive below sea level).
An example of local innovation in this context is the personal health train – an important technology developed
in the Netherlands, which can enable data exchange on a distributed/federated network thus avoiding the
need for central aggregation of personal data (Dutch Tech Centre for Life Sciences, 2021[2]). Similarly, the
EHDEN project is a federated network that avoids the need for central aggregation of personal data.

Data custodians in the Netherlands adopt different approaches to health data
governance and exchange
The Netherlands’ health data landscape is characterised by the highest number of data custodians
reported in the OECD. This fragmented structure does not preclude being able to leverage available data
to achieve the objectives listed earlier. It does, however, create greater challenges to data sharing and
integration than in other countries.
A 2019/20 OECD survey found that most OECD countries have 3 to 5 custodians of the 13 national health
and health care datasets considered integral to a national health information system. Custodians of these
data are usually national governmental organisations such as health ministries, national statistical offices
or health information agencies funded by the government (Oderkirk, 2021[3]).
The Netherlands reported nine separate custodians of key national data sets, with only one custodian
being a fully governmental body, the CBS. Most data custodians are either government-funded
autonomous foundations or institutes, or private-sector funded non-profit organisations (Table 3.1).
Dutch health data custodians adopt different approaches to health data governance, including policies
around data sharing and access to data for within-country and cross-border statistical and research
projects (Table 3.2 and Table 3.3). Further, their adoption of best practices to protect privacy and data
security, including ‘privacy-by-design’ varies.
The lack of a Common Data Model for health and related social and socio-economic data, as well as a
common data governance framework for data exchange, dataset linkage and integration, translates into
each instance where data need to be integrated across different organisations becoming a separate project
requiring a great deal of effort to standardise data elements, develop governance arrangements, seek
approval for data sharing and integration and so on. In new data integration projects, the majority of funding
and human effort is taken up by these preliminary steps and the analytical and publication steps are a
minority of the effort.
Nonetheless, the Netherlands conducts projects on a regular basis that require record linkage across key
national health datasets. The key national health datasets investigated by the OECD in 2019-20 include
hospital and mental hospital in-patients, emergency care, primary care, prescription medicines, cancer,
diabetes and CVD registries, long-term care, population health survey, patient-experiences survey and
mortality data.
With the strong flow of health care data to the Netherlands CBS, the Netherlands is among a minority of
OECD countries who regularly link health and health care data to a rich set of contextual data about risk
factors, living conditions, socio-economic status and demographic data. Population registry (demographic)
data are linked with hospital inpatient, mental hospital inpatient, primary care, cancer registry, long-term care,
mortality and population health survey data. Tax data (income) are linked to hospital inpatient, long-term care
and population health survey data. Quality of life questionnaire data are linked to cancer registry data.
TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

 63
However, there are key datasets in the Netherlands that are not regularly linked and that are crucial to
understanding health trajectories and outcomes including national data on prescription medicines as well
as data within the national cardiovascular disease and diabetes registries and data on patients in
emergency health care.

Table 3.1. Custodians of the Netherlands key national health datasets
Key National Health Dataset

Dataset Custodian

Hospital in-patient data
Mental hospital In-patient data
Emergency health care data
Primary care data
Prescription medicines data
Cancer registry data
Diabetes registry data
Cardio-vascular disease registry
Mortality Data
Formal long-term care data
Patient experiences survey data
Population health survey data
Population Census/Registry data

Dutch Hospital Data (DHD) + CBS
NZa (Nederlandse Zorgauthoriteit)
Veiligheid NL (Consumer and Safety Institute)
Nivel (Nederlands Instituut voor Onderzoek van de Gezondheidszorg)
Zorginstituut Nederland (ZiN)
Netherlands Comprehensive Cancer Organisation (IKNL)
DPARD (Dutch Pediatric and Adult Registry of Diabetes)
Nederlande Hart Registratie (Dutch Heart Registration)
CBS (Centraal Bureau voor de Statistiek)
Several organisations (CIZ, Het CAK, NZa, ZIN, SVB, Bureau Jeugdzorg, Vektis)
n.a.
CBS (Centraal Bureau voor de Statistiek)
CBS (Centraal Bureau voor de Statistiek)

Source: OECD 2019-20 Survey of Health Data Development, Use and Governance. See Oderkirk (2021[3]), “Survey results: National health
data infrastructure and governance”, https://doi.org/10.1787/55d24b5d-en.

Table 3.2. Sharing and access to de-identified data varies by health dataset custodian
Analysts from the following organisations could be approved access to de-identified data for statistical or research
purposes in the public interest
Hospital
inpatient
data
Government
ministry or
government
national data
custodian

Yes

Mental
hospital
inpatient
data
Yes

Emergency
health care
data

Primary
care
data

Prescription
medicines
data

Cancer
registry
data

Diabetes
registry
data

Mortality
data

No

Cardiovascular
disease
registry
data
Yes

No

Yes

Yes

Yes

Yes

Formal
longterm
care
data
Yes

% of
national
health
care
datasets
80%

University or
non-profit
research
institute

Yes

No

Yes

Yes

Yes

Yes

No

Yes

Yes

Yes

80%

Health Care
Provider

Yes

No

Yes

Yes

Yes

Yes

Yes

Yes

No

No

70%

For-profit
business

No

No

No

No

Yes

No

No

Yes

No

No

20%

Foreign
university or
non-profit
research
institute

No

No

Yes

Yes

Yes

Yes

No

Yes

Yes

No

60%

Source: OECD 2019-20 Survey of Health Data Development, Use and Governance. See Oderkirk (2021[3]), “Survey results: National health
data infrastructure and governance”, https://doi.org/10.1787/55d24b5d-en.

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

64 

Table 3.3. Data protection and security policies and practices vary by dataset custodian

Legislation
authorises dataset
creation

Hospital Mental
inhospital
patient
indata
patient
data
Yes
Yes

Emergency
health care
data

Primary care Prescription Cancer Diabetes
data
medicines registry registry
data
data
data

Cardiovascular
disease
registry data

Mortality
data

Formal
long-term
care data

No

Yes

Yes

No

Yes

Yes

Yes

Yes2

% of
national
health
care
datasets
80%

Data Protection
officer

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes2

Yes

100%

Control and
tracking of staff
data access

Yes

Yes

No

No

No

Yes

Yes

No

Yes

Yes

60%

Process to assess
risk of data
re-identification

Yes

Yes

No

Yes

No

Yes

No

Yes

Yes

Yes

70%

Treatment of
variables posing a
reidentification
risk

Yes

Yes

Yes

Yes

No

Yes

Yes

No

Yes

Yes

80%

Public description
of the dataset
including its legal
basis

Yes

No

Yes

Yes

Yes

n.r.

Yes

Yes

Yes

No

70%

Sharing data with
external
researchers is
legally authorised

Yes

Yes

No

Yes

Yes

No

Yes

No

Yes

Yes

70%

Individuals
consent or opt-out
to data sharing

No

Optout

Opt-out

Opt-out

Consent

No

Optout

No

Consent/
opt-out

Consent

70%

Procedure to
request access to
data and approval
criteria are public

Yes

Yes

No

Yes

No

Yes

Yes

Yes

Yes

Yes

80%

Procedure to
request a dataset
linkage and
approval criteria
are public

n.a.

Yes

No

Yes

No

Yes

No

Yes

Yes

Yes

60%

Approval body for
dataset linkages

n.a.

n.r.

Veiligheid
NL
(Consumer
and Safety
Institute)

GPs and
privacy
committee

n.r.

n.a.

n.a.

Board of
directors

Central
Bureau of
Statistics

Health
care
insurers

50%

Standard data
sharing
agreement

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

100%

Secure remote
data access
service

Yes

Yes

No

No

No

No

No

Yes

Yes

No

40%

Supervised
research data
centre

No

No

No

No

No

No

No

Yes

Yes

Yes

30%

Source: OECD 2019-20 Survey of Health Data Development, Use and Governance. See Oderkirk (2021[3]), “Survey results: National health
data infrastructure and governance”, https://doi.org/10.1787/55d24b5d-en.

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 65

Legislation, regulations and their interpretation can hinder data exchange
In their submission to the 2019-20 OECD survey, Dutch officials reported that organisations can create
datasets and can undertake dataset linkages only if their proposed activities meet the requirements of the
EU General Data Protection Regulation (GDPR) and the Medical Treatment Act. The Netherlands’ Data
Protection Authority evaluates whether datasets meet GDPR requirements.
However, without national health data governance guidelines for the implementation of the GDPR, officials
reported that dataset custodians each have their own interpretation of the GDPR and that some have
interpreted the GDPR as indicating that past data exchange arrangements are no longer legally permitted.
For example, sharing data between custodians for the purpose of calculating indicators of health care
outcomes by health care institution is often considered legally prohibited.

The current approach reduces benefits while increasing risks to data privacy
A fragmented approach to health data management creates (a) missed opportunities to generate
improvements in health and other desirable outcomes, and (b) heightened risk of personal health data
being compromised. A recent example of a potentially preventable health data privacy breach was due to
an absence of stronger security requirements on institutions handling personal health data and resulted in
attempts to sell individuals’ COVID-19 status on the dark web (see Box 3.1).

Box 3.1. COVID-19 data breach could have been avoided by stronger governance
In February 2021 there were local and international media reports of a large breach of personal health
data from the systems of the Gemeentelijke gezondheidsdienst (GGD). The GGD is responsible for
COVID-19 testing and vaccinations. Media reports and experts interviewed by the OECD indicated that
there was a lack of safeguards including a lack of staff data access controls, gaps in the tracking of staff
data access, inadequate supervision of data protection, inadequate staff training in data protection, and
a lack of system-level data protection against the risk of data downloading.
A strong, national data governance framework, with requirements for data custodians to adopt and
maintain a privacy-by-design approach to their IT systems and with the controls and safeguards
required of data custodians that are set out in the OECD Recommendation on Health Data Governance,
may well have limited or avoided the egregious data breach (see Annex B). For example, the OECD
Recommendation in Article 12 sets out safeguards to be implemented within health data custodians
including lines of accountability, data privacy and security training for all staff members, formal risk
management processes, and technological, organisational and physical measures designed to protect
privacy and data security.
Source: Loohuis (2021[4]), “Data of Thousands of Dutch Citizens Leaked from Government COVID-19 Systems”,
https://www.computerweekly.com/news/252495983/Data-of-thousands-of-Dutch-citizens-leaked-from-government-Covid-19-systems.

Privacy-protected data uses are supported by the GDPR but need to be implemented
Implementation of the GDPR can include national legislations regarding the collection, exchange, linkage
and accessibility of health data and authorisation of data processing by a legal basis that is not limited to
patient consent. Implementation guidelines for organisations processing health data are also necessary to
avoid divergent interpretations that unnecessarily reduce data exchange and collaboration.
A recent preliminary opinion of European Data Protection Supervisor regarding the creation of a European
Health Data Space (EHDS) explains that because the space will be created to enhance access to health
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66 
data in order to allow for evidence-based policy decisions and for scientific research within the EU, they
do not consider Article 6(1)(a) GDPR (i.e. consent of the data subject), as the most appropriate legal basis
(EDPS, 2020[5]). Instead, they refer to Article 6(1)e that authorises health data processing where
processing is necessary for the performance of a task carried out in the public interest or in the exercise
of official authority vested in the controller; Article 9(2)(i) that allows processing of sensitive data for
reasons of public interest and Article 9(2)(j) that authorises processing operations involving health data
when the processing is necessary for scientific research purposes. Further, they explain that Article 89
allows member states to develop legislation that provides for derogations from certain rights, subject to
safeguards.
GDPR provisions may still provoke some limitations, however, such as the use of data for exploratory
purposes including machine learning and AI algorithm development, which require greater volumes of data
than principles of data minimisation may support (Oliveira Hashiguchi, Slawomirski and Oderkirk, 2021[6]).
Another example is the use of blockchain technologies which can violate rights set out in the GDPR, such
as the right to erasure (OECD, 2020[7]). Resolving these issues will require further work at the European
level but do not limit the Netherlands from adopting the recommendations set out in this report.
Both a national health data governance framework and guidance on the implementation of the GDPR
would help to overcome different legal interpretations that are limiting data sharing in the Netherlands. It is
therefore encouraging to hear of discussions about legislation governing secondary uses of health data
have begun. Such laws to enable secure access to personal data for research and other purposes with
public benefit have been enacted in other jurisdictions and were discussed in Chapter 2.
A further issue raised by experts in the Netherlands are legacy legislations that precede the GDPR and
that may create unnecessary obstacles to the exchange and use of health data. In particular, the Medical
Treatment Contracts Act (Wgbo) requires doctors to obtain patient consent to share data with third parties.
Third parties include quality standards/registers. Under Wgbo, patients are required to provide explicit
consent for their records to be included within the Landelijk Schakel Punt (LSP). As a result, the exchange
is missing data on non-consenting patients and for patients whose health care provider did not ask them
to provide consent. This limits the reliability of the data for direct care or secondary uses.

New framework law is a good start but will need follow-on administrative orders and
policies to achieve the desired result
A new framework law (Wegiz) introduced in 2021 aiming to improve health data interoperability takes a
cautious and incremental approach, raising concerns among experts interviewed that full health data
interoperability would not be achieved. Experts interviewed indicate that the law asks health care
professionals to set standards for treatment. The standards are then submitted to the National Quality
Register, which has a legal status. When the National Quality Register adopts the standard, it would
become a norm that the Inspectorate has the authority to uphold. The ministry would then ‘translate’ these
professional standards into technical/informational requirements.
The framework law will likely require additional follow-on administrative orders to authorise the new
standards called for by professional groups. Experts interviewed are concerned that the process could be
slow and potentially result in conflicting and incomplete sets of standards. To avoid this, follow-on
administrative orders could take a more holistic approach, broadening the conditions for agreed data
standards for all the purposes in the public interest (direct care and secondary data uses that would benefit
the public, including quality monitoring). Follow-on administrative orders must also ensure that standards
are not limited to health care data, but also include public health and social care data which are key to an
integrated health information system.
A recent letter from Minister De Jonge to parliament (15 October 2021) outlies ways in which
implementation of the Wegiz is being expedited.

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 67
Further development and implementation of information standards (technical “how”)
and quality standards (clinical “what”) is foreseen
The Framework law requires the development and implementation of information standards and
complementary quality standards. Evaluating and adopting standards is a complex undertaking. Before
recommending standards, it will be necessary to evaluate whether health care providers and organisations
could conform to new requirements and the evaluation will necessitate acquiring knowledge about the
various IT architectures and software in current use including the different structured terminology standards
and uses of free text (unstructured data). Supporting health care providers and organisations to adopt
standards will require implementation guidelines that are feasible and specific enough for IT developers to
implement within diverse architectures, terminologies, data quality standards and other variations across
the Dutch health information system landscape. Since quality registers may not have expertise in IT
architectures, software development or existing IT systems, it will be essential to support quality registers
with a consortium of partners with health informatics skills.
A useful reference for the scope of this work may be the HL7 Clinical Quality Information Work Group and
the related Da Vinci Project (see Box 3.2). These projects of HL7 require a diverse set of partners with
skills encompassing the full spectrum of the project, particularly experts in the IT architectures and software
who can prepare implementation guidelines and draft software codes for IT developers to follow so that
clinical information systems might be adapted to produce the desired data and information.

Box 3.2. HL7 Clinical Quality Information Work Group and Da Vinci Project
The Clinical Quality Information (CQI) Work Group is creating and maintain HL7 standards in support
of measuring and reporting on quality in health care including dimensions of safety, effectiveness,
patient centredness, timeliness, efficiency and equity. To do this, the Work Group collaborates with
other HL7 Work Groups with expertise in data models, content, and expressions that can affect the
measurement of quality of care. Communication is frequent with the following Work Groups: Clinical
Information Modeling Initiative (CIMI), Fast Healthcare Interoperability Resources (FHIR),
Implementable Technology Specifications (ITS), Patient Care (PC), Structured Documents (SD),
Orders and Observations (O&O) and Pharmacy (Pharm).
The HL7 Da Vinci project is working to solve data interoperability problems to enable value based care.
Da Vinci is a private sector driven initiative of US health care payers, providers and IT software vendors
that work together to define business problems, identify the corresponding data exchange requirements
and use that information to draft standards in the form of implementation guides and sample software
code.
Outputs of the Work Group and Da Vinci include standards specifications and implementation guides
that provide detailed guidance for IT developers to follow. Before such work is adopted, there is a
process to review and test new specifications and there are levels of approval within HL7 that must be
passed.
Source: HL7 (n.d.[8]), “Clinical Quality Information”, https://www.hl7.org/Special/committees/cqi/index.cfm; HL7 (n.d.[9]), “Da Vinci Project”,
https://confluence.hl7.org/display/DVP/Da+Vinci+Welcome.

A national Common Data Model would facilitate data exchange for many beneficial
purposes
In the near term, the Netherlands could standardise health data to support health care quality measurement
and information by mapping/re-coding data from the diverse array of information systems in the
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68 
Netherlands to a common data model (CDM). While this may not be feasible for health organisations with
the most customised and irregular IT systems, it may be possible for most health care providers and
organisations holding health data to have their existing data mapped/re-coded to a CDM.
Erasmus University MC leads the development of an open science federated network of data providers in
Europe called the European Health Data & Evidence Network (EHDEN) that are coding health and health
care data to the global Observational Medical Outcomes Partnership (OMOP) common data model
(EHDEN, 2021[1]). There are six data partners in this project within the Netherlands who have coded their
data to OMOP CDM including the Erasmus Integrated Primary Care Information (IPCI) database which is
based on data from primary care electronic medical records. The IPCI data is from a Netherlands’ network
of over 600 General Practitioners whose electronic medical record systems involve a variety of different
software vendors. Recently, the electronic medical records of Erasmus MC have also been coded to
OMOP CDM so the hospital could participate in international COVID-19 research.
Other data coded to OMOP CDM include the National Intensive Care Evaluation (NICE) quality registry
that is based on intensive care data extracted from electronic health records of hospitals, the Foundation
for the Provision of Information for Care and Research (STIZON) which includes data on prescription
medications data from pharmacy records and electronic patient records within hospitals and GPs; the
Netherland’s data of the European Society for Blood and Marrow Transplantation (EBMT) and the
Netherlands Integral Cancer Centre (IKNL) and data from the electronic patient records of the University
of Amsterdam MC. An expert interviewed for this study reported that the Health RI initiative in the
Netherlands is exploring the use of the OMOP CDM to facilitate clinical data analysis.
Through EHDEN’s funding, the coding of participating organisation’s data to the OMOP CDM is financially
supported up to 100K Euros per organisation. The cost of mapping data is particularly high among
organisations whose data don’t already conform to global clinical terminology standards, such as
SNOMED-CT, so the funding requirements for mapping data to the OMOP CDM in the Netherlands could
be significant.
Throughout Europe there are partners in the EHDEN federated network in 20 countries including public
sector and private sector partners. EHDEN is funded by the European Union and EFPIA and is affiliated
with the global OHDSI project and part of the same federated network. The OHDSI project and its OMOP
CDM have been implemented in 74 countries and have over 2 700 collaborating partners. While used for
a wide range of health and health care research, a recent example is the ability of this network to respond
to the COVID-19 pandemic. There are over 200 COVID-19 research papers in Google Scholar that refer
to the OMOP CDM, with dozens of citations for multi-country studies involving the Netherlands’ EHDEN
partners.
Participation in the OMOP CDM is growing within the OECD. To support COVID-19 research, the
Korean Government recently funded coding the health insurance claims records for the full population
which are held by HIRA (Health Insurance Review and Assessment Agency), as well as COVID-19 case
data from the disease control agency (KCDA) and other data to the OMOP CDM for research undertaken
through OHDSI regarding COVID-19 patient treatments and outcomes. The Korean Government is also
funding hospitals to recode their data to OMOP CDM. In France, the Health Data Hub is working to code
its data holdings on the population of France to the OMOP to support COVID-19 research. Other countries
reporting to the OECD in 2021 that they were coding electronic clinical records to the OMOP common data
model included Australia and Israel.

The Centraal Bureau voor de Statistiek (CBS) exemplifies good practice, but its remit is
limited
Interviews with experts conducted as part of this review identified the CBS as a model for the appropriate
implementation of GDPR requirements and a privacy-by-design approach to data development, linkage,

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 69
sharing and accessibility that is secure and privacy-protective. Several health care data custodians
indicated that they are sharing their data with the CBS and that they benefit from the CBS’ secure remote
data access facility when their data are shared with external researchers.
Experts from CBS have indicated that they welcome expanding their data holdings of health and health
care data and have ambitious plans for providing secure data access within the ODISSEI initiative which
includes advanced technical infrastructure and computing power for complex data analysis and software
development. Indeed, experts report that CBS is becoming the main provider of secure remote data access
services in the Netherlands for both health and social-economic data.
However, CBS experts also report that their authorising legislation makes it difficult for them to receive
health datasets from other organisations because they are, by law, required to create national statistics
from any dataset they accept. Under these arrangements, CBS cannot become a hub for secure health
data linkage and access for research purposes.
Further, CBS is not funded to provide data linkage and access to data. It employs a cost-recovery model
that experts interviewed indicate is expensive. The ODISSEI initiative, for example, has funding from
universities through scientific grants that help to offset the costs of data access for research. Health-RI is
funded through government grants (See below).

The approach to electronic health and medical records is un-co-ordinated
A well designed, longitudinal (interoperable) electronic health record (eHR) system can greatly enhance
care quality – especially co-ordination and integration – as well as supply valuable information for research,
innovation and public health. For example, an individual with multiple health problems can manage their
health much better if they have access to their own medical information, and if all their health care providers
– GPs, specialists, hospitals, emergency rooms, pharmacists, dieticians and physiotherapists – also have
access to the same information. Patient Internet Portals to their own current medical records from multiple
health care providers exist now in most OECD countries as discussed in Chapter 2.
Moreover, data can be extracted from the eHR system for quality monitoring, clinical registries and health
statistics which is common practice among many OECD countries now. The data within the eHR system
can be linked to other datasets to, for example, develop machine learning algorithms to predict the mortality
risk in sub-strata of patients thereby improving the safety and effectiveness of care in close to real-time.
Such risk stratification models are being developed in Israel and Spain.
A longitudinal eHR system does not mean a single, centralised electronic medical record (eMR). It can
equally comprise a distributed network of eMRs belonging to hospitals, specialists’ rooms, GPs and
pharmacies if the technical and operational infrastructure exists for data to be standardised and exchanged
between them, and where people can access all their own health information in one place. The lack of
eMR interoperability means that patients and the public are missing out on better care and more knowledge
to improve care co-ordination and integration, public health, and research and innovation.

The Netherlands is lagging other countries in eMR interoperability
The situation in the Netherlands is not as advanced as in many other OECD countries regarding
interoperability of medical data as was discussed in Chapter 2. While notable initiatives such as MedMij
and LSP are trying to address this, the lack of co-ordination and steering is evident.
Experts interviewed described that most health care organisations have engaged software vendors to
develop bespoke eHR platforms to specifications that suit their requirements and priorities. In most cases,
and in the absence of an overarching national data strategy and governance framework, little attention has
been paid to exchanging data. Experts described that many providers are locked into agreements with

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70 
their vendors, who either limit or charge large sums to retrofit interoperability and exchange capability into
their systems.
Stakeholder interviews suggest that patients often need to bring paper records of their health information
to different practitioners, and that general practitioners are unable to share important data such as
COVID-19 vaccination status with public health officials. Recent media reports describe patients
transferred between hospitals needing to carry a CD containing their medical information because the
hospitals’ eMRs cannot exchange data.2

Collaboration and data exchange are limited for other reasons
An integrated health information system means that all types of health care, public health and social care
data can flow to where they are needed and are fit for use upon arrival. In the context of the Dutch health
system, this means enabling secure data exchange across the numerous silos and requiring strict technical
and semantic interoperability standards.
Timely and secure data exchange opens entirely new possibilities in biomedical science as well as health
service design and delivery. For example, the capacity to link various clinical, administrative and social
datasets to study the safety and effectiveness of COVID-19 vaccines in various population sub-groups in
real time. Results can alert providers and policy makers to potential risks and opportunities, as well as
contribute to global efforts to control the pandemic. Such studies have recently been conducted in Israel
and Scotland.
In another example, New Zealand has been able to generate ‘virtual’ registries by harvesting data from a
range of sources, saving time and resources. Virtual registries and statistical databases based on data
extracted from EHR systems for national health monitoring were reported in 2021 in 12 countries (see
Chapter 2).
Despite many stakeholders’ best efforts over the past decade, experts interviewed described how strong
collaboration and smooth exchange of data are largely lacking in the Netherlands. This can be attributed
to several legal and policy barriers discussed in this section.

Rules to protect competition inhibit collaboration and data exchange
The managed competition model forms the basis of a large part of the Dutch health system. This requires,
by definition, a strong regulatory framework. However, some regulations and policies are in direct
opposition to promoting data integration. For example, to protect the functioning of the health care market,
collaboration between providers is monitored by the Netherlands Authority for consumers and markets
(acm.nl). Experts described that, under this authority, collaboration among health care providers is
generally prohibited except under certain conditions.
The tension between supporting market competition and fostering smooth, secure data exchange and,
more broadly, collaboration among providers, needs to be explicitly acknowledged and addressed.

Agreements lack requirements for data interoperability that cannot be overcome by
voluntary data exchange initiatives
Experts interviewed explained that multiple institutes are funded by the government to collect data on
aspects of health or parts of the health care system. However, funding is not contingent upon collaboration
among them and data interoperability among them is not required.

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 71
Similarly, ‘hoofdlijnakkoorden’ (outline agreements) between the government and specific sectors such as
medical specialists, include agreements on finances and quality but not on data interoperability. As a result,
sectors continue to operate in silos.
Experts also explained that standards developed by either Nictiz or MedMij are voluntary and participation
in a data exchange is voluntary.
Further, experts described that while the government provides financial incentives to physicians and
hospitals to become MedMij certified; certification does not include verification that the data within MedMiJ
are interoperable, nor verification that the user experience for patients would meet reasonable
expectations. For example, verification of how well health information is integrated and presented to the
patient is not included.

Data coverage gaps are evident
Two private data exchanges exist: LSP for exchange among providers and MedMij for exchange between
providers and patients. Experts interviewed explained that the LSP is a centralised architecture and the
MedMij is developed through open Application Programming Interfaces. A decision is needed to develop
a harmonised approach, which would allow for exchange among all stakeholders and avoid unnecessary
duplication. Both exchanges are non-binding and therefore they are incomplete, which limits their
usefulness for direct care and secondary uses and compromises patient safety.
Experts explained that under current policy, MedMij is conditional upon a patient having a PGO (personal
data environment). Patients without a PGO will be missing from MedMij. Also, patients who see providers
that are not MedMij certified will be missing part of their health records. For health care providers, MedMij
will be an incomplete information source, missing patients and providing incomplete information for
patients.
Further, experts also indicated that Personal data environments (PGO) are evolving for sub-sets of patients
rather than toward an integrated PGO that provides a complete source of information. The consequence
will be that many patients may never have a complete picture of their health and health care within a single
PGO. This problem will likely be most evident for patients with multi-morbidity or complex health and social
care needs.
The Landelijk Schakel Punt (LSP) is funded by health insurers. Costs to participate are borne by health
care providers and legislation requiring consent (see above) limits its usefulness because some patients
are inevitably missing and there are missing data for included patients.

Costs of interoperability are high and exacerbated by information blocking
The Dutch Government plans to invest in integrated care through the ‘right care at the right place’ initiative.
Integrated care requires data interoperability among health and social care providers. In addition to legal
barriers to the exchange of data that were discussed earlier, there are resource and technical constraints
to health data exchange that will limit reaching the goal of integrated care.
Experts interviewed explained that a large vendor of electronic health record system software in the
Netherlands, which provides eHR software to both hospitals and primary care offices, has an IT
architecture that limits data exchange and locks health care providers out of accessing their own data.
Experts interviewed indicate that hospitals and medical offices are unable to access their own data and
must go through the software vendor to enable data exchange or to enable views of their data (business
intelligence tools). This creates a financial disincentive for health care providers to exchange data, as they
face financial charges to do so. Further, when financial incentives may be provided by the government to
encourage data exchange, the rewards are taken up by the fees of the software provider.

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72 
Health care providers experiencing this information blocking are also limited in their ability to adopt new
devices, apps and decision-support tools that are set up for a modern IT architecture. At the same time,
the Dutch technology sector is limited from creating devices, apps and tools that could be sold in both
domestic and international markets.
The situation is likely to continue without legislation, certification and financial incentives to prevent
information blocking by software vendors and to encourage software vendors to provide modern IT
architectures that support data exchange and analytical uses of data that are in the public interest. This
can, in fact, create a level playing field for competition and the market to thrive while advancing public
policy objectives.

An updated reimbursement model would create better incentives to collaborate
The current health care remuneration model encourages more activity and service volume. In addition to
laws explicitly forbidding collaboration (see previous sections), funding based on fee-for-service further
disincentivises collaboration and integration of care across sectors and settings because the provider is
rewarded simply for their input item in the broader care cycle. Not only can this result in sub-optimal patient
experiences and health outcomes, but it is also often more expensive.
Experts interviewed explained that there are calls to change the funding model to encourage co-ordination
and value across entire cycles of care, as opposed to paying for processes and inputs. Bundled payments
for an entire care pathway from initial diagnosis to an agreed endpoint can potentially address this problem.
Several initiatives using bundled payments have emerged in the Netherlands over the past few years, but
this model is not yet the norm.
Because care integration also relies on sharing information about patients and processes, financially
rewarding joined-up care and outcomes will de facto also encourage the sharing of information about
patients’ health and their care. Funding reforms are therefore an integral part of creating an environment
where data linkage and exchange makes financial sense. The business case will strengthen if collaboration
is rewarded.
Experts interviewed also raised concern about incentives. In the absence of financial incentives for data
interoperability, the benefits of data interoperability and integration mainly accrue to government,
researchers and health insurers; while the costs of improving the interoperability of health information
systems are mainly borne by health care providers. Government leadership and legislative and policy tools
are needed to create the right environment for information exchange and collaboration.

The Netherlands risks being left behind on research and innovation
Many countries are gearing up to use data, including health data, as the fuel to power research and
innovation. The Netherlands risks being left behind in this regard unless current deficiencies in data
governance, interoperability and exchange are addressed. A recent Open Data Institute report put the
Netherlands in the ‘limited vision’ category for advancing the secondary use of health data when compared
with other EU countries (Boyd M, 2021[10]).
There are worrying signs. As a result of the various issues with data access and interoperability outlined
in the previous sections, interview subjects reported that researchers and AI developers in the Netherlands
are frequently working with patient clinical data from other countries, such as the United States and China.
Emerging EU requirements for a Health Data Space (see Chapter 2) should be seen as an opportunity to
capitalise on secure use of health data for secondary purposes.

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 73
Dutch initiatives – Health-RI & ODISSEI – and EU EHDEN exhibit the right approach
While there are many health data custodians in the Netherlands, three research infrastructures have
emerged whose aims and purpose align with those envisaged for Health Data Spaces.
Hospitals in the Netherlands have provided start-up funding to create the Health Research Infrastructure
initiative (Health-RI) which aims to “establish an interconnected data infrastructure for Dutch personalised
medicine and health research” (Dutch Tech Centre for Life Sciences, 2021[2]). Experts interviewed indicate
that Health-RI would like to access data within hospital and GP electronic health record systems for
approved research projects in real time.
Health-RI intends to use the personal health train concept to protect privacy and data security. With the
personal health train, analytics and other software code (research questions) travel to the data only
research results (answers) flow back to the researcher. This the Netherlands innovation is a new privacyenhancing technology that embodies ‘privacy-by-design’. Health-RI recently received a funding boost of
EUR 69 million from the Dutch Government National Growth Fund (Health-RI, 2021[11]). Ongoing funding
for the initiative may be considered to cement its role in the Dutch health data ecosystem.
ODISSEI (Open Data Infrastructure for Social Science and Economic Innovations) provides researchers
with access to the data holdings of the CBS, including the micro-data in-flowing to CBS from Dutch
Hospitals, GPs, health insurers and research institutes as well as health survey data and information on
the health care industry (ODISSEI, 2021[12]).
Experts interviewed explained that ODISSEI follows ‘privacy-by-design’ practices to offer secure data
linkage services and secure access to data, as well as an advanced computing and analytic capacity.
Funding for ODISSEI is through scientific grants that subsidise the costs of data linkages, infrastructure
and secure access to data enabling CBS to provide services to ODISSEI members at a lower cost.
ODISSEI’s membership includes social data research centres and, more recently, medical research
centres have joined as observers. Experts interviewed explained that medical research centres are
attracted to the model ODISSEI provides, where ODISSEI sets the research strategy and the CBS provides
data curation, linkage and secure remote data access. Further, there is interest in the research community
to bring the social sciences and the life sciences closer together because of their overlapping research
objectives and data needs.
Health research projects, particularly those in the public health domain where the influences of
environment, health behaviours and socio-economic factors are important, take place within ODISSEI. For
example, recent projects include a study examining genome-wide associations with health care costs and
an analysis of how behaviours and inequalities spread through social networks. There are, however,
important research centres and health data that are outside of ODISSEI. Experts interviewed explained,
for example, that it has not been possible to link the social networking model developed within ODISSEI
to the COVID-19 case data collected by the Rijksinstituut voor Volksgezondheid en Milieu (RIVM). If such
exchanges were more feasible, then it would be possible to leverage the investment in the social
networking model to predict how and where the pandemic may be spreading, and which population groups
are at highest risk. This information could guide public policy decisions.
ODISSEI reports a shortfall in governmental funding for national cohort surveys that follow individuals over
a long period of time. Longitudinal data from cohorts provides unique information about how the trajectory
of individuals’ health, behaviours and environments influence their future health outcomes and health care
use. Such data is not available from clinical or administrative data sources.
As the strategy for an integrated health information system is developed, it will be important to consider
how the Health RI project and the ODISSEI project can be connected with one another and with all the key
data that are needed for the Netherlands to reach its public policy goals.

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74 
The Netherlands participation in the EU EHDEN project (introduced earlier and led by Erasmus MC) is a
further exhibition of best practices. Through EHDEN, participating organisations re-code their health and
clinical data to the OMOP Common Data Model. Participating organisations are part of a federated network
with a privacy-by-design approach. The data within the network always remain in the custody of the
organisations holding them and therefore remain under the legal and policy frameworks of the data holding
organisations. Researchers can view the specifications for the common data model and may query the
data using a tool provided (ATLAS) or may submit customised statistical or software code. Researchers
cannot access or even visualise the underlying microdata held by the participating organisations and
therefore privacy and data security risks are greatly reduced which is how EHDEN and the affiliated OHDSI
project can develop multi-country health research in a timely way. A further accelerator of the timeliness
of research within the EHDEN federated network is from the open science method of sharing code through
GitHub, supporting interoperability of data analytics as well as of data. For example, standardised analytics
codes in the R statistical language for commonly used statistical methods/applications are shared and
individual researchers contribute and re-use codes.
As was discussed earlier, the OMOP CDM is a tool the Netherlands can use to overcome health data
interoperability problems in the near term. This tool would work very well within the ODISSEI and Health
RI projects, particularly to ensure that a personal health train approach could work in practice as it is
already applied for distributed analytics within the EHDEN and OHDSI federated networks.

References
Boyd M, Z. (2021), Secondary Use of Health Data in Europe, Open Data Institute,
http://theodi.org/wp-content/uploads/2021/09/Secondary-use-of-Health-Data-In-Europe-ODIRoche-Report-2021-5.pdf.

[10]

Dutch Tech Centre for Life Sciences (2021), Health-RI, https://www.dtls.nl/large-scale-researchinfrastructures/health-ri/.

[2]

EDPS (2020), Preliminary Opinion 8/2020 on the European Health Data Space.,
https://edps.europa.eu/sites/default/files/publication/20-1117_preliminary_opinion_health_data_space_en.pdf.

[5]

EHDEN (2021), European Health Data and Evidence Network, https://www.ehden.eu/.

[1]

Health-RI (2021), Dutch Government has pledged 69 million euros investment to Health-RI,
https://www.health-ri.nl/news/dutch-government-has-pledged-69-million-euros-investmenthealth-ri.

[11]

HL7 (n.d.), Clinical Quality Information, Health Level Seven International,
https://www.hl7.org/Special/committees/cqi/index.cfm.

[8]

HL7 (n.d.), Da Vinci Project, Health Level Seven International,
https://confluence.hl7.org/display/DVP/Da+Vinci+Welcome.

[9]

Loohuis, K. (2021), Data of Thousands of Dutch Citizens Leaked from Government Covid-19
Systems, https://www.computerweekly.com/news/252495983/Data-of-thousands-of-Dutchcitizens-leaked-from-government-Covid-19-systems.

[4]

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 75
Oderkirk, J. (2021), “Survey results: National health data infrastructure and governance”, OECD
Health Working Papers, No. 127, OECD Publishing, Paris, https://doi.org/10.1787/55d24b5den.

[3]

ODISSEI (2021), Open Data Infrastructure for Social Science and Economic Innovations,
https://odissei-data.nl/en/.

[12]

OECD (2020), “Opportunities and Challenges of Blockchain Technologies in Health Care”,
OECD Blockchain Policy Series, OECD, Paris, https://www.oecd.org/finance/Opportunitiesand-Challenges-of-Blockchain-Technologies-in-Health-Care.pdf.

[7]

Oliveira Hashiguchi, T., L. Slawomirski and J. Oderkirk (2021), “Laying the foundations for
artificial intelligence in health”, OECD Health Working Papers, No. 128, OECD Publishing,
Paris, https://dx.doi.org/10.1787/3f62817d-en.

[6]

Notes
1

https://eenvandaag.avrotros.nl/item/gegevens-op-de-fax-of-een-dvd-bij-verplaatsing-vancoronapatienten-wordt-gemis-van-elektronisch-patientendossier-wel-heel-duidelijk/.
2

https://eenvandaag.avrotros.nl/item/gegevens-op-de-fax-of-een-dvd-bij-verplaatsing-vancoronapatienten-wordt-gemis-van-elektronisch-patientendossier-wel-heel-duidelijk/.

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76 

4 Towards an integrated health
information system in the
Netherlands

This chapter describes the legal, policy and operational changes that are
needed in the Netherlands to establish an integrated health information
system. It sets out the requirements to take advantage of the strengths and
to address the problems uncovered in this review of the current Dutch
health information system. The recommendations include an overarching
requirement to approach health data more as a public good than as a
commodity, and to develop and implement a national digital health strategy
that strengthens mutual trust across all stakeholder groups. A range of
policy actions to implement the national digital health strategy are
recommended in this chapter, including the need for technical infrastructure
and interoperability standards, and an overarching data governance
framework that includes greater harmonisation of policies and practices to
ensure privacy and promote data security.

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 77
Many OECD countries have started harnessing their health data to work to achieve their public policy
objectives. Although the health systems are all organised and funded differently, they share some common
features: an integrated health information system based on a co-ordinated strategy that is supported by
strong leadership and a specifically designed data governance framework.
The preceding two chapters described how personal health data, as well as other data relevant to health
and well-being, are managed, exchanged, and deployed to advance policy objectives in the Netherlands
including service improvement, better public health, research outputs and innovation. Despite some
considerable strengths and advantages, the current health information landscape is too fragmented to
achieve these goals and presents a risk to the Netherlands of falling behind other countries in a range of
social and economic domains.
This chapter outlines legal, policy and operational changes to establish an integrated health information
system. It sets out the requirements to take advantage of strengths described in the previous chapter and
to address the problems uncovered in this study.
The first requirement is a mindset that sees data as a public good and a resource that can be harnessed
to advance the health and welfare of the Dutch people. This needs to be embodied in a National Strategy
that must be developed inclusively and be trusted by all stakeholders. A range of policies, regulations and
enabling legislation will be needed to implement the national strategy. Technical infrastructure and
standards will need to be implemented. An overarching governance framework will be required, including
greater harmonisation of data privacy and security policies and practices.

Steps toward an integrated HIS
The foundation of a modern, 21st century health information system that seeks to embrace the
opportunities of health data while protecting individuals’ rights to privacy is a modern, robust data
governance framework. Such a framework comprises legislation, policy and regulation on standardisation,
interoperability, and exchange; on security and privacy requirements; and on public transparency and
engagement to ensure necessary levels of trust among the public and other key stakeholders. In effect, it
is a technical, policy and political apparatus.
A cohesive, national framework is necessary in any context, but especially in countries with a fragmented
health data ecosystem such as the Netherlands. The alternative – a collection of data silos that cannot
and/or will not exchange valuable information, and where management of data security and privacy risks
is ad hoc and very variable – is not in the interest of patients, providers, industry, governments, or the
public, and will hinder the realisation of the four policy goals outlined in the introduction.

Radical health system reform is not needed
The Dutch health system has served the country very well in the 20th century. But the challenges and
opportunities of the 21st century are vastly different, and the increasing quantity of generated health data
calls for a political choice, legislative guidance and fitting strategic action in order to facilitate ethical and
optimal use of this rapidly expanding commodity. The challenge does not lie within specific actors in the
health system, but across all of them. There is a need to have a common infrastructure in order to have
health data that is fit for use and purpose for each actor’s mandate in the health system because,
fundamentally, most health system actors are reliant on data generated by others to achieve their
objectives.
Building the tracks and the signals, to create an integrated health information system that meets the
needs and opportunities of the 21st century will require a unified national strategy (preferably aligned
with a broader national digital/data strategy). It will require a new set of institutiona l function to develop,
implement and oversee a health data infrastructure and integrated information system, either through a
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78 
new national authority or by consolidating and strengthening the remit, function, and competencies of
existing agencies. Successful implementation will require good governance, policy, and trust among all
stakeholders.

A unified, national strategy is needed
A strategic plan is a common first step toward an integrated health information system. Developing a
strategy should consider the data assets and information infrastructure already in place and build forward
from them to develop the tracks and signals that are missing. Key to the development of the strategy will
be working with stakeholders to determine the objectives of the strategy and the values that the
stakeholders want to uphold.
It is essential that the strategy is sufficiently broad and deep. Breadth refers to incorporating the four
main data types: health care, public health, social care and long-term care data. Depth ensures that all
data are included, and that they can be linked at the individual level to enable better care integration as
well as more precision and scope in secondary uses.
An important accompaniment to the digital strategy are roadmaps for each strategic o bjective,
particularly those that will be challenging to achieve, such as data interoperability. The roadmaps should
be specific about who is responsible for what and when deliverables can be expected. The roadmaps
should address the full breadth and depth of the strategy to ensure a balanced and coherent
strengthening of the Dutch health information system. Hence not only enhancement of interoperability
and secondary use of data in clinical care but inclusion of data uses in public health, long term care and
social care.
Figure 4.1 presents a graphical overview of the recently published national digital strategy of
New Zealand, which includes many goal posts that would resonate in the Netherlands such as: digital
services and health information contribute to patient empowerment; health care quality and outcomes
are improved; health system performance is strengthened; and there is greater capacity for
evidence-based decision-making.
Essential elements include those that enable the strategy to be realised at a policy level, such as leg al
reforms, policy guidelines, governing and operational bodies, and financial incentives; as well as those
that enable the strategy at a technical level, such as data architecture, technical infrastructure and
terminology and interoperability standards.

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 79

Figure 4.1. New Zealand Digital Health Strategic Framework

Source: Ministry of Health, New Zealand (2020[1]), “Digital Health Strategic Framework”, https://www.health.govt.nz/our-work/digitalhealth/digital-health-strategic-framework.

A national strategy will require leadership and expertise
The Ministerie van Volksgezondheid, Welzijn en Sport (VWS) would take the lead in the development of
the national strategy. Indeed, all experts interviewed for this country review called for leadership from the
ministry to build the tracks and the signals. The ministry must be supported in developing the strategy by
experts, particularly external experts in health data informatics, data interoperability and health data
science, as well as external experts in ‘privacy-by-design’ approaches to health data governance.

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80 
Internal support will also be needed for the ministry to build a team to take the lead. The ministry could
consider creating a new unit and engaging or seconding experts in health information systems, health data
science and informatics and health data governance. This expertise will be essential to ensuring an
effective national strategy.
The MHWS should lead the development of a national strategy. In doing so, the MHWS should:

1. Build trust and support for the strategy among stakeholders and the public.


Consult with governmental agencies (Informatie Beraad, IGJ, ZIN, NZa) on needs for information,
analytics and information products.



Consult with non-government stakeholders especially patient groups, regions and municipalities,
provider organisations, health professional groups, insurers, academia, biomedical industry and
software vendors.



Develop and implement a public information campaign, public consultations and other avenues for
public input into the strategy.



Conduct public consultations at all stages of development of the national health data governance
framework and provide public information, such as a website, to disseminate information about the
development process and its outcome, as part of the National Strategy.



Launch a government campaign with communication experts to promote a dialogue with the public
about the benefits of data sharing and exchange, with the goal of valuing health data in the
Netherlands as a public good (see below).
o

This public dialogue must assuage public and stakeholder concerns about privacy risks and
reassure them by clearly communicating about how privacy will be protected when data are
used.

2. Draft the high-level IT architecture/infrastructure for an integrated health information system
that meets the information needs of key stakeholders.


Review existing architectures within and outside of the Netherlands and improved architectures
proposed in the academic literature.



Review existing data exchanges to co-ordinate, integrate and ensure the exchange meets the
needs of all stakeholders.



Review and recommend global standards for data exchange and semantic interoperability, taking
into consideration developments and requirements within the EU.



Include privacy-by-design protections, particularly federated learning (distributed analytics).



Include interoperability in analytics, information and knowledge and foster the adoption of a global
common data model (CDM).



Include lifecycle interoperability to ensure analytical uses of historical data as the information
system evolves (i.e. ensure health trajectories and longitudinal data analysis are supported).

3. Further develop and strengthen the national health data governance legislative framework to
support the national strategy. The framework must align with European regulations and should
specify the following.


The requirements for uniform data standards for health terminology, data exchange,
interoperability and a common health data model.



The requirements for the exchange, access to and use of data to serve the health-related public
interest.



The requirements for data security and privacy protection by design (‘privacy-by-design’).

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 81
4. Lead the legislative and policy reforms necessary to realise the strategy, in consultation with
other areas of government where needed.


Draft the role and mandate of the national authority responsible for the implementation,
maintenance, and oversight of the integrated health information system (see next section for
detailed functions of such an authority).



Develop policy tools and financial incentives to realise the strategy.

5. Develop the draft roadmaps for each strategic objective within the national strategy.


Ensure that the roadmaps are specific regarding who is responsible for each step and when results
can be expected.

Role of the MHWS in the implementation of the integrated health information system:


Ensure the MHWS oversees the national agency and is engaged in strategic planning and strategic
decision-making (see the next section regarding the role of the national agency).



Evaluate and publicly report on progress in the implementation of the national strategy.



Facilitate progress in policy and legal reforms to support the on-going development of the
integrated health information system in consultation with the national agency and the
Informatieberaad Zorg.



Develop and maintain analytics products and dashboards for ministerial policy making and
reporting.



Co-ordinate planning and funding of health information projects within the ministry to align them
with the strategy.



Develop campaigns and tools to improve public transparency about health information, information
governance and public benefits from improvements in health information.



Review planning and funding of health information projects within the ministry to ensure they align with
and contribute to the strategy and do not detract from or create disincentives to advance the strategy.

Key competencies to develop and implement the strategy:


Strategic planning of health information projects,



Evidence-based indicator development and policy analysis,



Informatics (IT architecture, data exchange standards, semantic interoperability),



Health data science (statistical and software development competencies, interoperability of
analytics),



Legislative frameworks,



Privacy-by-design (privacy protection, data security and related information technology
competencies), and



Public consultation and communications/public relations.

Aligning with a broader national digital strategy
Considering the general nature of developing the strategy for an integrated health information system,
incorporating it into a broader national strategy will be an advantage. In fact, most countries that are
successfully digitalising their health systems have a national digital strategy – and data governance – that
encompasses all areas of public policy including health. Estonia, for example, decided over two decades
ago to become a ‘digital society’ meaning that 99% of public services, including health care are accessible
virtually.1 This has paid not only immense dividends during the COVID-19 pandemic, enabling the country’s

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82 
health, education and welfare systems to continue to function as normal, it has also promoted technological
and policy advances in privacy and digital identity, made Estonia into Europe’s top entrepreneurial hotspot
according the World Economic Forum.2
Several Dutch experts and stakeholders interviewed emphasised their preference for need for a general
national digital or data strategy. Some mentioned the approach taken in the field of education (i.e. SURF).
Others mentioned initiatives of Municipalities and the Ministry of Internal Affairs which include social care
data. In addition to the obvious synergies, the advantages of a cross-sector approach are particularly
strong in the health arena given the value placed on privacy and security, the key role of non-health data
(which can greatly enhance knowledge-generation), and the fact that makes a country more attractive for
investment of biotech capital.

Institutional functions to develop, implement and oversee an integrated health
information system
Implementing the National Strategy and operationalising its various facets can be described as ‘building
the tracks’ of the integrated health information system. It will principally concern developing and
maintaining consistent national data standards, and then certifying and incentivising actors to implement
the strategy, including health care providers, software vendors and other developers of IT solutions. This
will require a range of functions and competencies that are currently absent, without legal mandate or
dispersed across various agencies in the Dutch health data landscape. These functions can be assigned
to existing key institutions or be taken on by a new agency.

A national agency to implement and oversee the health information system
A single agency will be needed to co-develop and implement the national strategy and oversee/maintain
the resulting health information system. This could be done by ‘strengthening’ or combining expertise of
existing organisations or creating a new agency. In either case, this agency will have the authority to
develop consistent national standards for semantics (terminology), electronic messaging (exchange), and
data accessibility/sharing. It would also be responsible for keeping the standards up to date. Consider the
roles of similar national agencies in Portugal and Estonia from Chapter 2. The national agency should also
develop the national platform for public data exchange, acting as a hub through which the data flows to
support secure access to and use of health data to serve the public interest. Consider the role of the French
Health Data Hub, the Finnish FinData, the Australian DataPlace and the EU Health Data Space discussed
in Chapter 2.
Many OECD countries have separate organisations responsible for national health data and for national
electronic health record systems (see Chapter 2). This legacy has been problematic wherever there were
no formal structures requiring the separate organisations to work closely together toward a common goal
of enabling the secure primary and secondary use of health data. Working closely together is difficult
because, for example, when tackling similar tasks, health statisticians and researchers within health data
organisations differ from health informatics experts in both working methods and even in the vocabulary
used to discuss the task. Further, the working methods and vocabularies of experts in health data privacy
and security are more closely aligned with the legal community and are different from both health
informatics and health statistics and research professionals. An integrated health information system is
therefore dependent upon the effective integration of functions and of different professional groups who
bring critical skills together to fulfil these functions.
The agency would best operate under a formal shared governance of standard setting with the existing
health research infrastructure organisations and health information organisations (such as Health RI, CBS,
ZiN, and ODDISEI), so that the standards developed will cover all data and data uses that are planned for

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 83
within the National Strategy. It would have formal links with the IC as an advisory body for development
and maintenance of technical standards.
The role of this authority would be responsible for standardisation, certification, a national public data
platform and stakeholder consultation and engagement.

1. Standardisation: Agreeing (or developing) and maintaining consistent national standards and
keeping standards for:


Semantics (terminology),



Electronic messaging (exchange),



Analytics (common data model, code sharing/analytics pipeline),



Data accessibility/sharing (prevent information blocking, secure (privacy-protective) data access,
patient portals, health data space), and



Harmonisation of data privacy and security policies and practices including national guidance for
health data processors.

2. Certification and verification of compliance with national standards


Certifying vendors of IT solutions and digital tools for compliance with national standards.



Certifying and verifying health care providers and other information system actors have achieved
interoperability standards and are exchanging useable (quality) data and are not blocking data.
This process must go beyond simply demonstrating that standards are used. Proof of data
interoperability (exchange, data quality) should also be required to achieve certification.

3. Building and maintaining a national public data platform for data exchange, acting as a hub
through which the data flows to:


Enable effective and secure processing of personal health data including data integration/linkage,



Foster adoption of a common health data model (CDM),



Manage the approval process for data integration and access requests involving data from multiple
organisations,



Enable effective and secure mechanisms for access to personal health data for approved
purposes, such as approved research,



Improve data quality, including conducing data quality auditing, and



Reduce overlapping and duplicative administrative and data processing activities among key
stakeholders within the health information system.

4. Stakeholder engagement and consultation to develop engagement in and support of the
implementation of the national strategy through:


Stakeholder and Public consultation about the national strategy and its implementation, and



Public transparency about the national strategy and the development, exchange, uses and data
privacy and security protections of health data.

Governance of the national agency
The governance of the national agency requires consideration of the role such governance will play in
effecting a change in the culture toward co-operation in health data development and exchange and in
valuing health data as a public good.
To increase the buy-in and support for the agency and its mandate to implement the national strategy, it
will be important to ensure that the national agency seeks the advice of and listens closely to the needs of
all relevant stakeholder groups, such as the groups represented within the Informatieberaad Zorg today
and health data infrastructure organisations, holders of key national health data, and health and medical

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84 
research institutes and businesses who contribute to and depend upon the health information system, such
representatives of pharmaceutical, medical device, data analytics, data applications and EHR system
businesses. A potential advisory body is an expanded Health which is discussed further below.
The formal governance of the national agency must be appropriate to the Dutch context and culture.
Consider, however, how frequently stakeholders will be engaged in advising the agency and the effort they
will expend to do so and ensure that these organisations will realise a win-win from their participation.

Key competencies of the national agency:


Strategic planning and management of health information projects,



Evidence-based indicator development and policy analysis,



Informatics (IT architecture, data exchange standards, semantic interoperability),



Data science/analytics (statistical analysis, database architecture, coding, machine learning,
distributed analytics, common data models, open science/code sharing),



Systems testing, data quality checks and software evaluation including certification,



Web and mobile applications development (websites, web portals and smartphone apps),



Privacy by design (privacy protection, data security and related information technology
competencies), and



Public consultation and communications/public relations.

Technical infrastructure and standards
A key role of the new agency will relate to the technical infrastructure needed for an integrated health
information system. Several requirements will also require attention, particularly if the system is to be
retrofitted to the existing health system.
To facilitate information development and analytics, it will be necessary in many cases to re-code existing
data to a common a data model (CDM). Leading global health data models, such as the OMOP
(Observational Medical Outcomes Partnership) CDM, should be selected for this purpose and the technical
capacity instituted.
Similarly, modern IT architecture and global standards for data terminology and exchange (messaging)
should be deployed. For the Netherlands to participate in multi-country research and monitoring, the
standards must comply with current and emerging European regulations. It will also be an advantage if the
Netherlands participates in global and European efforts to develop global standards for health data
terminology and exchange.
These functions can be performed by the agency responsible for operationalising the national strategy, in
close liaison with the IC and Ministry. However, the need for expertise in IT architecture, informatics and
data science is again emphasised.

The Informatieberaad Zorg as an advisory body to the national agency
A potential advisory body for developing and implementing the national strategy is already in place, the
Informatieberaad Zorg. This body currently lacks a formal mandate and is missing participation from key
organisations with responsibility for national health information and who contribute to and depend upon
the health information system. Furthermore, its focus is presently on primary use of clinical data hence the
needed broadening (to other sectors like public health, long term care and social care) and secondary data
use needs to be reflected in either the composition of the IC or another mechanism of representation of
stakeholders to assure an integrated health information system for the health system as a whole. Ensuring

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 85
the IC includes representatives from key stakeholders in all aspects of an integrated health information
system is highly recommended to make the most informed decisions about the strategy.
The Informatieberaad Zorg could become a forum of reflection and advice to the government and to the
national agency. Specifically, its role would principally concern:


Advising on the development and implementation of the national strategy for an integrated health
information system, and



Acting as ambassadors and spokespersons for the national strategy.

Membership of the Informatieberaad Zorg
Representatives within all key stakeholders in an integrated health information system, including
organisations participating in the existing IC and new members representing organisations with
responsibility for national health information (including health care, public health, social care and long-term
care data); national health care quality registries; national health research infrastructures; organisations
providing national health data access, linkage and governance; and businesses who contribute to and
depend upon the health information system, such representatives of pharmaceutical, medical device, data
analytics, data applications and EHR system businesses.
Members of the Informatieberaad Zorg should have executive or decision-making power within their
respective organisations to provide strategic advice to the national agency on matters that may impact
upon their organisations.

Implementation will hinge on governance, policy as well as trust
Key governance and policy reforms constitute ‘the signals’ that enable data to flow along the newly built
tracks. These reforms will be executed by the ministry, with advice of the IC and the implementation
capability of the national agency, and will primarily comprise developing new legislation, guidelines,
governance, and funding mechanisms.

A legislative framework
Legal authority will be needed to authorise and finance the National Strategy and its implementation. This
can be follow-on administrative orders to the new framework legislation for data exchange via care quality
standards. They will complement the framework legislation and ensure depth and breadth (i.e. incorporate
public health data and social care data and facilitate use of data for secondary purposes). The new
administrative orders should require compliance with standards that ensure data interoperability and
prevent data blocking by data custodians and software vendors.
Revisions may be needed to legacy legislations that are posing unnecessary obstacles to an integrated
health information system, such as revisions to the Medical Treatment Contracts Act (Wgbo) to allow for
lawful alternatives to consent for data exchange and uses in the public interest; to legislation authorising
the Central Bureau of Statistics to allow it to act as a central hub for access to health datasets; and to
regulations related to consumers and markets that prevent health care collaborations and data integration.

Building trust
The national strategy will steer the Netherlands away from the current situation of data silos toward an
integrated system where secure data exchange is the norm. The strategy should modernise data
development, exchange, management, and governance and it will require a change management
approach that builds trust (See Box 4.1).

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86 

Box 4.1. Building Trust
Building trust among stakeholders and the public is an important aspect of health data governance and
an effective data infrastructure. A lack of trust will undermine efforts to exchange data for primary and
secondary purposes. First and foremost, trust is achieved through actions not words. Rhetoric must be
matched by visible acts and changes to the status quo. It is a challenging process. While trust is
established over a long time (years not months), it can be lost very quickly.
Any campaign to establish trust (and it should be approached as a campaign) should be based on
transparency and inclusion. All stakeholders need to be part of developing and designing the change –
in this case the strategy – from the beginning. Consultation on the finished product, developed by
experts, will not achieve this. An iterative consultation process on the national strategy comprising 2 to
3 steps may take longer but will ensure people trust the finished product because inter alia they will
have a sense of ownership and are invested in its success.
Transparency is key for establishing trust and for maintaining it. Key decisions, challenges, problems
and resolutions should be communicated, and lines of accountability made clear. Successful countries
have created public websites where people can access information about the strategy and everything
concerning health data, its use, how it is managed and secured, how privacy is protected as well as the
outputs of various programmes and projects that use personal health data.
Using health data to serve the public interest should be framed as an opportunity, not a risk. The long
list of benefits should be explained in detail, using real-world examples. Every stakeholder group should
be made aware how the changes will benefit them. For example: patients stand to receive modern
health services, higher quality care and access to better, safe treatments; providers will have better
data and information to improve practice and deliver high quality care; public health officials will have
timely and complete information about infectious disease outbreaks, real-time data on vaccine safety
and effectiveness, granular data to guide policies for managing NCDs; payers stand to access more
detailed information on health care activity, costs and outcomes; policy makers will be better able to
assess how the system performs and regulate it more intelligently; industry will have a tremendous
resource to spur invention and technology; and society will benefit from an innovative and agile health
sector that not only delivers the best possible outcomes but attracts investment and contributes to
economic growth.
This way, the conversation can shift to a more complete view where NOT using data is a risk health
and prosperity, and the discussion becomes how this can be done safely and securely. It is therefore
crucial to be upfront about privacy, how it is secured, and how problems or failures are resolved. In fact,
transparency is critically important when things don’t go to plan. Nothing destroys trust faster than bad
news being hidden. Equally, timely and clear communication about how past problems have been
resolved can have a reassuring effect.
Finally, public education and PR campaigns need to be intelligently planned and rolled out. Engagement
of professional expertise from advertising and communications are advised. Prominent ‘champions’ and
thought-leaders from various walks of life should be co-opted to be part of the campaign promote the
strategy. Alongside health and data science experts, it can be helpful to employ public figures (actors,
musicians, footballers) to communicate the message. Getting the PR campaign wrong can have
consequences. In 2014, the United Kingdom mailed out paper pamphlets to inform the public about
health data governance under the care.data project. The campaign failed to get the public’s attention
and when public concerns about care.data arose later on they included the reaction that public
consultation and communication about care.data were inadequate.
Source: OECD (2015[2]), Health Data Governance: Privacy, Monitoring and Research, https://dx.doi.org/10.1787/9789264244566-en.

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 87
The key will be to allocate sufficient time and resources to consultation with stakeholder bodies and the
public at all points in the development of the strategy, so that progress from a draft strategy to a final
strategy to roadmaps and implementation will feel natural, expected and safe.
Another key will be to have the right input in terms of technical, IT, policy, and legal expertise to develop a
worthwhile and trustworthy strategy. Stakeholders will then be more at ease and comfortable to share their
needs, their constraints, and their hopes for the strategy.
Members of the advisory body to the strategy, as well as the core strategy team, will be ambassadors and
spokespersons for the strategy and should be encouraged to discuss the strategy widely with their
communities and with the media to reach the public. For example, we understand from experts we
interviewed that having leading Dutch experts speak to the media about the trustworthiness of the
COVID-19 monitoring app alleviated the public’s concerns about data privacy. The process of developing
the strategy and roadmaps will result in a more complete and well-considered plan than can be developed
through this OECD country review.

A firm hand will be needed to address resistance
From the outset it must be foreshadowed that an integrated health information system – as envisaged here
– will be opposed and resisted by stakeholders who benefit from the current arrangements. For example,
a firm hand will be needed with EHR system software vendors whose business model and products are
out of alignment with global standards for clinical terminology and data exchange, and who do not support
data interoperability within or across health care organisations.
These stakeholders may pressure the government to favour their local IT solutions, but unless compliant
with international terminologies and electronic messaging standards, these solutions will not help the Dutch
health technology sector to compete globally; will not allow local health care providers to adopt
solutions/tools from the global marketplace; and will make progress toward the national strategy expensive,
slow and probably impossible.

Regulation and guidelines
National policies will be needed to fulfil regulatory requirements that enable access to data for those who
need them, while also keeping data secure and maintaining individuals’ rights to privacy. These will guide:


Implementing one national interpretation of the GDPR by all actors in the health information
system,



Emphasising privacy-by-design,



Adhering to FAIR principles, and



Developing reasonable approaches or lawful alternatives to consent.

It is critical that these national policies align with existing and developing guidance and regulations at the
European level.
As part of this reform, the functionality and capacity of the two data exchanges (LSP and MedMij) should
be harmonised to meet the needs of all stakeholders, including those currently using MedMij and LSP, and
to realise the goals of the national strategy. The exchange of data should ensure full coverage of patients
and providers and that patient records are complete. The exchange should be legally authorised, follow a
‘privacy-by-design’ approach and meet international standards for data security.

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88 
Complementary funding and incentives
To complement laws and policies, financial incentives will be needed to encourage compliance with
national GDPR guidelines, with national data standards, and for demonstrating (verifiable) data
interoperability.
This will require a review of government funding and subsidies of activities related to the exchange and
use of health data, including research projects funded by government grants. It may also require explicit
financial incentives to encourage health care providers and other actors to move to certified IT solutions
and succeed in achieving verifiable interoperability.
The ministry and IC should consider how broader reforms to health care funding and remuneration that
reward care co-ordination and value will affect the functioning of an integrated health information system.

References
Ministry of Health, New Zealand (2020), Digital Health Strategic Framework,
https://www.health.govt.nz/our-work/digital-health/digital-health-strategic-framework.

[1]

OECD (2015), Health Data Governance: Privacy, Monitoring and Research, OECD Health Policy
Studies, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264244566-en.

[2]

Notes
1

https://e-estonia.com/.

2

https://www.weforum.org/agenda/2020/07/estonia-advanced-digital-society-here-s-how-that-helped-itduring-covid-19/.

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 89

Annex A. Consultation with experts

The recommendations presented in this report were supported by a series of interviews and focus group
discussions conducted by the OECD team with experts in the Netherlands from February to April 2021.
Initial interview subjects were identified by the Ministry of Health and Welfare. These interview subjects
recommended other experts for the OECD to consult. The OECD continued interviews until the information
gathered from key informants began to share similar messages. Further rounds of interviews and focus
groups took place from June to October 2021, gathering experts’ reflections on proposed
recommendations and expanding our understanding of the data landscape and recent innovations in the
Netherlands.
The OECD thanks and appreciates the contributions of the following experts whose insights, experiences
and aspirations informed the development of these recommendations.

Table A A.1. Experts interviewed about the health information system in the Netherlands
Name

Position

Organisation

Caroline A. Baan
Frank Berens
Adriaan Blankenstein

Science Officer
Policy Advisor
Chief Executive Officer

Hidde Boonstra
Teresa Cardosa
Herko Coomans
Dirk Deelstra
Tom Emery

Senior Policy Advisor
Digital Health Policy Co-ordinator
Senior Policy Advisor
Deputy Director

Leone Flikweert
Emi van Galen
Jeroen Geelhoed
Ronald Gijsen
Ivo LWJ Gorissen
Jan Hazelzet
Marcel Heldoorn
Peter Jansen
Anil Jadoenathmisier

Chief Executive Officer
Adviser
Senior Manager
Researcher
Account Manager
Professor in Healthcare Quality and Outcomes
Manager, Digital Healthcare
Information Manager
Director, IT and Innovation

Sander Klous
Johan van Manen
Frits van Merode
Misja Mikkers
Lokke Moerel
Isabel Moll
Annemiek Mulder
Yola Park
Ron Rozendaal
Charlotte de Schepper

Partner, Big Data Analytics
Adviser
Researcher, Fac. Health, Medicine and Life Sciences
Chief Economist
Professor of Global ICT Law
Partner, Digital Trust Data (Healthcare)
Senior Policy Advisor
Adviser, Information Policy
Director, Information Policy and CIO
Representative

Ministry of Health, Welfare and Sport
V&VN
VZVZ (Association of care providers for care
communication)
VNG
ZiN Zorginstituut Nederland
Ministry of Health, Welfare and Sport
ZiN Zorginstituut Nederland
Open Data Infrastructure for Social Science and Economic
Innovations (ODISSEI)
Health Research Infrastructure (Health RI)
NZa
BeBright Consulting
Rijksinstituut voor Volksgezondheid en Milieu (RIVM)
Central Bureau of Statistics (CBS)
Erasmus University Medical Centre
Netherlands Patient Federation
ZN (Organisation of health insurers)
Vereniging van Zorgaanbieders voor Zorgcommunicatie
VZVZ
KPMG
NZa
Maastricht University
NZa
Tilburg University
KPMG
ACTIZ (Organisation of LTC/home care providers)
Ministry of Health, Welfare and Sport
Ministry of Health, Welfare and Sport
KNOV (Organisation of midwives)

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90 
Name

Position

Organisation

Gert-Jan van Boven
Lies van Gennip
J.A.M. van Oers
(Hans)
Vincent Van Polanen
Petel
Peter Rjinbeek

Chief Executive Officer
Director
Professor of Public Health

Dutch Hospital Data
Stichting PALGA (Pathology Registry)
Tilburg University

Head, Health and Social Care Statistics

Central Bureau of Statistics (CBS)

Deputy Head, Department of Medical Informatics and
EU EHDEN Co-ordinator
Chief Executive Officer

Erasmus MC

Maarten van Rixtel
Tino de Velde
Inez Young

Chief Data Officer

Sensor (Organisation of LTC/home care providers)
VNG
Rijksinstituut voor Volksgezondheid en Milieu (RIVM)

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 91

Annex B. OECD Recommendation on Health Data
Governance

The work of the OECD to support strengthening health data infrastructure and governance and to protect
privacy and data security culminated in the OECD Recommendation on Health Data Governance
[OECD/LEGAL/0433], which provides guidance for building national governance frameworks that enable
personal health data to be both protected and used towards public policy goals.
The Recommendation applies to the access to, and the processing of, personal health data for healthrelated public interest purposes, such as improving health care quality, safety and responsiveness;
reducing public health risks; discovering and evaluating new diagnostic tools and treatments to improve
health outcomes; managing health care resources efficiently; contributing to the progress of science and
medicine; improving public policy planning and evaluation; and improving patients’ participation in and
experiences of health care.
The Recommendation recommends that Adherents establish and implement a national health data
governance framework to encourage the availability and use of personal health data to serve health-related
public interest purposes while promoting the protection of privacy, personal health data and data security.
National health data governance frameworks should provide for:


Engagement and participation of stakeholders in the development of a national health data
governance framework;



Co-ordination within government and co-operation among organisations processing personal
health data to encourage common data-related policies and standards;



Reviews of the capacity of public sector health data systems to serve and protect public interests;



Clear provision of information to individuals about the processing of their personal health data
including notification of any significant data breach or misuse;



The processing of personal health data by informed consent and appropriate alternatives;



The implementation of review and approval procedures to process personal health data for
research and other health-related public interest purposes;



Transparency through public information about the purposes for processing of personal health data
and approval criteria;



Maximising the development and use of technology for data processing and data protection;



Mechanisms to monitor and evaluate the impact of the national health data governance framework,
including health data availability, policies and practices to manage privacy, protection of personal
health data and digital security risks;



Training and skills development of personal health data processors;



Implementation of controls and safeguards within organisations processing personal health data
including technological, physical and organisational measures designed to protect privacy and
digital security; and



Requiring that organisations processing personal health data demonstrate that they meet the
expectations set out in the national health data governance framework.

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92 
These 12 principles set the parameters to encourage greater cross-country harmonisation of data
governance frameworks so that more countries can use health data for research, statistics and health care
quality improvement.
The Recommendation also recommends that Adherents support trans-border co-operation in the
processing of health data for purposes that serve the public interest. It further recommends that Adherents
engage with relevant experts and organisations to develop mechanisms that enable the efficient exchange
and interoperability of health data.
Finally, it encourages non-governmental organisations to follow the Recommendation when processing
personal health data for health-related purposes that serve the public interest and invites non-Adherents
to take account and to adhere to the Recommendation.

TOWARDS AN INTEGRATED HEALTH INFORMATION SYSTEM IN THE NETHERLANDS © OECD 2022

Towards an Integrated Health Information System
in the Netherlands
Twenty‑first century health systems have to be built around data and information. An integrated health
information system enables the secure flow of data to where they can be used, to provide information
to strengthen integrated care delivery, enable public health monitoring and management, and foster medical
and health research and innovation. This report describes the requirements and the benefits of an integrated
health information system; outlines the current situation in the Netherlands in the context of progress across
OECD countries; and recommends legal, policy and operational changes to overcome barriers to the efficient
exchange and sharing of health data and to establish an integrated health information system.

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