=Paper=
{{Paper
|id=Vol-3415/paper-14
|storemode=property
|title=Surveyed common data access policies preferences amongst European Reference Networks
|pdfUrl=https://ceur-ws.org/Vol-3415/paper-14.pdf
|volume=Vol-3415
|dblpUrl=https://dblp.org/rec/conf/swat4ls/BallesterosBBCC23
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==Surveyed common data access policies preferences amongst European Reference Networks==
https://ceur-ws.org/Vol-3415/paper-14.pdf
Surveyed common data access policies preferences
amongst European Reference Networks
Alberto Cámara1,∗ , Nirupama Benis2,3 , César H. Bernabé4 , Inés D.O. Coelho5 ,
Clémence M. A. Le Cornec6 , Aylin Demir7 , Bruna D.S. Vieira5,8 , Jose A. Ramírez6 ,
K. Joeri van der Velde9 , Shuxin Zhang2,3 , Ronald Cornet2,3 , Annika Jacobsen4 ,
Marco Roos4 , Franz Schaefer6 , Morris A. Swertz9 and Mark D. Wilkinson1
1
Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de
Biosistemas, Centro de Biotecnología y Genómica de Plantas. Universidad Politécnica de Madrid (UPM) - Instituto
Nacional de Investigación y Tecnología Agraria y Alimentaria-CSIC (INIA-CSIC). Campus Montegancedo 28223 Pozuelo
de Alarcón (Madrid), Spain.
2
Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Meibergdreef 9, Amsterdam,
The Netherlands.
3
Amsterdam Public Health, Digital Health Methodology, Amsterdam, The Netherlands.
4
Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
5
Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands.
6
Division of Paediatric Nephrology, Center for Paediatrics and Adolescent Medicine, University of Heidelberg, Heidelberg,
Germany.
7
Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main,
Germany.
8
Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
9
Genomics Coordination Center, University of Groningen and University Medical Center, Groningen, The Netherlands.
Abstract
Background: Data sharing amongst existing Rare Disease (RD) registries, even though being a process
that presents multiple barriers, would enrich and ease research, as well as facilitate interoperability
between the registries themselves. Methods: To understand their preferences on sharing data, we
surveyed 24 European Reference Networks (ERNs) from the RD Domain. Results: The answers show
that most ERNs are willing to share a set of Common Data Elements for free with authenticated users
at an aggregated or pseudonymized level the moment the data is collected. The one exception is the
industry sector, to which ERNs prefer to ask for a fee. Objective: Our aim is to create a reference for
how most RD registries are willing to share their data, improving the ability of other stakeholders to
make informed decisions to make their data interoperable.
Keywords
Rare diseases, patient registries, FAIR data sharing
14th International SWAT4HCLS Conference, February 13–16, 2023, Basel, Switzerland
*Corresponding author.
Envelope-Open alberto.camara-ballesteros@ejprd-project.eu (A. Cámara)
Orcid 0000-0001-5613-9704 (A. Cámara); 0000-0002-2101-6154 (N. Benis); 0000-0003-1795-5930 (C. H. Bernabé);
0000-0002-0756-2722 (I. D.O. Coelho); 0000-0001-7893-0505 (B. D.S. Vieira); 0000-0003-0942-4371 (J. A. Ramírez);
0000-0002-0934-8375 (K. J. v. d. Velde); 0000-0003-4715-9070 (S. Zhang); 0000-0002-1704-5980 (R. Cornet);
0000-0003-4818-2360 (A. Jacobsen); 0000-0002-8691-772X (M. Roos); 0000-0001-7564-9937 (F. Schaefer);
0000-0002-0979-3401 (M. A. Swertz); 0000-0001-6960-357X (M. D. Wilkinson)
© 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
1. Introduction
Amongst the clinical domains, the Rare Disease (RD) domain is one of the most convoluted re-
garding data sharing. This is the result of numerous factors, such as the intrinsic low prevalence
of RDs that causes data to be siloed, scarce, and heterogeneous (as it ranges from documents
updated by patients or their caretakers to clinical registries operated by data stewards and
managing institutions). Another relevant aspect of RD data is that it usually is highly distributed
[1], as specialised institutions usually focus on one RD or a group of RDs. Perhaps the most
crucial limitation is that the data from the RD domain is personally identifiable by nature (as a
consequence of the small number of people affected by these diseases) [2]. These circumstances,
together with general problems related to information sharing, such as the absence of a common
standardised vocabulary to describe it, cause great impediments to research activities [3].
To alleviate some of these issues, the Joint Research Centre1 composed a set of Common
Data Elements (CDEs) [4] that are considered essential for further research on RDs. This set of
CDEs collects information that is prevalent for all European Registry Networks (ERNs), such as
diagnosis, sex, status, phenotype, etc. The CDEs are modeled by the European Joint Programme
on Rare Diseases (EJP-RD)2 as the CDE Semantic Model, which recommends a collection of
widespread ontologies that serve as a common group of terminologies to represent knowledge.
By implementing the CDE Semantic Model, ERNs can increase their data sharing capabilities
amongst themselves and with external resources. With the help of EJP-RD, most registries are
undergoing a FAIRification process and implementation of the CDEs, which are crucial steps
towards improving interoperability and data sharing within the RD community. [5] shows the
procedure for applying the CDE Semantic Model to a registry of vascular anomalies, which
entails the use of standardised terms from widespread ontologies, applying a transformation
layer from whatever kind of data existed in the registry to a Resource Description Framework
(RDF), as a way to make the data machine-interpretable and provide semantics amongst other
steps. The EJP RD is currently working on the Virtual Platform (VP), a place where ERNs
and other RD-related resources can connect to become discoverable (requiring the creation
and collection of a Data Catalog Vocabulary (DCAT)-based minimal set of metadata about the
registry and its contents, which is being designed by the experts at the EJP-RD) and share their
data. The objective of this paper is to inventorize the ERNs’ preferences when sharing their
data, such as exactly what data to share, how to share it, whom to give access to it, and its time
of publication.
2. Methods and results
All 24 ERNs were invited to complete a survey in which they describe which stakeholder is al-
lowed for which level of data sharing. Nine types of stakeholders were considered: Contributing
researcher (CR), Non-contributing researcher (NCR), Industry (IND), National Health Authority
(NHA), Regulatory authority (RA), Health technology Assessment/Payors (HTA), European
Health Data Space (EHDS). Patient Organisation (PO), and Non-Governmental Organization
1
https://joint-research-centre.ec.europa.eu/index_en
2
https://www.ejprarediseases.org/
(NGO). Five aspects of data sharing are considered: Data to be shared (1), Highest data level to
be shared (2), Access modalities(3), Timing (4), and Need for Data Access Committee (DAC) (5).
The options presented for each aspect, as well as the results from the survey can be found on
their respective tables.
Table 1
Data to be shared. *CDEs plus selected disease history/intervention/outcome data.
Stakeholder None CDEs CDEs + extras* All available data
CR 0.0% 21.4% 28.6% 50.0%
NCR 0.0% 21.4% 35.7% 42.9%
IND 0.0% 45.5% 45.5% 9.1%
NHA 0.0% 63.6% 27.3% 9.1%
RA 0.0% 54.5% 36.4% 9.1%
HTA 0.0% 60.0% 30.0% 10.0%
EHDS 0.0% 60.0% 30.0% 10.0%
PO 0.0% 41.7% 33.3% 25.0%
NGO 0.0% 44.4% 44.4% 11.2%
Average 0.0% 45.8% 38.9% 19.6%
To help with visualisation, the responses were plotted, they can be found here [6]. You can
find the original responses from the ERNs that agreed to share them here [7].
3. Discussion
The results from the survey indicate that the paramount priority for ERNs is to protect their
patient’s privacy, as they all want to share their data, but in a controlled and safe manner. That
is why no ERN answered that they did not want to share any of their data, and most of them are
willing to give access to the CDEs by themselves (45.8% on average) or with some extras (38.9%
on average) to all stakeholders. Most ERNs want to share data that is pseudonymised (37.0% on
average) or aggregated (42.1% on average), as it allows for research to be done without risking
the privacy of their patients. The majority of ERNs want to share their data for free (42.8%
on average), but a considerable amount of them require the user to be authenticated (42.5%
on average). Regarding the data sharing timing, the overwhelming majority are willing to
share it immediately upon collection (72.2% on average), probably because that way it becomes
available for research as soon as possible, and almost all registries require stakeholders trying
to access their data need to submit a request to their DAC - the next point of the survey. This
is no surprise, as that way they can carefully examine exactly who accesses their data, what
data they share and exactly when to share it. Two stakeholders seem to be polar opposites
in the ERNs perspective: researchers and industry. For researchers, ERNs want to share all
their data at pseudonymised patient level (57.1%), and for free (some of them with (50.0%) and
some of them without authentication (42.9%)). These answers further support the point that the
RD community is willing to assist researchers as much as possible while protecting patients’
privacy. This might be the cause for the trend towards industry, one of the stakeholders with
Table 2
Highest data level to be shared
Stakeholder None Yes/No Counts Aggregated data Anonymised data Pseudonimised data
CR 0.0% 0.0% 7.1% 28.6% 7.1% 57.1%
NCR 0.0% 0.0% 7.1% 35.7% 21.4% 35.7%
IND 0.0% 0.0% 7.1% 57.1% 7.1% 28.6%
NHA 0.0% 0.0% 8.3% 41.7% 8.3% 41.7%
RA 0.0% 0.0% 16.7% 25.0% 25.0% 33.3%
HTA 0.0% 0.0% 16.7% 41.7% 8.3% 33.3%
EHDS 0.0% 0.0% 8.3% 33.3% 16.7% 41.7%
PO 0.0% 0.0% 14.3% 57.1% 0% 28.6%
NGO 0.0% 0.0% 8.3% 58.3% 0% 33.3%
Average 0.0% 0.0% 10.4% 42.1% 10.4% 37.0%
Table 3
Access modalities
Stakeholder Free Fees Authenticated Authenticated and fees
CR 42.9% 0.0% 50.0% 7.1%
NCR 42.9% 0.0% 57.1% 0.0%
IND 23.1% 15.4% 7.7% 53.8%
NHA 50.0% 0.0% 41.7% 8.3%
RA 41.7% 0.0% 50.0% 8.3%
HTA 50.0% 8.3% 33.3% 8.3%
EHDS 41.7% 0.0% 58.3% 0.0%
PO 42.9% 0% 42.9% 14.3%
NGO 50.0% 0% 41.7% 8.3%
Average 42.8% 2.6% 42.5% 12.0%
which ERNs have the lowest percentage of willingness to share all available data (9.3%), the
highest willingness to share aggregated data (57.1%), and the highest willingness to have access
with both authentication and fees (53.8%). Remarkably, researchers seem to favor data sharing
with the industry over other stakeholders like patient organisations, which might suggest that
researchers are faced with maintaining balance between protecting their patients and finding in
the industry a source for funding that increases the sustainability of the registry itself.
Acknowledgments
This work was supported by the European Joint Programme on Rare Diseases, ERICA and
the following Europen Reference Networks: BOND, ERKNeT, Endo-ERN, ERNICA, EURA-
CAN, eUROGEN, EURONMD, GUARD-Heart, LUNG, MetabERN, PaedCan, RARE-LIVER, RITA,
VASCERN.
Table 4
Timing
Stakeholder Never Immediately after collection X years after collection Only published data
CR 0.0% 91.7% 8.3% 0.0%
NCR 0.0% 54.5% 45.5% 0.0%
IND 0.0% 80.0% 10.0% 10.0%
NHA 0.0% 70.0% 30.0% 0.0%
RA 0.0% 80.0% 20.0% 0.0%
HTA 0.0% 66.7% 22.2% 11.1%
EHDS 0.0% 77.8% 22.2% 0.0%
PO 0.0% 54.5% 45.5% 0.0%
NGO 0.0% 75.0% 25.0% 0.0%
Average 0.0% 72.2% 25.4% 2.3%
Table 5
Need for DAC
Stakeholder Yes No
CR 100.0% 0.0%
NCR 100.0% 0.0%
IND 100.0% 0.0%
NHA 75.0% 25.0%
RA 100.0% 0.0%
HTA 75.0% 25.0%
EHDS 100.0% 0.0%
PO 75.0% 25.0%
NGO 75.0% 25.0%
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