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Raab, R.* ; Küderle, A.* ; Zakreuskaya, A.* ; Stern, A.D.* ; Klucken, J.* ; Kaissis, G. ; Rueckert, D.* ; Boll, S.* ; Eils, R.* ; Wagener, H.* ; Eskofier, B.M.*

Federated electronic health records for the European Health Data Space.

Lancet Digit. Health 5, e840-e847 (2023)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The European Commission's draft for the European Health Data Space (EHDS) aims to empower citizens to access their personal health data and share it with physicians and other health-care providers. It further defines procedures for the secondary use of electronic health data for research and development. Although this planned legislation is undoubtedly a step in the right direction, implementation approaches could potentially result in centralised data silos that pose data privacy and security risks for individuals. To address this concern, we propose federated personal health data spaces, a novel architecture for storing, managing, and sharing personal electronic health records that puts citizens at the centre—both conceptually and technologically. The proposed architecture puts citizens in control by storing personal health data on a combination of personal devices rather than in centralised data silos. We describe how this federated architecture fits within the EHDS and can enable the same features as centralised systems while protecting the privacy of citizens. We further argue that increased privacy and control do not contradict the use of electronic health data for research and development. Instead, data sovereignty and transparency encourage active participation in studies and data sharing. This combination of privacy-by-design and transparent, privacy-preserving data sharing can enable health-care leaders to break the privacy-exploitation barrier, which currently limits the secondary use of health data in many cases.
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Publication type Article: Journal article
Document type Review
Language english
Publication Year 2023
HGF-reported in Year 2023
ISSN (print) / ISBN 2589-7500
e-ISSN 2589-7500
Journal The Lancet Digital Health
Quellenangaben Volume: 5, Issue: 11, Pages: e840-e847 Article Number: , Supplement: ,
Publisher Elsevier
Publishing Place Radarweg 29, 1043 Nx Amsterdam, Netherlands
Reviewing status Peer reviewed
Institute(s) Institute for Machine Learning in Biomed Imaging (IML)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-507100-001
Grants
European Federation of Pharmaceutical Industries and Associations (EFPIA)
European Union's Horizon 2020 research and innovation programme
Mobilise-D project - Innovative Medicines Initiative (IMI) 2 Joint Undertaking
German Research Foundation
Federal Ministry for Economic Affairs and Climate Action of Germany
Private Artificial Intelligence in Medicine (PrivateAIM) projects
Bavarian State Ministry for Science and the Arts through the Munich Centre for Machine Learning
German Federal Ministry of Education and Research
Luxembourg Research Foundation
Federal Ministry for Economic Affairs and Climate Action
DOI 10.1016/S2589-7500(23)00156-5
WOS ID 001148114500001
Scopus ID 85172451679
PubMed ID 37741765
Erfassungsdatum 2023-10-18
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