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Federated electronic health records for the European Health Data Space.
Raab, René; Küderle, Arne; Zakreuskaya, Anastasiya; Stern, Ariel D; Klucken, Jochen; Kaissis, Georgios; Rueckert, Daniel; Boll, Susanne; Eils, Roland; Wagener, Harald; Eskofier, Bjoern M.
Afiliação
  • Raab R; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Küderle A; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Zakreuskaya A; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Stern AD; Harvard Business School and Harvard-MIT Center for Regulatory Science, Boston, MA, USA.
  • Klucken J; Chair of Digital Medicine, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Digital Medicine Group, Luxembourg Institute of Health, Strassen, Luxembourg; Centre Hospitalier de Luxembourg, Luxembourg, Luxembourg.
  • Kaissis G; Klinikum Rechts der Isar, Technical University of Munich, Institute for Artificial Intelligence and Informatics in Medicine, Munich, Germany; Helmholtz Munich, Institute for Machine Learning in Biomedical Imaging, Neuherberg, Germany; Department of Computing, Imperial College London, London, UK.
  • Rueckert D; Klinikum Rechts der Isar, Technical University of Munich, Institute for Artificial Intelligence and Informatics in Medicine, Munich, Germany; Department of Computing, Imperial College London, London, UK.
  • Boll S; OFFIS-Institut für Informatik, Oldenburg, Germany.
  • Eils R; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Digital Health Center, Berlin, Germany.
  • Wagener H; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Digital Health Center, Berlin, Germany.
  • Eskofier BM; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. Electronic address: bjoern.eskofier@fau.de.
Lancet Digit Health ; 5(11): e840-e847, 2023 11.
Article em En | MEDLINE | ID: mdl-37741765
ABSTRACT
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Médicos / Registros Eletrônicos de Saúde Limite: Humans Idioma: En Revista: Lancet Digit Health Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Médicos / Registros Eletrônicos de Saúde Limite: Humans Idioma: En Revista: Lancet Digit Health Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha