Unlocking Health Data for Research: Legal, Technical, and Organisational Lessons from a Belgian Interdisciplinary Case Study

The reuse of clinical health data holds immense promise for advancing medical research, yet remains constrained by complex legal, technical, and organisational barriers. This article examines these challenges through the case study of TumorScope, a Belgian interdisciplinary initiative developing a secure, multimodal data environment for glioblastoma research. Drawing on five years of practical experience integrating imaging, genetic, tissue-based, and clinical datasets, the study identifies key legal, ethical, technical, and operational obstacles to effective data access, linkage, and reuse. Technical issues included fragmented data flows, pseudonymisation complexities, and limited interoperability, while legal and ethical barriers arose from strict interpretations of the General Data Protection Regulation, medical secrecy obligations, and intellectual property constraints. These were compounded by operational challenges such as unclear governance structures, resource limitations, and the limited capacity of Medical Research Ethics Committees to assess data-driven research. The analysis further considers the European Health Data Space Regulation (EHDS) as a potential enabler of responsible secondary data use, while noting uncertainties in its national implementation. Overall, the study demonstrates that meaningful health data reuse requires more than regulatory compliance, it depends on robust governance frameworks, institutional coordination, and sustained investment in infrastructure and expertise. The findings contribute to ongoing debates in healthcare informatics on how to translate the vision of the EHDS into practical, ethically grounded data reuse for patient benefit.

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Publication Details

Journal
Journal of Healthcare Informatics Research
Published
2025-10-23
DOI
https://doi.org/10.1007/s41666-025-00220-w
Primary Topic
Machine Learning in Healthcare
Type
article
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article

Unlocking Health Data for Research: Legal, Technical, and Organisational Lessons from a Belgian Interdisciplinary Case Study

Pieter Cornu, Paul Quinn, Johnny Duerinck, Konstantina Tzavella et al.
Journal of Healthcare Informatics Research
Machine Learning in Healthcare
article

Unlocking Health Data for Research: Legal, Technical, and Organisational Lessons from a Belgian Interdisciplinary Case Study

Pieter Cornu, Paul Quinn, Johnny Duerinck, Konstantina Tzavella, Wim Vranken, Ramses Forsyth, S. De Sutter, Catharina Olsen, Audrey Van Scharen, Sonia Van Dooren, Wim Waelput, Jef Vandemeulebroucke, Arne Witdouck, Karen Cruyt, Jeroen Colon
article en

Abstract

The reuse of clinical health data holds immense promise for advancing medical research, yet remains constrained by complex legal, technical, and organisational barriers. This article examines these challenges through the case study of TumorScope, a Belgian interdisciplinary initiative developing a secure, multimodal data environment for glioblastoma research. Drawing on five years of practical experience integrating imaging, genetic, tissue-based, and clinical datasets, the study identifies key legal, ethical, technical, and operational obstacles to effective data access, linkage, and reuse. Technical issues included fragmented data flows, pseudonymisation complexities, and limited interoperability, while legal and ethical barriers arose from strict interpretations of the General Data Protection Regulation, medical secrecy obligations, and intellectual property constraints. These were compounded by operational challenges such as unclear governance structures, resource limitations, and the limited capacity of Medical Research Ethics Committees to assess data-driven research. The analysis further considers the European Health Data Space Regulation (EHDS) as a potential enabler of responsible secondary data use, while noting uncertainties in its national implementation. Overall, the study demonstrates that meaningful health data reuse requires more than regulatory compliance, it depends on robust governance frameworks, institutional coordination, and sustained investment in infrastructure and expertise. The findings contribute to ongoing debates in healthcare informatics on how to translate the vision of the EHDS into practical, ethically grounded data reuse for patient benefit.

Journal of Healthcare Informatics ResearchVol. 10(1)
Université Libre de Bruxelles (BE), Vrije Universiteit Brussel (BE), Imec the Netherlands (NL), Universitair Ziekenhuis Brussel (BE)
Openalex Percentile: Top 84%
Machine Learning in Healthcare
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