ArticleDigital health
Lessons from federated networks for implementing the European health data space. Empirical study.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
Objectives: To explore first-hand expert perspectives on the development and use of federated repositories for health data sharing, with a focus on their role in secondary use of health data and the European Health Data Space framework. Methods: A qualitative study was conducted using semi-structured interviews with 19 experts directly involved in developing federated health data repositories. Interview findings were thematically analysed to identify perceived benefits, limitations, and suitable use contexts for federated data-sharing models. Results: Federated networks were perceived as effective in contexts where they can support new opportunities for research data sharing, engage new data providers, and address trust-related barriers. However, participants also identified important limitations. These included high resource demands, complex governance requirements, privacy risks, and reduced suitability for certain types of research. Conclusion: Federated repositories may offer valuable governance and technical solutions for health data sharing, especially where trust and provider engagement are central concerns. Their benefits are context-dependent, and they are not suitable for all research scenarios. The findings contribute to debates on data governance for secondary use and the future role of federated infrastructures under the European Health Data Space.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.