A rapid review on the application of common data models in healthcare: Recommendations for data governance and federated learning in artificial intelligence development - UTU Research Portal

A2 Refereed review article in a scientific journal

A rapid review on the application of common data models in healthcare: Recommendations for data governance and federated learning in artificial intelligence development

Authors: von Gerich, Hanna; Chomutare, Taridzo; Kytö, Ville; Lundberg, Peter; Siggaard, Troels; Peltonen, Laura-Maria

Publisher: SAGE Publications

Publication year: 2025

Journal:Digital health

Article number: 20552076251395536

Volume: 11

eISSN: 2055-2076

DOI: https://doi.org/10.1177/20552076251395536

Web address : https://doi.org/10.1177/20552076251395536

Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/505395228

Abstract

Objective

This rapid review was undertaken to summarize contemporary knowledge on the application of common data models (CDMs) for semantic data standardization in the field of healthcare and provide a set of recommendations to guide the development of a CDM.

Methods

The review adapted the Cochrane methodological recommendations for rapid reviews, namely (1) topic refinement, (2) setting eligibility criteria, (3) searching, (4) study selection, (5) data extraction, and (6) synthesis.

Results

A total of 69 studies were included in the analysis. The analysis resulted in three interconnected layers covering (1) the federated network, (2) the iterative application process of a CDM, and (3) the data management process of each partner.

Conclusion

Development and implementation of CDMs is a collaborative and iterative process, highly affected by the boundaries set by the individual federated learning partners, and the nature of their data. Interdisciplinary collaboration in application of CDMs for federated learning and data governance of health data is mandatory, with a call to increase domain expert involvement in data management.

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Funding information in the publication:
Nordic Innovation. Vinnova & MedTech4Health, Sweden (PL) and National Board of Health and Welfare, Sweden (PL)