Health Data Set Bias Examination in the European Health Data Space

Journal Article (2026)
Author(s)

Evangelia Anna Markatou (HL7 Europe, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Catherine Chronaki (HL7 Europe)

Research Group
Cyber Security
DOI related publication
https://doi.org/10.3233/SHTI260527 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Cyber Security
Journal title
Studies in health technology and informatics
Volume number
336
Pages (from-to)
1761-1765
Downloads counter
5
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Abstract

Diversity in health datasets is a necessary, quantifiable property of inclusivity across key domains (e.g., demographic, socioeconomic, health, and environmental) that directly shapes how well research generalizes and how fair its impacts are. In its absence, interventions risk encoding bias and exacerbating health disparities. In this work, we outline how dataset diversity can be measured and how these measures can be surfaced in the EHDS via metadata. We argue that simple annotations are insufficient: structured interaction with the data owner is required to assess the utility of health datasets for specific research purposes.