TY - JOUR
T1 - Rethinking Trust in Synthetic Health Data
T2 - Lessons From 7 European Research Initiatives
AU - Declerck, Jens
AU - Kalra, Dipak
AU - Airola, Antti
AU - Ali Amer, Ahmed Youssef
AU - Chatzichristos, Christos
AU - Mañu Pereira, Maria del Mar
AU - de Brito Robalo, Bruno M.
AU - Ghini, Francesco
AU - Gutierrez-Torre, Alberto
AU - Hoogteijling, Sem
AU - Hultsch, Susanne
AU - Ramon, Jan
AU - Reidel, Sara
AU - Regazzoni, Francesco
AU - Silva, Luís
AU - Silveira, Inês
AU - Sofia, Tsekeridou
AU - Maes, Christophe
N1 - Publisher Copyright:
©Jens Declerck, Dipak Kalra, Antti Airola, Ahmed Youssef Ali Amer, Christos Chatzichristos, Maria del Mar Mañu Pereira, Bruno M. de Brito Robalo, Francesco Ghini, Alberto Gutierrez-Torre, Sem Hoogteijling, Susanne Hultsch, Jan Ramon, Sara Reidel, Francesco Regazzoni, Luís Silva, Inês Silveira, Tsekeridou Sofia, Christophe Maes.
PY - 2026
Y1 - 2026
N2 - Synthetic data generation (SDG) structured health data is increasingly promoted as a solution to longstanding barriers in health data access. It is offering the promise of privacy-preserving data reuse for research, innovation, and policy. Despite rapid technical advances, the adoption of synthetic health data in real-world settings remains limited. Shaped by challenges around data quality, representativeness, infrastructure readiness, trust, and legal uncertainty, this viewpoint draws on experiences from 7 European research initiatives within the HealthData4EU cluster to reflect on how SDG is being operationalized in practice. It synthesizes cross-project insights to highlight recurring methodological and governance tensions and to examine their implications for trust and responsible use. The analysis argues that trustworthy SDG cannot be achieved through technical optimization alone but requires alignment between evaluation practices, upstream data stewardship, regulatory clarity, and sustained stakeholder engagement. Addressing these conditions is essential for moving synthetic data from experimental pilots toward a credible and sustainable component of European health research ecosystems.
AB - Synthetic data generation (SDG) structured health data is increasingly promoted as a solution to longstanding barriers in health data access. It is offering the promise of privacy-preserving data reuse for research, innovation, and policy. Despite rapid technical advances, the adoption of synthetic health data in real-world settings remains limited. Shaped by challenges around data quality, representativeness, infrastructure readiness, trust, and legal uncertainty, this viewpoint draws on experiences from 7 European research initiatives within the HealthData4EU cluster to reflect on how SDG is being operationalized in practice. It synthesizes cross-project insights to highlight recurring methodological and governance tensions and to examine their implications for trust and responsible use. The analysis argues that trustworthy SDG cannot be achieved through technical optimization alone but requires alignment between evaluation practices, upstream data stewardship, regulatory clarity, and sustained stakeholder engagement. Addressing these conditions is essential for moving synthetic data from experimental pilots toward a credible and sustainable component of European health research ecosystems.
KW - data quality dimensions
KW - health data
KW - health data quality
KW - privacy
KW - project
KW - synthetic data generation
UR - https://www.scopus.com/pages/publications/105037450359
U2 - 10.2196/83369
DO - 10.2196/83369
M3 - Article
C2 - 42054696
AN - SCOPUS:105037450359
SN - 1439-4456
VL - 28
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
M1 - e83369
ER -