Integration of real-world heterogeneous data sources for public health research within and across jurisdictional borders
(2025)
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- Abstract
- Real-world data, routinely collected in vast amounts, are revolutionizing public health research and advancing evidence-informed public health policy. In a complex landscape where data are distributed across isolated data sources and jurisdictional borders, researchers face growing expectations to deliver timely, accurate, and actionable evidence on public health concerns. To successfully conduct observational public health research, they need to find their way through legislations, take into consideration ethical and legal concerns related to privacy and data security, tackle interoperability challenges, and effectively address biases. This thesis demonstrates the integration of heterogenous data sources for policy-relevant observational public health research in Belgium and Europe. It generates valuable real-world evidence, but also highlights potential biases and uncovers challenges for future research. A methodological framework is proposed, offering researchers a systematic approach to develop federated cross-border (causal) observational studies using distributed personal data in a privacy-preserving and interoperable way. Subsequently, experts’ experiences and perceptions towards the integration of heterogenous data sources for public health research are mapped. The outcomes of this thesis contribute to advancing observational public health research within and across jurisdictional borders and identify areas for future action.
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Citations
Meurisse, M. (2025). Integration of real-world heterogeneous data sources for public health research within and across jurisdictional borders.