Landscape of Data Sources for Real-World Observational Studies: Focus on the French Context

Author(s)

Aurélie Schmidt, MSc, Doris Barnier-Ripet, MSc, Diane-Charlotte Baillet, MSc, Helene Denis, PharmD.
HEVA, Lyon, France.
OBJECTIVES: To provide a comprehensive overview of data sources and associated regulatory frameworks available for researchers, study sponsors and regulators in order to investigate the use, safety and effectiveness of therapeutic innovations in France.
METHODS: A structured literature review was conducted to identify existing data sources relevant for real-world observational studies. Both local and international initiatives were examined to ensure the completeness of the review. Giving the large number of data sources, we refined the scope of work to France.
RESULTS: The review identified four main categories of data sources. (1) Primary data collection include tailored datasets such as prospective cohorts, clinical registries and population-based health surveys. (2) Reimbursement databases include medico-administrative databases, as well as data related to medical biology and radiology. (3) Patients records, which can be extracted through chart reviews conducted by clinical research associates (CRAs) or through direct access to health data warehouses. (4) Finally, environmental and socio-economic data, publicly available on national websites or collected through sensors, can be linked to previous data sources using geographic identifiers to enrich analyses. Regulatory requirements vary according to the type of data source but systematically involve obtaining authorization from the data owner and approval from ethics committee.
CONCLUSIONS: This work provides practical guidance for researchers in selecting the most suitable data sources for real world studies and outlines the key regulatory processes.

Conference/Value in Health Info

2025-11, ISPOR Europe 2025, Glasgow, Scotland

Value in Health, Volume 28, Issue S2

Code

RWD112

Topic

Methodological & Statistical Research, Patient-Centered Research, Real World Data & Information Systems

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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