French administrative health care database (SNDS): The value of its enrichment.

SNIIRAM/SNDS, the French administrative health care database, covers around 99% of the population. Its main limitation is the absence of clinical information and biological results. This report exposes the value of SNIIRAM/SNDS enrichment by external databases, and the linkage issues. It is illustrated by examples: the well-known population-based cohort CONSTANCES created to answer to epidemiological research questions with a specific interest on occupational and social factors, chronic diseases, and aging; the CANARI study, a regional-based study that collected Gleason score in all pathology laboratories in Brittany and then, linked pathology results to an ad hoc extraction from SNIIRAM database; the goal was to investigate the risk of high grade prostate cancer in patients treated by 5-alpha-reductase inhibitors for a symptomatic benign prostatic hyperplasia; the SACHA study, that identified and medically validated major bleeding event referred to emergency wards, then linked those clinical data to SNIIRAM; the goal was to minimize misclassification bias when estimating bleeding risk in patients who were prescribed antithrombotic drugs; the ISO-PSY study linked the SNIIRAM with the national cause of death registry (CépiDc) and the nationwide emergency department surveillance system (OSCOUR network) to investigate the potential link between isotretinoin and suicidal risk; the EFEMERIS cohort that assesses drugs prescriptions in French pregnant women who delivered in the Haute-Garonne region; the EPI-GETB-AM study that derived a SNIIRAM/SNDS-based algorithm to identify venous thromboembolism and linked SNIIRAM/SNDS to the EPI-GETBO-III survey for validation. Another perspective of SNDS enrichment is clinical trials' data for medico-economic assessment, and extended follow-up without attrition bias. Linkage is not straightforward. Apart from regulatory approbation and authorized data center issues, which could be solved by the Health Data Hub Initiative, a multidisciplinary team with medical, pharmacological and methodological knowledge, as well as with technical skills is essential to handle the whole process.