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Pharmacoepidemiol Drug Saf. 2017 Aug;26(8):954-962. doi: 10.1002/pds.4233. Epub 2017 May 24.

The national healthcare system claims databases in France, SNIIRAM and EGB: Powerful tools for pharmacoepidemiology.

Author information

1
Department of Medical Pharmacology, CHU de Bordeaux, Université de Bordeaux, 33076, Bordeaux, France.
2
INSERM U1219, 33076, Bordeaux, France.
3
Bordeaux PharmacoEpi, INSERM CIC1401, 33076, Bordeaux, France.

Abstract

The French health care system is based on universal coverage by one of several health care insurance plans. The SNIIRAM database merges anonymous information of reimbursed claims from all these plans, linked to the national hospital-discharge summaries database system (PMSI) and the national death registry. It now covers 98.8% of the French population, over 66 million persons, from birth (or immigration) to death (or emigration), making it possibly the world's largest continuous homogeneous claims database. The database includes demographic data; health care encounters such as physician or paramedical visits, medicines, medical devices, and lab tests (without results); chronic medical conditions (ICD10 codes); hospitalisations with ICD10 codes for primary, linked and associated diagnoses, date and duration, procedures, diagnostic-related groups, and cost coding; date but currently not cause of death. The power of the database is correlatively great, and its representativeness is near perfect, since it essentially includes the whole country's population. The main difficulty in using the database, beyond its sheer size and complexity, is the administrative process necessary to access it. Recent legislative advances are making this easier. EGB (Echantillon Généraliste de Bénéficiaires) is the 1/97th random permanent representative sample of SNIIRAM, with planned 20-year longitudinal data (10 years at this time). Access time is 1 to 3 months, but its power is less (780 000 subjects). This is enough to study common issues with older drugs but may be limited for new products or rare events.

KEYWORDS:

claims database; pharmacoepidemiology; population studies

PMID:
28544284
DOI:
10.1002/pds.4233
[Indexed for MEDLINE]

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