Literature DB >> 28544284

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

Julien Bezin1,2, Mai Duong2,3, Régis Lassalle3, Cécile Droz3, Antoine Pariente1,2, Patrick Blin3, Nicholas Moore1,2,3.   

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.
Copyright © 2017 John Wiley & Sons, Ltd.

Entities:  

Keywords:  claims database; pharmacoepidemiology; population studies

Mesh:

Year:  2017        PMID: 28544284     DOI: 10.1002/pds.4233

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  94 in total

1.  Identifying diabetes cases in health administrative databases: a validation study based on a large French cohort.

Authors:  Sonsoles Fuentes; Emmanuel Cosson; Laurence Mandereau-Bruno; Anne Fagot-Campagna; Pascale Bernillon; Marcel Goldberg; Sandrine Fosse-Edorh
Journal:  Int J Public Health       Date:  2018-12-04       Impact factor: 3.380

2.  Analysis of the association between emergency dialysis start in patients with end-stage kidney disease and non-steroidal anti-inflammatory drugs, proton-pump inhibitors, and iodinated contrast agents.

Authors:  Aurélie Pétureau; Maxime Raffray; Elisabeth Polard; Cécile Couchoud; Cécile Vigneau; Sahar Bayat
Journal:  J Nephrol       Date:  2021-04-20       Impact factor: 3.902

3.  Coronary Events After Dispensing of Ibuprofen: A Propensity Score-Matched Cohort Study Versus Paracetamol in the French Nationwide Claims Database Sample.

Authors:  Mai Duong; Abdelilah Abouelfath; Regis Lassalle; Cécile Droz; Patrick Blin; Nicholas Moore
Journal:  Drug Saf       Date:  2018-11       Impact factor: 5.606

4.  Risks of 23 specific malformations associated with prenatal exposure to 10 antiepileptic drugs.

Authors:  Pierre-Olivier Blotière; Fanny Raguideau; Alain Weill; Elisabeth Elefant; Isabelle Perthus; Véronique Goulet; Florence Rouget; Mahmoud Zureik; Joël Coste; Rosemary Dray-Spira
Journal:  Neurology       Date:  2019-06-12       Impact factor: 9.910

5.  An Automated System Combining Safety Signal Detection and Prioritization from Healthcare Databases: A Pilot Study.

Authors:  Mickael Arnaud; Bernard Bégaud; Frantz Thiessard; Quentin Jarrion; Julien Bezin; Antoine Pariente; Francesco Salvo
Journal:  Drug Saf       Date:  2018-04       Impact factor: 5.606

6.  Effectiveness and safety of 110 or 150 mg dabigatran vs. vitamin K antagonists in nonvalvular atrial fibrillation.

Authors:  Patrick Blin; Caroline Dureau-Pournin; Yves Cottin; Jacques Bénichou; Patrick Mismetti; Abdelilah Abouelfath; Regis Lassalle; Cécile Droz; Nicholas Moore
Journal:  Br J Clin Pharmacol       Date:  2018-12-16       Impact factor: 4.335

7.  Work-Related Stressors and Increased Risk of Benzodiazepine Long-Term Use: Findings From the CONSTANCES Population-Based Cohort.

Authors:  Guillaume Airagnes; Cédric Lemogne; Romain Olekhnovitch; Yves Roquelaure; Nicolas Hoertel; Marcel Goldberg; Frédéric Limosin; Marie Zins
Journal:  Am J Public Health       Date:  2018-11-29       Impact factor: 9.308

8.  POMME: The New Cohort to Evaluate Long-Term Effects After Prenatal Medicine Exposure.

Authors:  Justine Benevent; Caroline Hurault-Delarue; Mélanie Araujo; Jean-Louis Montastruc; Isabelle Lacroix; Christine Damase-Michel
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

9.  Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.

Authors:  Chungsoo Kim; Seng Chan You; Jenna M Reps; Jae Youn Cheong; Rae Woong Park
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

10.  Risk assessment of using off-label morphine sulfate in a population-based retrospective cohort of opioid-dependent patients.

Authors:  Célian Bertin; Jessica Delorme; Marie Riquelme; Hélène Peyrière; Georges Brousse; Alain Eschalier; Denis Ardid; Chouki Chenaf; Nicolas Authier
Journal:  Br J Clin Pharmacol       Date:  2019-08-24       Impact factor: 4.335

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