title: [Benefits of large healthcare databases for drug risk research].
abstract: Large electronic healthcare databases have become an important worldwide data resource for drug safety research after approval. Signal generation methods and drug safety studies based on these data facilitate the prospective monitoring of drug safety after approval, as has been recently required by EU law and the German Medicines Act. Despite its large size, a single healthcare database may include insufficient patients for the study of a very small number of drug-exposed patients or the investigation of very rare drug risks. For that reason, in the United States, efforts have been made to work on models that provide the linkage of data from different electronic healthcare databases for monitoring the safety of medicines after authorization in (i) the Sentinel Initiative and (ii) the Observational Medical Outcomes Partnership (OMOP). In July 2014, the pilot project Mini-Sentinel included a total of 178 million people from 18 different US databases. The merging of the data is based on a distributed data network with a common data model. In the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCEPP) there has been no comparable merging of data from different databases; however, first experiences have been gained in various EU drug safety projects. In Germany, the data of the statutory health insurance providers constitute the most important resource for establishing a large healthcare database. Their use for this purpose has so far been severely restricted by the Code of Social Law (Section 75, Book 10). Therefore, a reform of this section is absolutely necessary.
authors.affiliation: Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Achterstraße 30, 28359, Bremen, Deutschland. garbe@uni-bremen.de.|Wissenschaftsschwerpunkt "Gesundheitswissenschaften", Universität Bremen, Bremen, Deutschland. garbe@uni-bremen.de.
authors.forename: Edeltraut
authors.initials: E
authors.lastname: Garbe
authors.affiliation: Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Achterstraße 30, 28359, Bremen, Deutschland.|Institut für Statistik, Fachbereich Mathematik und Informatik, Universität Bremen, Bremen, Deutschland.
authors.forename: Iris
authors.initials: I
authors.lastname: Pigeot
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration*; D057225:Data Mining / Q000379:methods; D066264:Datasets as Topic / Q000706:statistics & numerical data*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005858:Germany / Q000453:epidemiology; D006302:Health Services Research / Q000379:methods; D006801:Humans; D008498:Medical Record Linkage / Q000379:methods; D000071220:Pharmaceutical Research / Q000379:methods*; D060735:Pharmacovigilance; D011159:Population Surveillance / Q000379:methods; D015995:Prevalence; D012307:Risk Factors; D014481:United States / Q000453:epidemiology