title: Replication of the OMOP experiment in Europe: evaluating methods for risk identification in electronic health record databases.
abstract: BACKGROUND
  The Observational Medical Outcomes Partnership (OMOP) has just completed a large scale empirical evaluation of statistical methods and analysis choices for risks identification in longitudinal observational healthcare data. This experiment drew data from four large US health insurance claims databases and one US electronic health record (EHR) database, but it is unclear to what extend the findings of this study apply to other data sources.
  
  
  OBJECTIVE
  To replicate the OMOP experiment in six European EHR databases.
  
  
  METHODS
  Six databases of the EU-ADR (Exploring and Understanding Adverse Drug Reactions) database network participated in this study: Aarhus (Denmark), ARS (Italy), HealthSearch (Italy), IPCI (the Netherlands), Pedianet (Italy), and Pharmo (the Netherlands). All methods in the OMOP experiment were applied to a collection of 165 positive and 234 negative control drug-outcome pairs across four outcomes: acute liver injury, acute myocardial infarction, acute kidney injury, and upper gastrointestinal bleeding. Area under the receiver operator characteristics curve (AUC) was computed per database and for a combination of all six databases using meta-analysis for random effects. We provide expected values of estimation error as well, based on negative controls.
  
  
  RESULTS
  Similarly to the US experiment, high predictive accuracy was found (AUC >0.8) for some analyses. Self-controlled designs, such as self-controlled case series, IC temporal pattern discovery and self-controlled cohort achieved higher performance than other methods, both in terms of predictive accuracy and observed bias.
  
  
  CONCLUSIONS
  The major findings of the recent OMOP experiment were also observed in the European databases.
authors.affiliation: Department of Medical Informatics, Erasmus University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands, m.schuemie@erasmusmc.nl.
authors.forename: Martijn J
authors.initials: MJ
authors.lastname: Schuemie
authors.forename: Rosa
authors.initials: R
authors.lastname: Gini
authors.forename: Preciosa M
authors.initials: PM
authors.lastname: Coloma
authors.forename: Huub
authors.initials: H
authors.lastname: Straatman
authors.forename: Ron M C
authors.initials: RM
authors.lastname: Herings
authors.forename: Lars
authors.initials: L
authors.lastname: Pedersen
authors.forename: Francesco
authors.initials: F
authors.lastname: Innocenti
authors.forename: Giampiero
authors.initials: G
authors.lastname: Mazzaglia
authors.forename: Gino
authors.initials: G
authors.lastname: Picelli
authors.forename: Johan
authors.initials: J
authors.lastname: van der Lei
authors.forename: Miriam C J M
authors.initials: MC
authors.lastname: Sturkenboom
mesh_terms: D019540:Area Under Curve; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis*; D057286:Electronic Health Records; D005060:Europe; D006801:Humans; D012107:Research Design; D018570:Risk Assessment / Q000379:methods*