title: A new approach to identify, classify and count drug-related events.
abstract: OBJECTIVE
  The incidence of clinical events related to medication errors and/or adverse drug reactions reported in the literature varies by a degree that cannot solely be explained by the clinical setting, the varying scrutiny of investigators or varying definitions of drug-related events. Our hypothesis was that the individual complexity of many clinical cases may pose relevant limitations for current definitions and algorithms used to identify, classify and count adverse drug-related events.
  
  
  METHODS
  Based on clinical cases derived from an observational study we identified and classified common clinical problems that cannot be adequately characterized by the currently used definitions and algorithms.
  
  
  RESULTS
  It appears that some key models currently used to describe the relation of medication errors (MEs), adverse drug reactions (ADRs) and adverse drug events (ADEs) can easily be misinterpreted or contain logical inconsistencies that limit their accurate use to all but the simplest clinical cases. A key limitation of current models is the inability to deal with complex interactions such as one drug causing two clinically distinct side effects or multiple drugs contributing to a single clinical event. Using a large set of clinical cases we developed a revised model of the interdependence between MEs, ADEs and ADRs and extended current event definitions when multiple medications cause multiple types of problems. We propose algorithms that may help to improve the identification, classification and counting of drug-related events.
  
  
  CONCLUSIONS
  The new model may help to overcome some of the limitations that complex clinical cases pose to current paper- or software-based drug therapy safety.
authors.affiliation: Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. thomas.buerkle@imi.med.uni-erlangen.de
authors.forename: Thomas
authors.initials: T
authors.lastname: Bürkle
authors.forename: Fabian
authors.initials: F
authors.lastname: Müller
authors.forename: Andrius
authors.initials: A
authors.lastname: Patapovas
authors.forename: Anja
authors.initials: A
authors.lastname: Sonst
authors.forename: Barbara
authors.initials: B
authors.lastname: Pfistermeister
authors.forename: Bettina
authors.initials: B
authors.lastname: Plank-Kiegele
authors.forename: Harald
authors.initials: H
authors.lastname: Dormann
authors.forename: Renke
authors.initials: R
authors.lastname: Maas
mesh_terms: D000465:Algorithms; D064420:Drug-Related Side Effects and Adverse Reactions / Q000145:classification / Q000453:epidemiology*; D006801:Humans; D008508:Medication Errors / Q000145:classification / Q000706:statistics & numerical data*
keywords: adverse drug event; adverse drug reaction; medication error; medication pathway; medication safety