title: Estimation of severe drug-drug interaction warnings by medical specialist groups for Austrian nationwide eMedication.
abstract: OBJECTIVE
  The objective of this study is to estimate the amount of severe drug-drug interaction warnings per medical specialist group triggered by prescribed drugs of a patient before and after the introduction of a nationwide eMedication system in Austria planned for 2015.
  
  
  METHODS
  The estimations of interaction warnings are based on patients' prescriptions of a single health care professional per patient, as well as all patients' prescriptions from all visited health care professionals. We used a research database of the Main Association of Austrian Social Security Organizations that contains health claims data of the years 2006 and 2007.
  
  
  RESULTS
  The study cohort consists of about 1 million patients, with 26.4 million prescribed drugs from about 3,400 different health care professionals. The estimation of interaction warnings show a heterogeneous pattern of severe drug-drug-interaction warnings across medical specialist groups.
  
  
  CONCLUSIONS
  During an eMedication implementation it must be taken into consideration that different medical specialist groups require customized support.
authors.affiliation: Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna, Austria.
authors.forename: C
authors.initials: C
authors.lastname: Rinner
authors.affiliation: Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna, Austria.
authors.forename: S K
authors.initials: SK
authors.lastname: Sauter
authors.affiliation: Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna, Austria.
authors.forename: L M
authors.initials: LM
authors.lastname: Neuhofer
authors.affiliation: Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna, Austria.
authors.forename: D
authors.initials: D
authors.lastname: Edlinger
authors.affiliation: Research Group Scientific Computing, University of Vienna , Vienna, Austria.
authors.forename: W
authors.initials: W
authors.lastname: Grossmann
authors.affiliation: Department of Clinical Pharmacology, Medical University of Vienna , Vienna, Austria.
authors.forename: M
authors.initials: M
authors.lastname: Wolzt
authors.affiliation: Main Association of Austrian Social Security Organizations , Vienna, Austria.
authors.forename: G
authors.initials: G
authors.lastname: Endel
authors.affiliation: Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna, Austria.
authors.forename: W
authors.initials: W
authors.lastname: Gall
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D001317:Austria / Q000453:epidemiology; D016303:Clinical Pharmacy Information Systems / Q000706:statistics & numerical data*; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D055695:Electronic Prescribing / Q000706:statistics & numerical data*; D006801:Humans; D050316:Medical Order Entry Systems / Q000706:statistics & numerical data*; D008511:Medicine / Q000706:statistics & numerical data*; D015995:Prevalence
keywords: Drug interactions; medical informatics; public health informatics