C Rinner1, S K Sauter1, L M Neuhofer1, D Edlinger1, W Grossmann2, M Wolzt3, G Endel4, W Gall1. 1. Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna , Vienna, Austria. 2. Research Group Scientific Computing, University of Vienna , Vienna, Austria. 3. Department of Clinical Pharmacology, Medical University of Vienna , Vienna, Austria. 4. Main Association of Austrian Social Security Organizations , Vienna, Austria.
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. CONCLUSION: During an eMedication implementation it must be taken into consideration that different medical specialist groups require customized support.
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. CONCLUSION: During an eMedication implementation it must be taken into consideration that different medical specialist groups require customized support.
Entities:
Keywords:
Drug interactions; medical informatics; public health informatics
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