Andreas D Meid1, Dirk Heider2, Jürgen-Bernhard Adler3, Renate Quinzler1, Herrmann Brenner4,5, Christian Günster3, Hans-Helmut König2, Walter E Haefeli1. 1. Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany. 2. Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 3. Wissenschaftliches Institut der AOK (WIdO), Berlin, Germany. 4. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany. 5. Network Aging Research, University of Heidelberg, Heidelberg, Germany.
Abstract
PURPOSE: The purpose of this study was to compare the predictive accuracy of different methods suggested for approximation of drug prescription durations in claims data. METHODS: We expanded a well-established modeling and simulation framework to compare approximated drug prescription durations with 'true' (i.e., simulated) durations. Real claims data of persons aged ≥65 years insured by the German nationwide 'Statutory Health Insurance Fund' AOK between 2010 and 2012 provided empiric input parameters that were completed with missing information on actual dosing patterns from an observational cohort. The distinct approximation methods were based on crude measures (one tablet a day), population-averaged measures (defined daily doses), or individually-derived measures (longitudinal coverage approximation of the applied dose, COV). As a proof-of-principle, we assessed the methods' performance to predict the well-characterized bleeding risks of anticoagulant, antiplatelet, and/or non-steroidal anti-inflammatory drugs. RESULTS: When applied to modeling and simulation data sets, the closest, least biased, and thus most accurate approximation was observed using the COV approximation. In a real-data example, rather similar results to an external reference were obtained for all methods. However, some of the differences between methods were meaningful, and the most reasonable and consistent results were obtained with the COV approach. CONCLUSION: Based on theoretically most accurate approximations and practically reasonable estimates, the individual COV approach was preferable over the population-averaged defined daily dose technique, although the latter might be justified in certain situations. Advantages of the COV approach are expected to be even bigger for drug therapies with particularly large dosing heterogeneity.
PURPOSE: The purpose of this study was to compare the predictive accuracy of different methods suggested for approximation of drug prescription durations in claims data. METHODS: We expanded a well-established modeling and simulation framework to compare approximated drug prescription durations with 'true' (i.e., simulated) durations. Real claims data of persons aged ≥65 years insured by the German nationwide 'Statutory Health Insurance Fund' AOK between 2010 and 2012 provided empiric input parameters that were completed with missing information on actual dosing patterns from an observational cohort. The distinct approximation methods were based on crude measures (one tablet a day), population-averaged measures (defined daily doses), or individually-derived measures (longitudinal coverage approximation of the applied dose, COV). As a proof-of-principle, we assessed the methods' performance to predict the well-characterized bleeding risks of anticoagulant, antiplatelet, and/or non-steroidal anti-inflammatory drugs. RESULTS: When applied to modeling and simulation data sets, the closest, least biased, and thus most accurate approximation was observed using the COV approximation. In a real-data example, rather similar results to an external reference were obtained for all methods. However, some of the differences between methods were meaningful, and the most reasonable and consistent results were obtained with the COV approach. CONCLUSION: Based on theoretically most accurate approximations and practically reasonable estimates, the individual COV approach was preferable over the population-averaged defined daily dose technique, although the latter might be justified in certain situations. Advantages of the COV approach are expected to be even bigger for drug therapies with particularly large dosing heterogeneity.
Authors: Andreas D Meid; Andreas Groll; Ulrich Schieborr; Jochen Walker; Walter E Haefeli Journal: Eur J Clin Pharmacol Date: 2016-12-24 Impact factor: 2.953
Authors: Andreas D Meid; Anna von Medem; Dirk Heider; Jürgen-Bernhard Adler; Christian Günster; Hanna M Seidling; Renate Quinzler; Hans-Helmut König; Walter E Haefeli Journal: Drug Saf Date: 2017-02 Impact factor: 5.606