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Propensity score methods (PSMs) such as matching and weighting have become a mainstay for the estimation of treatment effects from observational data. PSMs require the choice of a treatment effect of interest given a specific target population or subpopulation. The most commonly used treatment effects in observational studies are the average treatment effect (ATE) and the average treatment effect among the treated population (ATT). While the traditional matching approach usually discards observations that cannot be matched and is therefore mainly used for estimation of the ATT, the weighting approach utilizes all observations in most cases and can be used for estimation of both, the ATE and ATT. One concern when using the weighting approach is the occurrence of large weights which may disproportionately influence the results and yield estimates with high variance. Recently several newer approaches, including matching weights and overlap weights have been proposed to overcome these limitations. However, this may complicate the interpretation of the results as the population to be inferred depends on the PS estimate itself.

Background: Venous thromboembolism (VTE) mainly manifests as deep vein thrombosis (TVT) or pulmonary embolism (LE), and is the third most common cardiovascular disease worldwide. However, robust evidence on the incidence of VTE in Germany is lacking., Objective: Estimation and comparison of the incidence of VTE based on different routine data sources of the German healthcare system., Methods: Estimates and comparisons of the incidence of VTE, TVT and LE were made using two databases that both covered the inpatient and the outpatient setting; the DaTraV database comprising information of all persons subject to compulsory health insurance, and the Health Risk Institute (HRI) database derived from approximately 70 statutory health insurance funds. In addition, IMS Disease Analyzer, a medical record database comprising information from the outpatient setting, was used as a data source., Results: Patterns of age- and sex-specific VTE incidence estimates were comparable between all databases used. However, estimates based on the medical record database were comparatively high. Analyses of DaTraV data led to a VTE incidence of 0.14%. Use of HRI data yielded comparable results (0.17-0.20%). VTE incidence based on data of the IMS Disease Analyzer was comparatively high (0.32%)., Discussion: Results on the VTE incidence based on DaTraV or HRI date are comparable to international evidence, whereas the use of the IMS Disease Analyzer data presumably led to an overestimation due to double-counting of VTE cases. Different types of routine healthcare data sources can therefore lead to very heterogeneous results. Thus, the selection of adequate data sources strongly depends on the study question and the quality of the dataset., (Copyright © 2018. Published by Elsevier GmbH.)