Endel, F. (2021). Methods and applications for the secondary use of claims data from the Austrian health insurance system [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.35400
Health risk; Propensity scores; Regression; Robustness
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Abstract:
Background Previous studies suggest that a significantly increased risk to suffer from myocardial infarction can be observed for parents in comparison with adults without children. However, definitive evidence is lacking and insufficient to adapt clinical practice guidelines on that basis. Furthermore, actual cases seem to be rare and backing data isnot available. Objectives The main objective of this work is to gather evidence on the relative risk of myocardial infarction in parents compared with couples without children in a retrospective, observational cohort study. Methods Reimbursement data from the health care system are routinely collected by Austrian social insurance institutions for administrative and accounting purposes. GAP-DRG, a linked research database holding data from the Austrian health and socialinsurance system covering several years is utilized to determine the number of potential cases. Genealogical information is crucial but lacking from the data source. As a result, parentship is not encoded in the available administrative data. Therefore, a method for indirect deduction of this personal information is developed and implemented. Furthermore, information about individual comorbidities and the social-economic status are deduced. Identified cohorts are documented in detail and various statistical procedures are applied. Such methods include univariate statistics and cross-tabulations, decision trees, and multivariate regression models. Resampling, balancing, and propensity score matching are used to achieve more accurate estimates and robustness. Results In summary, no additional evidence was found to support the initial claim. In addition, unprecedented developments such as the disclosure of previously unknowndata quality problems in the administrative data source, coinsurance networks and genealogical information, the handling of socioeconomic information, and morbidity scores are reported in detail.