|Title:||Methods and applications for the secondary use of claims data from the Austrian health insurance system||Language:||English||Authors:||Endel, Florian||Qualification level:||Diploma||Advisor:||Filzmoser, Peter||Issue Date:||2021||Number of Pages:||165||Qualification level:||Diploma||Abstract:||
Background Previous studies suggest that a significantly increased risk to suffer frommyocardial infarction can be observed for parents in comparison with adults withoutchildren. However, definitive evidence is lacking and insufficient to adapt clinical practiceguidelines 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 ofmyocardial infarction in parents compared with couples without children in a retrospective,observational cohort study.Methods Reimbursement data from the health care system are routinely collectedby 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 potentialcases.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 forindirect deduction of this personal information is developed and implemented. Furthermore, information about individual comorbidities and the social-economic status arededuced.Identified cohorts are documented in detail and various statistical procedures are applied.Such methods include univariate statistics and cross-tabulations, decision trees, andmultivariate regression models. Resampling, balancing, and propensity score matchingare 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 andgenealogical information, the handling of socioeconomic information, and morbidityscores are reported in detail.
|Keywords:||Health risk; Propensity scores; Regression; Robustness||URI:||https://doi.org/10.34726/hss.2021.35400
|DOI:||10.34726/hss.2021.35400||Library ID:||AC16194153||Organisation:||E180 - Fakultät für Informatik||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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checked on May 13, 2021
checked on May 13, 2021
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