25gmds152 10.3205/25gmds152 urn:nbn:de:0183-25gmds1524 Meeting Abstract Krampe Krampe Jonas J

Gesundheitsforen Leipzig GmbH, Leipzig, Germany

author Leppert Leppert Beate B

Gesundheitsforen Leipzig GmbH, Leipzig, Germany

author Melnik Melnik Sima S

Gesundheitsforen Leipzig GmbH, Leipzig, Germany

author Puschmann Puschmann Julia J

Gesundheitsforen Leipzig GmbH, Leipzig, Germany

author German Medical Science GMS Publishing House

Düsseldorf

610 claims data extrapolation strategies risk adjustment 20251103 engl This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). M0631 152 Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie 70. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS) PS 8: Medizinische Biometrie Jena 20250907 20250911 Abstr. 91 TextIntroduction: Claims data in health service research offers potential for diverse analysis due to its large sample size, potential for longitudinal tracking, and lack of selection bias. This study aims to describe the Deutsche Analysedatenbank für Evaluation und Versorgungsforschung (DADB) database and explore how different extrapolation strategies affect representativeness relative to the German statutory health insurance (SHI) population based on available demographic measures and morbidity groups.Methods: The DADB includes data from approximately 4.4 million insured individuals (4% of the German SHI population in 2023), covering inpatient and outpatient diagnoses, procedural codes, and cost data. To ehance representativeness, adjustments for age, gender, and morbidity – based on the Risikostrukturausgleich (RSA) – were applied. The impact on confidence intervals is also discussed.Results: Compared to the overall SHI population, the DADB includes a slightly younger demographic. Frequencies of morbidity groups are similar between the datasets, though slightly lower in the DADB.These differences diminish after demographic and morbidity-based adjustments.Conclusion: The age and gender-adjusted DADB demonstrates good representativeness for the German SHI population. When significant discrepancies persist, further risk adjustment is advised. he DADB offers a comprehensive, longitudinal view of patient healthcare utilization, including the capacity to construct medication treatment lines.The authors declare that they have no competing interests.The authors declare that an ethics committee vote is not required.The contribution has already been published: Krampe J Utilizing claims data for health service research: an examination of extrapolation strategies of German SHI Data 2024 23. Deutscher Kongress für Versorgungsforschung (DKVF). Potsdam, 25.-27.09.2024 Krampe J, et al. Utilizing claims data for health service research: an examination of extrapolation strategies of German SHI Data. In: 23. Deutscher Kongress für Versorgungsforschung (DKVF). Potsdam, 25.-27.09.2024. Düsseldorf: GMS; 2024. Doc24dkvf055 DOI: 10.3205/24dkvf055 https://doi.org/10.3205/24dkvf055 0 0 0 0