Representativeness and external comparability of the InGef research database for epidemiological studies in Germany

Abstract Background Claims data from statutory health insurance (SHI) funds are increasingly used in public health research. We evaluated the representativeness and external comparability of the InGef research database (RDB), which contains anonymized claims data from approximately 10 million SHI-insured individuals in Germany, using selected disease-specific indicators. Methods A retrospective cohort study combining cross-sectional and longitudinal analyses (2015–2023) was conducted. We assessed (1) follow-up duration, (2) demographic representativeness, and external comparability based on two complementary reference indications (3) incidence and mortality of lung cancer, and (4) prevalence and pharmaceutical treatment of bronchial asthma. All outcomes were compared with external reference data from the German Federal Statistical Office (DESTATIS), the German Centre for Cancer Registry Data (ZfKD), and the SHI Pharmaceutical Index (GKV-AI). Direct age and sex standardization was applied to ensure comparability. Results The InGef-RDB showed high concordance with the general German population in terms of age and sex distribution (maximum deviation < 0.6 percentage points). 73% of all insured persons remained continuously observable over 9 years. 6.9% died and 19.5% left the database due to changes in their insurance provider, corresponding to an average annual attrition rate of approximately 2.4%. Overall mortality was slightly lower than national statistics (− 0.3 to − 0.4 percentage points). Between 2016 and 2022, the standardized asthma prevalence rose from 5,938 to 6,602 per 100,000 population, before decreasing to 5,977 per 100,000 in 2023. Monoclonal antibody prescription rates for asthma deviated by < 0.01 percentage points from SHI benchmarks. Lung cancer incidence (2016–2022) averaged 41.8 cases per 100,000 persons, closely matching ZfKD data. Conclusions The InGef-RDB demonstrates strong demographic alignment and good external comparability across distinct epidemiologic and health care use scenarios. Based on these evaluations, it represents a valid and reliable real-world data source for population-based epidemiological and health services research, provided that appropriate methodological adjustments are applied.