ArticleGesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))2026
[Formation of disease- and needs-related homogeneous groups of insured persons - PopGrouper 1.0].
Article in Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: Population-based classification systems are used in various countries to assess and present healthcare needs. The PopGroup project aimed to develop such a classification system for the German healthcare context. Version 1.0 of the PopGrouper is now available and assigns each person to exactly one PopGroup (PG). This article builds on a previous publication on the grouping of diseases with assignments of severity levels and explains the next steps for the mutually exclusive grouping of all insured persons across several levels, thus completing the methodological description of the grouper. Methodology: For the development of version 1.0, training and test data from a total of 8.8 million insured persons of the BARMER health insurance fund for the year 2022 were used in a ratio of 4 to 1. After an initial content and clinically oriented grouping, further splits were carried out algorithmically using decision lists and regression trees. This resulted in a set of rules that can be used also for grouping of other populations. Results: All individuals were assigned to exactly one of 10, 427, or 610 groups and finally into 776 PGs across 4 hierarchical levels. PGs explained 38.8% of the variance in insurance-related documented health care costs in test data. After applying the grouping rules to data from 2021 and 2023, the results were similar, with explained variance shares across all grouping levels tending to be higher in 2023 than in 2022. Conclusion: The PopGrouper 1.0 is the first population-based grouper adapted for statutory health insurance data in Germany that is comprehensively documented and free to use. The grouper has proven useful for data from the years 2021 to 2023, for which complete grouping rules already exist. The grouper should be updated for future years, while also examining to what extent simplifications of the grouper and its maintenance are possible without loss of quality.
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