[Definition of consolidated disease groups for a population-based system to classify morbidity-related healthcare needs: PopGroup].

OBJECTIVE: In recent years there has been an increased demand for a morbidity-oriented approach in the planning of healthcare facilities in Germany. Population-based classification systems, which already exist in various countries, are crucial for assessing regional healthcare needs. The PopGroup project aims to develop such a classification system (PopGrouper) for the German healthcare system and to test various applications. The PopGrouper assigns each individual to exactly one PopGroup based on clinical characteristics and healthcare needs. The initial phase of the PopGrouper development focused on grouping diagnoses into medically meaningful Consolidated Disease Groups (CDGs) to serve as the foundation for forming PopGroups. This article describes the formation and validation of CDGs, as well as the definition of a disease severity level to hierarchically rank the CDGs. METHODS: CDGs were formed using both medical expertise and analyses of claims data from the BARMER sickness fund. Pre-existing diagnosis groups (DxGs) defined for the German morbidity-based risk structure compensation scheme were used as the starting point. Initially, overarching Major Disease Categories (MDCs) were formed. Within MDCs, DxGs were grouped into CDGs based on predefined criteria. CDGs were validated by experts from scientific medical societies. Finally, a composite disease severity score was calculated based on three dimensions (mortality, costs, utilization) and severity levels from "very severe" to "very minor" were defined to classify CDGs. RESULTS: A total of 32 MDCs and 433 CDGs were defined and validated. Each CDG received a severity score. Based on this foundation, in the subsequent project phase, PopGroups were formed that took into consideration various diseases and combinations of diseases. CONCLUSION: CDGs and MDCs represent important initial steps in the PopGrouper development. The aggregation of diagnoses into a smaller number of medically meaningful groups also offers opportunities beyond the project, for instance for healthcare research, for the analysis of diseases, and for the identification of patient groups with similar characteristics.