ArticleResearch in health services & regions2025
The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework.
Article in Research in health services & regions, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Regional variation in healthcare utilization among patients with depression in Germany: a multilevel analysis with PopGrouper-based multimorbidity adjustment.Research in health services & regions · 2026Article
- Regional variation in ambulatory care-sensitive hospitalizations for people with type 2 diabetes in Germany: insights from a claims data analysis using the PopGrouper.Research in health services & regions · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalyzing regional variations can help improve equity, efficiency, and quality in health care provision. The PopGrouper is a population-based classification system which classifies persons with similar health care needs into distinct groups. It exhibits a high degree of morbidity differentiation. We present an analytical framework to use the PopGrouper in examining regional variations across different outcomes and populations using routine patient-level data.
methodsWe develop a two-step empirical strategy to examine the relative regional performance on a set of efficiency and quality outcomes (e.g., hospital bed days, cost of care, mortality). First, we propose PopGroup-standardized observed-to-expected ratios to compare regional performance. Second, we develop a multilevel regression model to separately estimate regional variation related to patient need measured by the PopGroup and variation related to regional characteristics.
resultsWe provide an analytical framework that demonstrates the PopGrouper's application as a tool for morbidity adjustment in the assessment of relative regional performance in efficiency and quality outcomes and the regional characteristics that explain this performance. We provide suggestions for empirical notation, interpretation of results, and graphical analyses of findings. The developed framework will be applied in subsequent empirical papers.
conclusionThis paper sets the analytical foundations to be applied in regional comparative analyses using the PopGrouper allowing for conclusions about unexplained variations in quality and efficiency of health care.
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