The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework

Abstract Background Analyzing 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...

Full description

Saved in:
Bibliographic Details
Main Authors: Anika Kreutzberg, Chrissa Tsatsaronis, Thomas G. Grobe, Wilm Quentin, Reinhard Busse, On behalf of the PopGroup consortium
Format: Article
Language:English
Published: Springer 2025-08-01
Series:Research in Health Services & Regions
Subjects:
Online Access:https://doi.org/10.1007/s43999-025-00068-y
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849333767284457472
author Anika Kreutzberg
Chrissa Tsatsaronis
Thomas G. Grobe
Wilm Quentin
Reinhard Busse
On behalf of the PopGroup consortium
author_facet Anika Kreutzberg
Chrissa Tsatsaronis
Thomas G. Grobe
Wilm Quentin
Reinhard Busse
On behalf of the PopGroup consortium
author_sort Anika Kreutzberg
collection DOAJ
description Abstract Background Analyzing 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. Methods We 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. Results We 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. Conclusion This 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.
format Article
id doaj-art-3abe2ac1dcd041168356798ab83687f0
institution Kabale University
issn 2730-9827
language English
publishDate 2025-08-01
publisher Springer
record_format Article
series Research in Health Services & Regions
spelling doaj-art-3abe2ac1dcd041168356798ab83687f02025-08-20T03:45:45ZengSpringerResearch in Health Services & Regions2730-98272025-08-014111310.1007/s43999-025-00068-yThe PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical frameworkAnika Kreutzberg0Chrissa Tsatsaronis1Thomas G. Grobe2Wilm Quentin3Reinhard Busse4On behalf of the PopGroup consortiumDepartment of Health Care Management, Technische Universität BerlinDepartment of Health Care Management, Technische Universität BerlinAbteilung Gesundheitsberichterstattung und Biometrie, Institut für angewandte Qualitätsförderung und Forschung im Gesundheitswesen GmbHDepartment for Planetary and Public Health, Universität BayreuthDepartment of Health Care Management, Technische Universität BerlinAbstract Background Analyzing 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. Methods We 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. Results We 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. Conclusion This 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.https://doi.org/10.1007/s43999-025-00068-yPopulation classificationRegional analysisRisk adjustmentClaims dataGermany
spellingShingle Anika Kreutzberg
Chrissa Tsatsaronis
Thomas G. Grobe
Wilm Quentin
Reinhard Busse
On behalf of the PopGroup consortium
The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework
Research in Health Services & Regions
Population classification
Regional analysis
Risk adjustment
Claims data
Germany
title The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework
title_full The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework
title_fullStr The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework
title_full_unstemmed The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework
title_short The PopGrouper as a tool for morbidity adjustment in regional comparisons of health care: an analytical framework
title_sort popgrouper as a tool for morbidity adjustment in regional comparisons of health care an analytical framework
topic Population classification
Regional analysis
Risk adjustment
Claims data
Germany
url https://doi.org/10.1007/s43999-025-00068-y
work_keys_str_mv AT anikakreutzberg thepopgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT chrissatsatsaronis thepopgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT thomasggrobe thepopgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT wilmquentin thepopgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT reinhardbusse thepopgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT onbehalfofthepopgroupconsortium thepopgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT anikakreutzberg popgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT chrissatsatsaronis popgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT thomasggrobe popgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT wilmquentin popgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT reinhardbusse popgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework
AT onbehalfofthepopgroupconsortium popgrouperasatoolformorbidityadjustmentinregionalcomparisonsofhealthcareananalyticalframework