Kreutzberg Anika, Tsatsaronis Chrissa, Grobe Thomas G, Quentin Wilm, Busse Reinhard
Department of Health Care Management, Technische Universität Berlin, Berlin, Germany.
Abteilung Gesundheitsberichterstattung und Biometrie, Institut für angewandte Qualitätsförderung und Forschung im Gesundheitswesen GmbH, Göttingen, Germany.
Res Health Serv Reg. 2025 Aug 6;4(1):10. doi: 10.1007/s43999-025-00068-y.
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.
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.
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.
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.
分析地区差异有助于提高医疗服务的公平性、效率和质量。PopGrouper是一种基于人群的分类系统，它将有相似医疗需求的人分为不同的组。该系统具有高度的发病率差异。我们提出了一个分析框架，用于利用PopGrouper，通过常规患者层面的数据来研究不同结果和人群之间的地区差异。
我们制定了一个两步实证策略，以检验在一系列效率和质量结果（如住院天数、护理成本、死亡率）方面的相对地区表现。首先，我们提出PopGroup标准化的观察值与预期值比率，以比较地区表现。其次，我们开发了一个多层次回归模型，分别估计与PopGroup衡量的患者需求相关的地区差异以及与地区特征相关的差异。
我们提供了一个分析框架，展示了PopGrouper作为一种工具在评估效率和质量结果方面的发病率调整以及解释这种表现的地区特征中的应用。我们为实证符号、结果解释和研究结果的图形分析提供了建议。所开发的框架将应用于后续的实证论文中。
本文奠定了在使用PopGrouper进行地区比较分析中的分析基础，从而能够得出关于医疗保健质量和效率中无法解释的差异的结论。
