Colquhoun Douglas A, Janda Allison M, Mentz Graciela, Fisher Clark A, Schonberger Robert B, Shah Nirav, Kheterpal Sachin, Mathis Michael R
Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan.
Department of Anesthesiology, Yale School of Medicine, New Haven, Connecticut.
Anesthesiology. 2025 May 1;142(5):793-805. doi: 10.1097/ALN.0000000000005395. Epub 2025 Apr 8.
Health services research frequently focuses on variation in the structure, process, and outcomes of clinical care. Robust approaches for detection and attribution of variation are foundational to both quality improvement and outcomes research. Describing care in structured healthcare systems across hospitals in which clinicians work to provide care for patients as a multileveled structure allows the impact of organization on practice and outcome to be ascertained. Mixed-effect statistical models can describe both the partitioning of variation among levels of these structures and by inclusion of explanatory variables the valid estimation of the features of health systems, clinicians, or patients, with observed differences in processes or patient outcomes. In this Readers' Toolbox, the authors describe the rationale for considering healthcare structures when assessing clinical practice, outcomes, and sources of variation. They describe statistical considerations and methods for the estimation of analysis of structured data and assessment of variance.
卫生服务研究经常关注临床护理的结构、过程和结果的差异。用于检测和归因差异的稳健方法是质量改进和结果研究的基础。将临床医生为患者提供护理的医院中的结构化医疗系统中的护理描述为多层次结构,可以确定组织对实践和结果的影响。混合效应统计模型既可以描述这些结构层次之间差异的划分,又可以通过纳入解释变量,对卫生系统、临床医生或患者的特征进行有效估计,同时观察到过程或患者结果中的差异。在本《读者工具箱》中,作者描述了在评估临床实践、结果和差异来源时考虑医疗结构的基本原理。他们描述了结构化数据估计分析和方差评估的统计考虑因素和方法。