Nguyen Danh V, Qian Qi, You Amy S, Kurum Esra, Rhee Connie M, Senturk Damla
Department of Medicine, University of California Irvine, Orange, CA 92868, USA.
Department of Biostatistics, University of California, Los Angeles, CA 90095, USA.
Int J Stat Med Res. 2023 Feb 15;12:193-212. doi: 10.6000/1929-6029.2023.12.24.
Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or "flagging" of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies.
概况分析旨在评估医疗服务提供者,包括医院、疗养院或透析设施等在患者预后方面的表现,例如30天内非计划再次入院或死亡率。在过去十年中,固定效应(FE)概况分析模型得以发展,其动机主要有以下几点:(a)提高对表现不佳的医疗服务提供者的准确识别或“标记”;(b)放宽随机效应(RE)概况分析模型中固有的假设;(c)考虑接受透析治疗的终末期肾病(ESKD)患者独特的疾病特征以及护理/治疗过程。在本文中,我们回顾了FE方法在ESKD人群中的现状及其基本原理,并阐述其在四个关键领域的应用:使用标准化动态再入院率(SDRR)对透析设施进行(1)患者随时间(纵向)住院情况的概况分析,(2)识别导致医院再入院的透析设施特征(如人员配备水平),以及(3)使用标准化事件率(SER)对不良复发事件进行概况分析。此外,我们重点研究FE概况分析模型的操作特征。在针对ESKD人群的这些应用领域中,我们确定了未来在方法学和临床研究方面的研究挑战。