Danh V Nguyen, Qi Qian, Amy S. You, Esra Kurum, Connie M. Rhee, Damla Senturk
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引用次数: 0
摘要
剖析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与患者结果(如 30 天非计划再入院或死亡率)相关的服务提供者。固定效应(FE)分析模型在过去十年中得到了发展,其总体需求是:(a)提高准确识别或 "标记 "表现不佳的医疗服务提供者的能力;(b)放宽随机效应(RE)分析模型的固有假设;(c)考虑透析终末期肾病(ESKD)患者的独特疾病特征和护理/治疗过程。在本文中,我们回顾了 FE 方法的现状及其在 ESKD 群体中的合理性,并说明了在四个关键领域中的应用:利用标准化动态再入院率 (SDRR) 分析透析机构在以下方面的情况:(1)随时间推移(纵向)的患者住院情况;(2)确定导致再入院的透析机构特征(如人员配置水平);(3)利用标准化事件比率 (SER) 分析不良复发事件。此外,我们还重点研究了 FE 剖析模型的运行特征。在这些应用于 ESKD 人群的领域中,我们确定了未来在方法论和临床研究方面的挑战。
High-Dimensional Fixed Effects Profiling Models and Applications in End-Stage Kidney Disease Patients: Current State and Future Directions
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.