COMPOSITE SCORES FOR TRANSPLANT CENTER EVALUATION: A NEW INDIVIDUALIZED EMPIRICAL NULL METHOD.

IF 1.3 4区 数学 Q2 STATISTICS & PROBABILITY
Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI:10.1214/23-aoas1809
Nicholas Hartman, Joseph M Messana, Jian Kang, Abhijit S Naik, Tempie H Shearon, Kevin He
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引用次数: 0

Abstract

Risk-adjusted quality measures are used to evaluate healthcare providers with respect to national norms while controlling for factors beyond their control. Existing healthcare provider profiling approaches typically assume that the between-provider variation in these measures is entirely due to meaningful differences in quality of care. However, in practice, much of the between-provider variation will be due to trivial fluctuations in healthcare quality, or unobservable confounding risk factors. If these additional sources of variation are not accounted for, conventional methods will disproportionately identify larger providers as outliers, even though their departures from the national norms may not be "extreme" or clinically meaningful. Motivated by efforts to evaluate the quality of care provided by transplant centers, we develop a composite evaluation score based on a novel individualized empirical null method, which robustly accounts for overdispersion due to unobserved risk factors, models the marginal variance of standardized scores as a function of the effective sample size, and only requires the use of publicly-available center-level statistics. The evaluations of United States kidney transplant centers based on the proposed composite score are substantially different from those based on conventional methods. Simulations show that the proposed empirical null approach more accurately classifies centers in terms of quality of care, compared to existing methods.

用于移植中心评估的综合评分:一种新的个性化经验无效法。
风险调整后的质量衡量标准用于评估医疗服务提供者是否符合国家规范,同时控制其无法控制的因素。现有的医疗服务提供者特征分析方法通常假定,这些指标在提供者之间的差异完全是由于医疗服务质量方面存在有意义的差异造成的。但实际上,医疗服务提供者之间的差异很大程度上是由于医疗质量的微小波动或不可观测的混杂风险因素造成的。如果不考虑这些额外的差异来源,传统方法就会不成比例地将规模较大的医疗服务提供者视为异常值,尽管他们偏离全国标准的程度可能并不 "极端",也没有临床意义。受移植中心医疗质量评估工作的启发,我们开发了一种基于新颖的个性化经验零方法的综合评估分数,该方法能稳健地考虑未观察到的风险因素导致的过度分散,将标准化分数的边际方差作为有效样本量的函数进行建模,并且只需要使用公开的中心级统计数据。根据建议的综合评分对美国肾移植中心进行的评估与根据传统方法进行的评估有很大不同。模拟结果表明,与现有方法相比,建议的经验空方法能更准确地对中心的医疗质量进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Applied Statistics
Annals of Applied Statistics 社会科学-统计学与概率论
CiteScore
3.10
自引率
5.60%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Statistical research spans an enormous range from direct subject-matter collaborations to pure mathematical theory. The Annals of Applied Statistics, the newest journal from the IMS, is aimed at papers in the applied half of this range. Published quarterly in both print and electronic form, our goal is to provide a timely and unified forum for all areas of applied statistics.
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