Hartman Nicholas, Shahinian Vahakn B, Ashby Valarie B, Price Katrina J, He Kevin
Department of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.
Kidney Epidemiology and Cost Center, University of Michigan, Ann Arbor, MI, U.S.A.
Health Serv Outcomes Res Methodol. 2024 Jun;24(2):156-169. doi: 10.1007/s10742-023-00307-0. Epub 2023 Jun 28.
Healthcare quality measures are statistics that serve to evaluate healthcare providers and identify those that need to improve their care. Before using these measures in clinical practice, developers and reviewers assess measure reliability, which describes the degree to which differences in the measure values reflect actual variation in healthcare quality, as opposed to random noise. The Inter-Unit Reliability (IUR) is a popular statistic for assessing reliability, and it describes the proportion of total variation in a measure that is attributable to between-provider variation. However, Kalbfleisch, He, Xia, and Li (2018) [, 18, 215-225] have argued that the IUR has a severe limitation in that some of the between-provider variation may be unrelated to quality of care. In this paper, we illustrate the practical implications of this limitation through several concrete examples. We show that certain best-practices in measure development, such as careful risk adjustment and exclusion of unstable measure values, can decrease the sample IUR value. These findings uncover potential negative consequences of discarding measures with IUR values below some arbitrary threshold.
医疗质量指标是用于评估医疗服务提供者并识别那些需要改进其医疗服务的统计数据。在临床实践中使用这些指标之前,开发者和评审者会评估指标的可靠性,可靠性描述了指标值的差异在多大程度上反映了医疗质量的实际差异,而非随机噪声。单位间可靠性(IUR)是一种常用的评估可靠性的统计量,它描述了指标总变异中可归因于提供者间变异的比例。然而,卡尔弗莱施、何、夏和李(2018年)[, 18, 215 - 225]认为IUR有一个严重的局限性,即提供者间的某些变异可能与医疗质量无关。在本文中,我们通过几个具体例子说明了这一局限性的实际影响。我们表明,指标开发中的某些最佳实践,如仔细的风险调整和排除不稳定的指标值,可以降低样本IUR值。这些发现揭示了丢弃IUR值低于某个任意阈值的指标可能带来的潜在负面后果。