A Comparison of statistical methods for hospital performance assessment

Xiaoting Wu, M. Zhang, Ruyun Jin, G. Grunkemeier, C. Maynard, Ravi S Hira, T. Mackenzie, M. Herbert, Chang He, S. Holmes, M. Thompson, D. Likosky
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Abstract

During hospital quality improvement activities, statistical approaches are critical to help assess hospital performance for benchmarking. Current statistical approaches are used primarily for research and reimbursement purposes. In this multiinstitutional study, these established statistical methods were evaluated for quality improvement applications. Leveraging a dataset of 42,199 patients who underwent coronary artery bypass grafting surgery from 2014 to 2016 across 90 hospitals, six statistical approaches were applied. The non-shrinkage methods were: (1) indirect standardization without hospital effect; (2) indirect standardization with hospital fixed effect; (3) direct standardization with hospital fixed effect. The shrinkage methods were: (4) indirect standardization with hospital random effect; (5) direct standardization with hospital random effect; (6) Bayesian method. Hospital performance related to operative mortality and major morbidity or mortality was compared across methods based on variation in adjusted rates, rankings, and performance outliers. Method performance was evaluated across procedure volume terciles: small ( 171). Shrinkage methods reduced inter-hospital variation (min-max) for mortality (observed: 0%-10%; adjusted: 1.5%-2.4%) and major morbidity or mortality (observed: 2.6%-35%; adjusted: 6.9%-17.5%). Shrinkage methods shrunk hospital rates toward the group mean. Direct standardization with hospital random effect, compared to fixed effect, resulted in 16.7%-38.9% of hospitals changing quintile mortality ranking. Indirect standardization with hospital random effect resulted in no performance outliers among small and medium hospitals for mortality, while logistic and fixed effect methods identified one small and three medium outlier hospitals. The choice of statistical method greatly impacts hospital ranking and performance outlier’ status. These findings should be considered when benchmarking hospital performance for hospital quality improvement activities.
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医院绩效考核统计方法的比较
在医院质量改进活动中,统计方法对于帮助评估医院绩效以制定基准至关重要。目前的统计方法主要用于研究和报销目的。在这项多机构研究中,这些已建立的统计方法被评估为质量改进的应用。利用2014年至2016年在90家医院接受冠状动脉搭桥术的42199例患者的数据集,采用了六种统计方法。非收缩方法:(1)间接标准化,不影响医院;(2)具有医院固定效应的间接标准化;(3)具有医院固定效果的直接标准化。收缩方法:(4)采用医院随机效应间接标准化;(5)具有医院随机效应的直接标准化;(6)贝叶斯方法。基于调整率、排名和异常值的差异,比较了不同方法中与手术死亡率和主要发病率或死亡率相关的医院绩效。方法的性能在程序体积范围内进行评估:小(171)。收缩方法减少了医院间死亡率的差异(最小-最大)(观察到:0%-10%;调整:1.5%-2.4%)和主要发病率或死亡率(观察:2.6%-35%;调整:6.9% - -17.5%)。收缩方法使住院率向组平均水平收缩。与固定效应相比,采用医院随机效应的直接标准化导致16.7%-38.9%的医院发生五分位死亡率排名变化。采用医院随机效应的间接标准化方法对中小医院的死亡率没有发现绩效异常值,而logistic和固定效应方法分别发现了1家小型和3家中型异常值医院。统计方法的选择对医院排名和绩效异常值的状况有很大影响。在为医院质量改进活动制定医院绩效基准时,应考虑这些发现。
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