Department of Biostatistics, University of Michigan, Ann Arbor, Michigan.
Stat Med. 2019 Feb 28;38(5):844-854. doi: 10.1002/sim.8005. Epub 2018 Oct 18.
In monitoring dialysis facilities, various quality measures are used in order to assess the performance and quality of care. The inter-unit reliability (IUR) describes the proportion of variation in the quality measure that is due to the between-facility variation. If the measure under evaluation is a simple average across normally distributed patient outcomes for each facility, the IUR is based on a one-way analysis of variance (ANOVA). However, more complex quality measures are not simple averages of individual outcomes. Even the standard bootstrap methods are inadequate because the computational burden increases quickly as the sample size grows, prohibiting its application in large-scale studies. To generalize the IUR to complex quality measures used in nonlinear models, we propose an approach combining the strengths of ANOVA and resampling. The proposed method is computationally efficient and can be applied to large-scale biomedical data with complex data structures. The method is exemplified in various measures of dialysis facilities using national dialysis data.
在监测透析设施时,使用各种质量措施来评估性能和护理质量。单元间可靠性 (IUR) 描述了质量指标中由于设施间变化而导致的变化比例。如果评估的指标是每个设施的正态分布患者结果的简单平均值,则 IUR 基于单因素方差分析 (ANOVA)。然而,更复杂的质量指标不是单个结果的简单平均值。即使是标准的自举方法也不够,因为随着样本量的增加,计算负担会迅速增加,从而禁止其在大规模研究中应用。为了将 IUR 推广到非线性模型中使用的复杂质量指标,我们提出了一种结合 ANOVA 和重采样优势的方法。所提出的方法计算效率高,可应用于具有复杂数据结构的大规模生物医学数据。该方法在使用国家透析数据的各种透析设施措施中得到了例证。