论文标题
院间差异的因果中介分析分解
Causal mediation analysis decomposition of between-hospital variance
论文作者
论文摘要
特定疾病特异性质量指标的因果方差分解可用于量化医院或医疗保健提供者之间的绩效差异。尽管方差分解可以证明护理质量的差异，但可用于研究护理途径，导致机构之间的绩效差异。这就提出了一个问题，即是否可以将两种方法合并以将结果类型指标分解为通过给定过程（间接效应）和由于所有其他途径引起的剩余变化（直接效应）引起的介导的院之间变化。为此，我们得出了院间差异的因果中介分析分解，讨论其解释，并提出了基于对结果和调解器的广义线性混合模型的估计方法。我们在一项仿真研究中研究了估计量的性能，并证明了其在安大略省肾脏癌症护理的行政数据中的使用。
Causal variance decompositions for a given disease-specific quality indicator can be used to quantify differences in performance between hospitals or health care providers. While variance decompositions can demonstrate variation in quality of care, causal mediation analysis can be used to study care pathways leading to the differences in performance between the institutions. This raises the question of whether the two approaches can be combined to decompose between-hospital variation in an outcome type indicator to that mediated through a given process (indirect effect) and remaining variation due to all other pathways (direct effect). For this purpose, we derive a causal mediation analysis decomposition of between-hospital variance, discuss its interpretation, and propose an estimation approach based on generalized linear mixed models for the outcome and the mediator. We study the performance of the estimators in a simulation study and demonstrate its use in administrative data on kidney cancer care in Ontario.
