BACKGROUND Patient-Reported Outcome Measures (PROMs) have been proposed for benchmarking health care quality across hospitals, which requires extensive case-mix adjustment. The current study's aim was to develop and compare case-mix models for mortality, a functional outcome, and a patient-reported outcome measure (PROM) in ischemic stroke care. METHODS Data from ischemic stroke patients, admitted to four stroke centers in the Netherlands between 2014 and 2016 with available outcome information (N = 1022), was analyzed. Case-mix adjustment models were developed for mortality, modified Rankin Scale (mRS) scores and EQ-5D index scores with respectively binary logistic, proportional odds and linear regression models with stepwise backward selection. Predictive ability of these models was determined with R-squared (R2) and area-under-the-receiver-operating-characteristic-curve (AUC) statistics. RESULTS Age, NIHSS score on admission, and heart failure were the only common predictors across all three case-mix adjustment models. Specific predictors for the EQ-5D index score were sex (β = 0.041), socio-economic status (β = - 0.019) and nationality (β = - 0.074). R2-values for the regression models for mortality (5 predictors), mRS score (9 predictors) and EQ-5D utility score (12 predictors), were respectively R2 = 0.44, R2 = 0.42 and R2 = 0.37. CONCLUSIONS The set of case-mix adjustment variables for the EQ-5D at three months differed considerably from the set for clinical outcomes in stroke care. The case-mix adjustment variables that were specific to this PROM were sex, socio-economic status and nationality. These variables should be considered in future attempts to risk-adjust for PROMs during benchmarking of hospitals.

中文翻译：

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缺血性中风护理中基于价值的医疗保健：临床和患者报告结局的病例混合调整模型。

背景技术已经提出了患者报告的结果量度（PROM）以对整个医院的卫生保健质量进行基准测试，这需要大量的病例组合调整。本研究的目的是开发和比较病例组合模型，用于缺血性中风护理中的死亡率，功能结局和患者报告结局指标（PROM）。方法分析2014年至2016年间在荷兰四个卒中中心收治的缺血性卒中患者的数据，并提供可用的结局信息（N = 1022）。案例混合调整模型针对死亡率，改良的兰金量表（mRS）得分和EQ-5D指数得分进行了开发，分别采用了二进制逻辑，比例赔率和逐步回归的线性回归模型。这些模型的预测能力由R平方（R2）和接收器工作特征曲线下面积（AUC）统计数据确定。结果在所有三种病例混合调整模型中，年龄，入院时NIHSS评分和心力衰竭是唯一常见的预测指标。EQ-5D指数得分的具体预测因子是性别（β= 0.041），社会经济地位（β=-0.019）和国籍（β=-0.074）。死亡率（5个预测因子），mRS评分（9个预测因子）和EQ-5D效用得分（12个预测因子）回归模型的R2值分别为R2 = 0.44，R2 = 0.42和R2 = 0.37。结论EQ-5D在三个月时的病例混合调整变量集与中风护理的临床结果集有很大差异。此PROM特定的大小写混合调整变量是性别，社会经济地位和国籍。在将来对医院进行基准测试期间风险调整PROM时，应考虑这些变量。