Liver Unit, Division of Gastroenterology and Hepatology, Department of Medicine, University of Calgary, Alberta, Canada.
Ann Hepatol. 2012 Jul-Aug;11(4):526-35.
Hospital outcome report cards are used to judge provider performance, including for liver transplantation. We aimed to determine the impact of the choice of risk adjustment method on hospital rankings based on mortality rates in cirrhotic patients.
We identified 68,426 cirrhotic patients hospitalized in the Nationwide Inpatient Sample database. Four risk adjustment methods (the Charlson/Deyo and Elixhauser algorithms, Disease Staging, and All Patient Refined Diagnosis Related Groups) were used in logistic regression models for mortality. Observed to expected (O/E) death rates were calculated for each method and hospital. Statistical outliers with higher or lower than expected mortality were identified and rankings compared across methods.
Unadjusted mortality rates for the 553 hospitals ranged from 1.4 to 30% (overall, 10.6%). For 163 hospitals (29.5%), observed mortality differed significantly from expected when judged by one or more, but not all four, risk adjustment methods (25.9% higher than expected mortality and 3.6% lower than expected mortality). Only 28% of poor performers and 10% of superior performers were consistently ranked as such by all methods. Agreement between methods as to whether hospitals were flagged as outliers was moderate (kappa 0.51-0.59), except the Charlson/Deyo and Elixhauser algorithms which demonstrated excellent agreement (kappa 0.75).
Hospital performance reports for patients with cirrhosis require sensitivity to the method of risk adjustment. Depending upon the method, up to 30% of hospitals may be flagged as outliers by one, but not all methods. These discrepancies could have important implications for centers erroneously labeled as high mortality outliers.
医院绩效报告卡用于评估医疗服务提供者的绩效，包括肝移植。本研究旨在评估基于肝硬化患者死亡率的风险调整方法选择对医院排名的影响。
我们在全美住院患者样本数据库中确定了 68426 名肝硬化患者。使用逻辑回归模型对死亡率进行了 4 种风险调整方法（Charlson/Deyo 和 Elixhauser 算法、疾病分期和所有患者精细化诊断相关组）的评估。计算了每种方法和医院的观察到的与预期的死亡率（O/E）。确定了高于或低于预期死亡率的统计异常值，并比较了不同方法的排名。
553 家医院的未调整死亡率范围为 1.4%至 30%（总体为 10.6%）。对于 163 家医院（29.5%），通过一种或多种但不是所有四种风险调整方法判断时，观察到的死亡率与预期死亡率显著不同（高于预期死亡率 25.9%，低于预期死亡率 3.6%）。只有 28%的表现不佳的医院和 10%的表现优异的医院始终被所有方法一致评为较差或较好。方法之间对医院是否被标记为异常值的一致性中等（kappa 值 0.51-0.59），除了 Charlson/Deyo 和 Elixhauser 算法，这两种方法具有极好的一致性（kappa 值 0.75）。
肝硬化患者的医院绩效报告需要对风险调整方法敏感。根据方法的不同，多达 30%的医院可能会被一种方法标记为异常值，但不是所有方法。这些差异可能对被错误标记为高死亡率异常值的中心产生重要影响。
