Myers Robert P, Quan Hude, Hubbard James N, Shaheen Abdel Aziz M, Kaplan Gilaad G
Department of Medicine, Division of Gastroenterology, University of Calgary, Calgary, Alberta, Canada.
Hepatology. 2009 Feb;49(2):568-77. doi: 10.1002/hep.22676.
Risk-adjusted health outcomes are often used to measure the quality of hospital care, yet the optimal approach in patients with liver disease is unclear. We sought to determine whether assessments of illness severity, defined as risk for in-hospital mortality, vary across methods in patients with cirrhosis. We identified 258,731 patients with cirrhosis hospitalized in the Nationwide Inpatient Sample between 2002 and 2005. The performance of four common risk adjustment methods (the Charlson/Deyo and Elixhauser comorbidity algorithms, Disease Staging, and All Patient Refined Diagnosis Related Groups [APR-DRGs]) for predicting in-hospital mortality was determined using the c-statistic. Subgroup analyses were conducted according to a primary versus secondary diagnosis of cirrhosis and in homogeneous patient subgroups (hepatic encephalopathy, hepatocellular carcinoma, congestive heart failure, pneumonia, hip fracture, and cholelithiasis). Patients were also ranked according to the probability of death as predicted by each method, and rankings were compared across methods. Predicted mortality according to the risk adjustment methods agreed for only 55%-67% of patients. Similarly, performance of the methods for predicting in-hospital mortality varied significantly. Overall, the c-statistics (95% confidence interval) for the Charlson/Deyo and Elixhauser algorithms, Disease Staging, and APR-DRGs were 0.683 (0.680-0.687), 0.749 (0.746-0.752), 0.832 (0.829-0.834), and 0.875 (0.873-0.878), respectively. Results were robust across diagnostic subgroups, but performance was lower in patients with a primary versus secondary diagnosis of cirrhosis.
Mortality analyses in patients with cirrhosis require sensitivity to the method of risk adjustment. Because different methods often produce divergent severity rankings, analyses of provider-specific outcomes may be biased depending on the method used.
风险调整后的健康结局常被用于衡量医院护理质量，但肝病患者的最佳方法尚不清楚。我们试图确定疾病严重程度评估（定义为住院死亡率风险）在肝硬化患者中是否因方法不同而有所差异。我们在全国住院患者样本中识别出2002年至2005年间住院的258,731例肝硬化患者。使用c统计量确定四种常见风险调整方法（Charlson/Deyo和Elixhauser共病算法、疾病分期以及所有患者细化诊断相关组[APR - DRGs]）预测住院死亡率的性能。根据肝硬化的原发性与继发性诊断以及在同质患者亚组（肝性脑病、肝细胞癌、充血性心力衰竭、肺炎、髋部骨折和胆结石）中进行亚组分析。患者还根据每种方法预测的死亡概率进行排序，并比较不同方法之间的排序。根据风险调整方法预测的死亡率仅在55% - 67%的患者中一致。同样，预测住院死亡率的方法性能差异显著。总体而言，Charlson/Deyo和Elixhauser算法、疾病分期以及APR - DRGs的c统计量（95%置信区间）分别为0.683（0.680 - 0.687）、0.749（0.746 - 0.752）、0.832（0.829 - 0.834）和0.875（0.873 - 0.878）。结果在各诊断亚组中都很稳健，但肝硬化原发性诊断患者的性能低于继发性诊断患者。
肝硬化患者的死亡率分析需要对风险调整方法具有敏感性。由于不同方法通常会产生不同的严重程度排名，根据所使用的方法，对医疗服务提供者特定结局的分析可能存在偏差。
