Department of Veterans Affairs, Office of Productivity, Efficiency and Staffing, Bedford, MA, USA.
Health Care Manag Sci. 2012 Jun;15(2):121-37. doi: 10.1007/s10729-011-9189-0. Epub 2011 Dec 14.
We develop a patient level hierarchical regression model using administrative claims data to assess mortality outcomes for a national VA population. This model, which complements more traditional process driven performance measures, includes demographic variables and disease specific measures of risk classified by Diagnostic Cost Groups (DCGs). Results indicate some ability to discriminate survivors and non-survivors with an area under the Receiver Operating Characteristic Curve (C-statistic) of .86. Observed to expected mortality ranges from .86 to 1.12 across predicted mortality deciles while Risk Standardized Mortality Rates (RSMRs) range from .76 to 1.29 across 145 VA hospitals. Further research is necessary to understand mortality variation which persists even after adjusting for case mix differences. Future work is also necessary to examine the role of personal behaviors on patient outcomes and the potential impact on population survival rates from changes in treatment policy and infrastructure investment.
我们利用行政索赔数据开发了一个患者层面的层次回归模型,以评估全国退伍军人事务部人群的死亡率结果。该模型补充了更传统的基于流程的绩效衡量标准,包括按诊断费用组 (DCG) 分类的人口统计学变量和疾病特异性风险衡量标准。结果表明,该模型具有一定的区分生存者和非生存者的能力,其接收者操作特征曲线 (C 统计量) 的面积为.86。在预测死亡率的十分位数中,观察到的死亡率与预期死亡率的范围从.86 到 1.12,而风险标准化死亡率 (RSMR) 的范围从 145 家退伍军人事务部医院的.76 到 1.29。即使在调整了病例组合差异后,仍需要进一步研究以了解死亡率的变化。未来的工作还需要研究个人行为对患者结果的影响,以及治疗政策和基础设施投资变化对人群生存率的潜在影响。