Fulton Lawrence V, Lasdon Leon S, McDaniel Reuben R, Coppola Nicholas
Information Systems Department at Baylor University.
Hosp Top. 2008 Fall;86(4):3-16. doi: 10.3200/HTPS.86.4.3-17.
The authors investigated cost models that incorporate quality, access, and efficiency to provide decision support for resource forecasting in the multi-billion-dollar U.S. Army health system. As the Army relocates thousands of troops, the medical system must plan for changes in demand; this study supports that effort. Loglinear cost models that include data envelopment analysis (DEA) efficiency scores were evaluated through ordinary least squares estimation, ridge regression, and robust regression, and serve as the analytical framework. Parsimonious models that incorporate a simple volume-complexity metric, a DEA metric, a quality metric, and medical center status variable provide superior forecasting capability.
作者们研究了包含质量、可及性和效率的成本模型，以为美国陆军数十亿美元的医疗系统中的资源预测提供决策支持。随着陆军重新部署数千名部队，医疗系统必须为需求变化做出规划；本研究为这一努力提供了支持。通过普通最小二乘法估计、岭回归和稳健回归对包含数据包络分析（DEA）效率得分的对数线性成本模型进行了评估，并将其作为分析框架。纳入简单的数量-复杂性指标、DEA指标、质量指标和医疗中心状态变量的简约模型具有卓越的预测能力。
