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运用数据包络分析评估退伍军人事务部医疗中心的管理效率。

Evaluating managerial efficiency of Veterans Administration medical centers using Data Envelopment Analysis.

作者信息

Sexton T R, Leiken A M, Nolan A H, Liss S, Hogan A, Silkman R H

机构信息

W. Averell Harriman School of Management and Policy, State University of New York, Stony Brook 11794.

出版信息

Med Care. 1989 Dec;27(12):1175-88. doi: 10.1097/00005650-198912000-00009.

Abstract

This study applied the methodology of Data Envelopment Analysis (DEA) to the set of VA medical centers to evaluate their relative managerial efficiencies. Each VAMC was viewed as a producer of multiple outputs and a consumer of multiple inputs. DEA uses linear programming to identify resources that were underutilized and services that were inefficiently produced. Managerial strategies based on the dual variables were constructed to indicate the manner in which inefficient VAMCs may be made efficient. The analysis showed that relative inefficiency existed in about one third of the VAMCs nationwide. Elimination of this inefficiency would save the VA over $300 million annually on personnel, equipment, drugs, and supplies, without reducing the level of services provided. A subsequent analysis of co-variance revealed that VAMCs affiliated with a university were generally less efficient than those without such an affiliation. A similar finding was obtained for larger VAMCs relative to smaller medical centers. In neither case, however, should these results be construed to imply that VAMCs should terminate their university affiliations or that VAMCs should be made smaller since factors other than relative efficiency are clearly as or more important in such decisions.

摘要

本研究将数据包络分析(DEA)方法应用于退伍军人事务部(VA)医疗中心,以评估其相对管理效率。每个VA医疗中心都被视为多种产出的生产者和多种投入的消费者。DEA使用线性规划来识别未充分利用的资源和生产效率低下的服务。基于对偶变量构建管理策略,以表明可使低效VA医疗中心变得高效的方式。分析表明,全国约三分之一的VA医疗中心存在相对低效的情况。消除这种低效每年可为VA节省超过3亿美元的人员、设备、药品和物资费用,同时不降低所提供服务的水平。随后的协方差分析表明,附属于大学的VA医疗中心通常比没有这种附属关系的医疗中心效率更低。相对于较小的医疗中心,较大的VA医疗中心也有类似的发现。然而,在这两种情况下,这些结果都不应被解释为意味着VA医疗中心应终止其大学附属关系,或者VA医疗中心应缩小规模,因为在这类决策中,除了相对效率之外,其他因素显然同样重要或更重要。

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