Huang Y G, McLaughlin C P
University of South Florida, College of Public Health, Tampa 33612-3899.
Health Serv Res. 1989 Jun;24(2):143-58.
This study applied data envelopment analysis (DEA) to the evaluation of rural primary health care programs, which are known to be very heterogeneous. DEA is a mathematical programming technique that optimizes the relative efficiency ratio of current inputs over current outputs for each decision-making unit (DMU). It produces a summary scalar efficiency ratio for each DMU and identifies the amount of inefficiency. The data came from the National Evaluation of Rural Primary Health Care Programs. Despite the demands of the software used for homogeneous units and nonzero values, the efficiency analysis was useful to the evaluation. It assessed multiple inputs and multiple outputs simultaneously, and identified directly those units that are performing efficiently or inefficiently when compared to specific peer programs. This then allowed us to compare this efficient-inefficient classification with other data, first, to verify the classification and, second, to assist with the evaluation. DEA can contribute to the evaluation of heterogeneous health programs, especially when used in conjunction with other methods of analysis.
本研究运用数据包络分析（DEA）对农村初级卫生保健项目进行评估，这些项目具有高度的异质性。DEA是一种数学规划技术，它能优化每个决策单元（DMU）当前投入与当前产出的相对效率比率。它为每个DMU生成一个汇总的标量效率比率，并确定无效率的程度。数据来自农村初级卫生保健项目的全国评估。尽管所使用的软件要求数据单元具有同质性且值不为零，但效率分析对评估仍很有用。它能同时评估多个投入和多个产出，并直接确定与特定同类项目相比表现高效或低效的那些单元。这使我们能够将这种高效 - 低效分类与其他数据进行比较，首先是验证分类，其次是辅助评估。DEA有助于对异质性卫生项目进行评估，特别是与其他分析方法结合使用时。
