Application of data envelopment analysis in optimal allocation of military health resources
- VernacularTitle:数据包络分析在部队卫生资源优化配置中的应用
- Author:
Peng SHI
- Publication Type:Journal Article
- Keywords:
data envelopment analysis;
health resources;
resource allocation;
military hygiene
- From:
Academic Journal of Second Military Medical University
2000;0(07):-
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the application of data envelopment analysis in optimal allocation of military health resources.Methods: The relative technical efficiency of 52 military health service units(MHSUs) was assessed by C~(2)GS~(2) model,a variable-return to scale,input oriented data envelopment analysis(DEA) method.MHSUs were classified with hierarchical clustering analysis.The confounding factors(geographic factor and arms of service) were analyzed using Cochran-Mantel-Haenszel ?~(2) test and the output of health service was analyzed using Kruskal-Wallis H test;then the quantity of health resources of different types of MHSUs was compared using Kruskal-Wallis H test and the structure of the resources was analyzed with ratios of different items.Results: Eighteen of the 52 MHSUs were technical efficient and the median score was 0.84.The relative technical efficiencies of 52 MHSUs were clustered into 4 types: type A,type B,type C and type D,referring to the best performance,average performance,inferior performance and the worst performance,respectively.The quantity of type D MHSUs was higher than those of other types of MHSUs and the structure of type D MHSUs was unreasonable compared with other types of MHSUs.The quantity and structure of type D MHSUs could be adjusted according to those of the type A or type B MHSUs.Conclusion: Combined with other statistical methods,DEA can be used to evaluate,classify the relative technical efficiency and analyze the resource allocation of different types of decision making units(DMUs).The quantity and structure of health resource with inferior relative technical efficiency DMUs can be adjusted to optimize the allocation of health resources.
