Performance evaluation of nonhomogeneous hospitals: the case of Hong Kong hospitals
Performance evaluation of nonhomogeneous hospitals: the case of Hong Kong hospitals
复制标题
非同质医院的绩效评估：以香港医院为例
DOI：
10.1007/s10729-018-9433-y
复制
发表时间：
2019-06-01
影响因子：
3.6
通讯作者：
Morton, Alec
中科院分区：
文献类型：
--
作者：
Li, Yongjun;Lei, Xiyang;Morton, Alec
在全球范围内，医院面临着越来越大的提高效率的压力。效率分析工具可以在使政策制定者了解哪些部门效率较低以及原因方面发挥作用。许多研究人员使用数据包络分析（DEA）作为效率分析工具来研究医院的效率。然而，在现有的基于DEA的绩效评估文献中，规模报酬不变（CRS）或规模报酬可变（VRS）DEA模型的一个标准假设是决策单元（DMU）使用相似的投入组合来生产相似的产出集合。事实上，具有不同主要目标的医院提供不同的服务并产生不同的产出。也就是说，医院是非同质的，DEA模型的标准假设不适用于非同质医院的绩效评估。本文在绩效评估中考虑医院之间的非同质性，并以香港的医院作为案例研究。基于VRS假设对Cook等人（2013）[1]的研究进行了扩展，以评估非同质医院的效率，因为医院的投入差异很大。遵循Cook等人（2013）[1]的理念，医院被分为同质组，每个医院的生产过程被分为子单元。医院的绩效是基于子单元来衡量的。所提出的方法可用于衡量其他表现出规模报酬可变的非同质实体的绩效。
Throughout the world, hospitals are under increasing pressure to become more efficient. Efficiency analysis tools can play a role in giving policymakers insight into which units are less efficient and why. Many researchers have studied efficiencies of hospitals using data envelopment analysis (DEA) as an efficiency analysis tool. However, in the existing literature on DEA-based performance evaluation, a standard assumption of the constant returns to scale (CRS) or the variable returns to scale (VRS) DEA models is that decision-making units (DMUs) use a similar mix of inputs to produce a similar set of outputs. In fact, hospitals with different primary goals supply different services and provide different outputs. That is, hospitals are nonhomogeneous and the standard assumption of the DEA model is not applicable to the performance evaluation of nonhomogeneous hospitals. This paper considers the nonhomogeneity among hospitals in the performance evaluation and takes hospitals in Hong Kong as a case study. An extension of Cook et al. (2013) [1] based on the VRS assumption is developed to evaluated nonhomogeneous hospitals’ efficiencies since inputs of hospitals vary greatly. Following the philosophy of Cook et al. (2013) [1], hospitals are divided into homogeneous groups and the product process of each hospital is divided into subunits. The performance of hospitals is measured on the basis of subunits. The proposed approach can be applied to measure the performance of other nonhomogeneous entities that exhibit variable return to scale.