Peykani Pejman, Memar-Masjed Elaheh, Arabjazi Nasim, Mirmozaffari Mirpouya
School of Industrial Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran.
Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran.
Healthcare (Basel). 2022 May 9;10(5):876. doi: 10.3390/healthcare10050876.
The goal of the current research is to propose the credibility-based fuzzy window data envelopment analysis (CFWDEA) approach as a novel method for the dynamic performance evaluation of hospitals during different periods under data ambiguity and linguistic variables. To reach this goal, a data envelopment analysis (DEA) method, a window analysis technique, a possibilistic programming approach, credibility theory, and chance-constrained programming (CCP) are employed. In addition, the applicability and efficacy of the proposed CFWDEA approach are illustrated utilizing a real data set to evaluate the performance of hospitals in the USA. It should be explained that three inputs including the number of beds, labor-related expenses, patient care supplies, and other expenses as well as three outputs including the number of outpatient department visits, the number of inpatient department admissions, and overall patient satisfaction level, are considered for the dynamic performance appraisal of hospitals. The experimental results show the usefulness of the CFWDEA method for the evaluation and ranking of hospitals in the presence of fuzzy data, linguistic variables, and epistemic uncertainty.
当前研究的目标是提出基于可信度的模糊窗口数据包络分析（CFWDEA）方法，作为一种在数据模糊性和语言变量情况下对医院不同时期动态绩效进行评估的新方法。为实现这一目标，采用了数据包络分析（DEA）方法、窗口分析技术、可能性规划方法、可信度理论和机会约束规划（CCP）。此外，利用一个真实数据集说明了所提出的CFWDEA方法的适用性和有效性，以评估美国医院的绩效。需要说明的是，在医院动态绩效评估中考虑了三个输入，包括床位数、与劳动力相关的费用、患者护理用品和其他费用，以及三个输出，包括门诊就诊次数、住院部入院人数和患者总体满意度水平。实验结果表明，CFWDEA方法在存在模糊数据、语言变量和认知不确定性的情况下，对医院评估和排名是有用的。
