A fuzzy stochastic slacks-based data envelopment analysis model with application to healthcare efficiency

Performance assessment can play an effective role in providing quality services in healthcare organizations. To develop and compete, hospitals need a performance evaluation system to measure the effectiveness and efficiency of their programs, processes, and workforce. However, hospital data are often uncertain, imprecise, or unknown. In this paper, a fuzzy stochastic data envelopment analysis (DEA) method based on the slacks-based measure of efficiency (SBM) is presented and employed to evaluate the performance of 11 hospitals in an urban setting. Due to the multiplicity of the initially identified criteria, an integrated algorithm based on Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) is used to determine the main and effective criteria. The result of the algorithm shows that the criterion “total inpatient visits” is the most important criterion in this evaluation. Finally, the proposed model is implemented based on different levels of significance, and the performance of each unit is determined in uncertain conditions.