Performance measurement in the health care sector: A leader-follower network DEA model based on double frontier analysis

Abstract

Efficiency evaluation for laboratories as one of the most significant areas of healthcare plays a key role in enhancing the quality of laboratory management. In this paper, a three-stage structure with optimal desirable and undesirable inputs and outputs was taken into consideration. This network comprises a leader and two followers. The suggested model simulates the internal structure of a diagnostic lab (pre-test, test, and post-test). The evaluation criteria are determined using the Fuzzy Delphi technique. Due to the environmental, economic, and social impacts of healthcare systems, the significance of sustainability criteria is obvious in the case study indicators. The non-cooperative method-based multiplicative Data Envelopment Analysis (DEA) technique is used to evaluate the efficiency of the network from both optimistic and pessimistic views. Moreover, a heuristic technique is employed to convert non-linear models into linear ones. Finally, a k-means method is proposed to cluster Decision-Making Units (DMUs) into several groups with similar characteristics based on double-frontier standpoint.