Performance Measurement in the Health Care Sector: a Leader-Follower Network DEA Model based on Double Frontier Analysis

Abstract

Measuring the performance of laboratories as one of the most significant areas of healthcare plays a key role in the quality of laboratories management. In this paper, we consider a three-stage network comprised of a leader and two followers in respect to the additional desirable and undesirable inputs and outputs. The suggested model simulates the internal structure of a diagnostic lab (the pre-test, the test and the post-test). The criteria for evaluation are achieved by using the Fuzzy Delphi technique. Due to the social, economic and environmental impacts of health care systems, the significance of sustainability criteria is obvious in the case study indicators. We utilize the non-cooperative approach multiplicative model to measure the efficiency of the overall system and the performances of decision-making units (DMUs) from both the optimistic and pessimistic views. The non-cooperative models from these view cannot be converted into linear models. Therefore, a heuristic method is suggested to convert the nonlinear models into linear models. Finally, after obtaining the efficiencies based on the double-frontier view, the DMUs are ranked and classified into three clusters by the k-means algorithm.