An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach

Given the perennial imbalance and chronic scarcity between the demand for and supply of available organs, organ allocation is one of the most critical decisions in the management of organ transplantation networks. Organ allocation systems undergo rapid revisions for the sake of improved outcomes in terms of both equity and medical efficiency. This paper presents a Data Envelopment Analysis (DEA)-based model to evaluate the efficiency of possible patient-organ pairs for kidney allocation in order to enhance the fitness of organ allocation under inherent uncertainty in such problem. Eligible patient-kidney pairs are regarded as decision making units (DMUs) in a Credibility-based Fuzzy Common Weights DEA (CFCWDEA) approach and are ranked based on efficiency scores. Using a common set of weights for all DMUs ensures a high degree of fairness in the assessment and ranking of DMUs. The proposed model is also the first allocation method capable of coping with the vague and intervallic medical and nonmedical allocation factors by the aid of fuzzy programming. Verification and validation of the proposed approach are performed in two steps using a real case study from the Iranian kidney allocation system. First, the superiority of the proposed deterministic model in enhancing allocation outcomes is demonstrated and analyzed. Second, the applicability of the proposed fuzzy DEA method is demonstrated using a series of data realizations for different credibility levels.