Advancement in medical knowledge has developed the trust of end-stage organ failure patients in organ transplantation. The success rate of organ transplantation has significantly intensified the confidence that increased vital organ demands such as kidneys (1). According to the US Organ Procurement and Transplantation Network (OPTN), 39,000 organs were transplanted in 2020. Still, 106,708 were waiting for an organ (2). The organ shortage kills three Americans every day, and up to one in six of those waiting for a heart, liver, or lung transplant die or are too ill to be given one. As the number of patients is added day-by-day to the waiting list for organ transplantation, the organ allocation procedure has become challenging. Different organ allocation policies are present but still, it is very difficult to find the most appropriate recipient. For kidney allocation, policies try to balance between utility (kidneys should be used as efficiently as possible) and equity (wait-listed patients have an equal chance of receiving kidneys) (3). To balance the utility and equity, substantial debates have raised many questions such as “Should we discriminate between patients while considering their medical conditions?” (4) but no one reported a definite settlement (5).
Although various organizations are managing organ transplantation in different countries such as Euro-transplant in Europe, United Network for Organ Sharing (UNOS) in the US, (6), and Israel National Transplant Center (INTC) in Israel (7). In leading countries, a point scoring system is used to allocate the kidneys. The patient secures maximum scores, a kidney would be allocated to him/her. Moreover, researchers have tried to improve the organ allocation system to make it transparent and effective. In 1990, David and Yechiali optimized the organ allocation model with different criteria to allocate various organs to recipients (8). In 2001, Yuan et al. introduced a fuzzy logic-based kidney allocation system to deal with complexity and ambiguity near to expert opinion (9). Similarly, in 2005, Gundogar et al. established a kidney allocation system, a fuzzy organ allocation system (FORAS), and claimed it was better compared to other allocation systems (10). Later, in 2008, a utility-based system was developed by Baskin & Nyberg to balance the demand and supply of kidney transplantation (11). For liver allocation, a rule-based decision-making system was proposed by Cruz-Ramirez in 2013 (12). Correspondingly, linear regression of score weights (13), fuzzy lung allocation system (FLAS) (14), Data Envelopment Analysis (DEA) (15), Delphi method, Analytic Hierarchy Process (AHP) (16–18), and Mamdani Style Fuzzy Inference System (MSFIS) (19) were developed and practiced for organ allocation. Although, AHP and Delphi have been extensively used for developing the organ allocation system. Recently, Taherkhani et al. used the Intuitionistic Fuzzy AHP method for weighting kidney allocation criteria to remove the uncertainty in decision making and improve the organ allocation system (6).
The patient's interests are the primary concern of all clinicians. Transplantation presents a unique challenge for clinicians as they tend to care for many patients who could benefit from a similar donated organ. Donated organs must be deliberated as a national resource and all the listed patients have equal opportunity to receive the donated organ. Therefore, donated organ allocation, selection, and rights of competing recipients need to be clearly defined, focused, and evidence-based that merely benefitting the patient (20). Alternatively, in the case of heart and liver, the clinician’s decision or center’s policies will be preferred to allocate the organ to the most appropriate recipient. Some patients are listed as super-urgent, if they do not get the urgent transplant, may lead to death. So that patients receive the available donated organ with clear justification. Further, cold ischaemic time (CIT) - the interval between the cooling and implantation of an organ- is considered in the organ allocation process. Organ with short CIT allocated to patients nearly available or present in that center (20).
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