Document Type: Research Paper
Group of Information Technology, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
PhD Research Scholar, Center of Excellence in Healthcare Systems Engineering, Tarbiat Modares University, Tehran 1411713116, Iran
Background and Objectives: Organ transplantation is an appropriate treatment for patients at the final stage of disease. The most important step in organ transplant is organ allocation. Decision making for organ allocation is a complex and multi-criteria problem. The demand for kidney is more than other organs. Donated kidneys in Iran are allocated by filtering the waiting list. This method is not optimal and efficient. Hence, the purpose of this study is developing a multi-media decision making model for kidney allocation based on a scoring method.
Methods: This study consists of two phases. The goal of the first phase is weighting the effective factors in kidney allocation. In this phase, the factors were extracted from the literature. Next, they were weighted using the Analytic Hierarchy Process (AHP) method. In the second phase, the patients on the waiting list were ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The main contribution of this study is developing an integrated kidney allocation model using AHP and TOPSIS methods. It is the first study that consists of both factors weighting and patients ranking phases.
Findings: Results show that "Zero Human Leukocyte Antigen (HLA) mismatches", "High Medical Urgency", and "Identical blood type between donor and recipient" to be the three most important factors for kidney allocation, respectively. "Panel Reactive Antibodies (PRA) <80%" is the least important.
Conclusions: The proposed model may be used to develop an organ allocation system in countries that do not have an allocation algorithm, or intend to improve their allocation systems. On the other hand, the proposed method can be applied to other organs with little modification.