Clinical decision supports for brain-dead kidney allocation: a review study of requirements, challenges, and solutions

With the change in the epidemiology of diseases, chronic kidney disease has shown a significant increase worldwide. Kidney transplantation is the optimal treatment option to improve patient quality of life. The main challenge in benefiting from a brain-dead patient's kidney is the selection of a right recipient in limited time. The purpose of this study was to review the requirements for designing and implementing clinical decision support systems for allocating brain-dead kidneys and the challenges facing them.

This scoping review was conducted by searching Scopus, PubMed, and Google scholar to find full-text English articles published until the end of 2021. The articles were analyzed based on the objectives of the study, the factors used in decision-making for allocation, the algorithms used in the decision-making process, and their outcome evaluations.

Two categories of medical (including the quality of the donated kidney) and equity/fairness factors were used in most allocation algorithms. However, the number of factors, the method, and the order of their application were different in different studies. Studies have reported different challenges but a positive impact using decision support systems.

One of the main challenges in the proper management of kidney transplants from brain-dead donors is to have local, agreed-upon protocols and algorithms regarding the methods, order, and weight of each of the medical and equity factors in the proposed protocol. Algorithms based on scoring have mostly been favored. Therefore, the probability of using a decision support system on this base seems to be higher.