چكيده به لاتين
One of the most vital subsets of healthcare systems is organ transplantation, which has become a popular and successful cure for many fatal diseases (e.g., end stage liver diseases and end stage renal diseases). Organs are considered as highly perishable products, which verity of each has specific perish time. One of the key problems in this field is matching - defined as finding the best recipient for a donated organ- is very crucial in healthcare management sciences.
In this research, we propose a fuzzy multi-period organ allocation model which considers different health levels of patient in each period. The present study proposes a two stage patients’ ranking and organ allocation model that takes into account not only medical criteria but also nonmedical ones (e.g., transportation time, transportation cost, etc.) in ranking patients. In the first stage, survival and medical urgency need of patients are estimated by the use of Cox Proportional Hazard method. In the second phase, multi-objective mathematical programming model is presented that makes a tradeoff between efficiency and equity. The proposed method is able to cope with the inherent uncertainties in medical and logistical parameters of the allocation problem by the aid of fuzzy programming. Subsequently, to solve the proposed possibilistic optimization model, a new hybrid novel interactive fuzzy solution approach based on priority preemptive goal programming is developed to find a preferred compromise solution.
In order to verify the efficiency and applicability of the presented model, some numerical examples are taken from a real case study in Iran’s organ transplantation network. Based on obtained results, the proposed method outperforms the current IRNOPT’s allocation policy in medical and nonmedical allocation criteria.
Keywords: Organ allocation, Survival Analysis, efficiency, equity, Possibilistic programming approach, Fuzzy goal programming
