چكيده به لاتين
One of the most vital subsets of the health system is organ transplantation, which in many cases is the only treatment for incurable diseases. In this study, the focus is on kidney transplantation. One of the most important and practical issues in this area is organ allocation and finding the right recipient, taking into account the relevant limitations. One of the managerial necessities of the Ministry of Health of Iran is to reduce the mortality rate of patients due to the long waiting time of patients. In addition, a case that has not been considered in Iran so far, but has recently been considered by the Ministry of Health of Iran, is the issue of the degree of HLA compliance or tissue compatibility between the patient and the donor, according to which The higher the level of compatibility, the higher the quality of the link. However, if we are looking for a high quality transplant, due to the high level of demand compared to the supply in this area, it will increase the waiting time of patients and consequently increase the mortality rate of patients.
Therefore, in this study, we have presented a multi-objective model to balance high quality transplantation by considering the degree of tissue compatibility and reducing patient waiting time. There is also a low limit for HLA between patient and donor to ensure transplant quality. Patients are divided into 3 categories: normal, sensitive and emergency. The condition of patients is determined using the scoring system that is currently used in Iran. The proposed model is multi-period and the health status of patients can be changed in each period and it is possible to change the patient status from normal to sensitive and from sensitive to emergency. In addition, the score of each patient in each period is recalculated. An example model is provided for validation. Since our case study was in Tehran and due to unfavorable conditions for the outbreak of Covid 19 disease, we could not access the real data, we tried to generate the data in accordance with the real environment by EXCLE at random. Finally, we have solved the model by ℇ-constraint method with the help of GAMS WIN64 24.1.3 software in a personal system with Windows 10, and we have also presented the optimal results obtained. Then, sensitivity analysis method was used to analyze some of the model parameters.
