Modeling the allocation and transfer of emergency patients according to the type of disease

Document Type : Research Paper

Authors

1 Department of Industrial Engineering, Bonab branch, Islamic Azad University, Bonab, Iran

2 Department of Industrial Engineering, Bonab Branch, Islamic Azad University, Bonab, Iran

3 Department of Industrial Engineering, Seraj university,Tabriz , Iran

4 Department of Engineering Management ,central branch of Payam-e-nour university, Tehran ,Iran

Abstract

Background and Objectives: The increase in the number of patients in hospitals and the long wait due to overcrowding are some of the main concerns in health system research. Transferring patients to emergency departments is one way to reduce the congestion of the emergency department.
Methods: This study deals with the allocation of patients in the emergency department of hospitals, according to the segregation of the type of disease, which reduces the congestion by transferring patients to other hospitals, if necessary, and minimizes the total cost of the system. In this paper, a linear model is presented for patient allocation and the model is solved using GAMS software.
Results: Patients admitted to the hospital are divided into different types in terms of the type of disease. To reduce the cost of waiting and reduce the waiting time for patients, patients who cannot be treated at the hospital due to lack of expertise in their illness are transferred to other hospitals. All costs, including the cost of increasing the patient's capacity, the cost of admitting the patient, the cost of transporting patients, the cost of waiting fines, the cost of unmet demand and the cost of overtime are calculated in the mathematical model.
Conclusion: by transferring patients, the number of expected patients and the number of patients who are considered as unmet needs can be reduced. Because with the increase in the number of patients waiting and patients who have not been considered as an unmet demand, the mortality rate, medical errors and patient dissatisfaction will increase and irreparable risks will arise, especially for patients with acute problems.  

Keywords