Applying Data Envelopment Analysis to Improve Performance of Emergency Departments in Iranian Hospital: A Case Study

One of the most important parts of the health system in each society is hospitals. It should not be forgotten that the emergency room of a hospital is the first point of entry for patients and their companions with the medical system, and one of the problems that often affect the performance of the emergency department is the length of time patients wait in the emergency room. This dissertation has been conducted with the aim of reducing the average waiting time of patients in the emergency department, improving the efficiency of nurses, and increasing the performance of the emergency department. The case study was “Razi Hospital” located in Ahwaz, Iran. It is a general hospital wich at present, with an area of 7,971 square meters, medical services including general surgery, orthopedics 1 and 2, internal medicine, infectious diseases, obstetrics, neonatology, CCU, ICU, emergency department, operating room, physiotherapy, radiology, laboratory, dialysis, echocardiography and specialized clinics visit patients. The data were prepared from the emergency department of the hospital for 12 months in 2018, 2019, and 2020. Data analysis obtained in this study is performed using PIM-DEA software based on the CCR model as a method that is one of the techniques of data envelopment analysis. According to the results, the most important priority is the number of patients with CPR procedures. With this in mind, we can focus on accepting patients with CPR in order to increase the level of emergency function. The next most important factor is the average time the patient leaves the hospital. According to the hospital experts, the time of the patient's discharge from the hospital is a very important indicator, because according to the capacity of the hospital and the number of staff, the lower the average time of the patient's discharge from the emergency room, the better iv the emergency performance. Keywords: Cardiopulmonary Resuscitation as CPR, CCR Model, Data Envelopment Analysis as DEA, Emergency Department