Background: Hospital indicators are among the most important factors in hospital performance. The aim of this study was to measure the performance of hospitals covered by Iran University of Medical Sciences and to compare them with the national indicators. Methods: In the present cross-sectional descriptive study, performance indicators of all hospitals covered by Iran University of Medical Sciences were compared descriptively in 2018-2019. Data were collected from the Medical Record of treatment deputy of Iran University of Medical Sciences. The collected information was analyzed using descriptive tools, Excel software, and the Ministry of Health and Medical Education standard index tables. Results: The average bed occupancy index, average hospital stay index, and patient registration ratio per bed were 69.17, 4.30, and 75.18 in the hospitals covered by Iran University of Medical Sciences in 2018-2019, respectively. These rates show average, undesirable, and desirable status by national standards, respectively. Conclusion: Given that the average length of stay indicator was at an inappropriate level in this study, hospital authorities are recommended to take the necessary measures to identify the reasons and improve the hospital performance in this regard.

Background: The optimal management of hospitals as the most important centers for providing health services has always been the focus of decision makers and policymakers. The present study aimed to evaluate the technical efficiency of hospitals affiliated to Ardebil University of Medical Sciences using Artificial Neural Network (ANN) method. Methods: The present descriptive, applied, and cross-sectional study was conducted in 2017. The study population consisted of 8 educational and therapeutic centers affiliated to Ardabil University of Medical Sciences and Health Services. Census sampling method was applied to select the participants and researcher-made checklists were used to collect the data. The artificial neural network method was also used to investigate the study objectives. The applied network was a multi-layer prospectron with a Levenberg Marquardt optimization function, a sigmoid tangent transfer function in the middle layer, and a linear function in the output layer. For processing and preparing data, Excel spreadsheet was used and Matlab software were used for analyzing and designing the network. Results: The results showed that the average technical efficiency of the studied hospitals was 0.75. Ardabil Bou Ali, Khalkhal Imam Khomeini, and Meshkinshahr Valiasr hospitals had the highest technical efficiency (1.00). With regard to the hospital bed occupancy rate, Germi Velayat hospital had the lowest efficiency rate (0.75). Furthermore, Parsabad Imam Khomeini hospital had the lowest efficiency in the number of discharged healthy patients (0.69) in 2017. Finally, the improvement space of each variable was calculated to achieve the total technical efficiency. Conclusion: According to the results, one of the factors that decreases  the technical efficiency of the educational centers is the low rate of hospital beds' utilization and occupancy rate. In other words, lack of full-capacity operation by the hospital centers and the low rates of active hospital bed imposed costs and consequently reduced the hospitals' performance.