Sensitivity analysis for efficiency security margin of medical sciences hospitals in Iran using data envelopment analysis

Subject Areas : International Journal of Data Envelopment Analysis

Fatemeh Komaki ¹ , Reza Fallahnejad ²

1 - Department of mathematics khoramabad branch, Islamic azad university, khoramabad, Iran. Postal code: 6817816645 , tel:[phone]
2 - Departeman of math,Islamic Azad university Khorram-Abad , Iran

Received: 2021-05-01 Accepted : 2021-06-22 Published : 2021-07-01

Keywords: Sensitivity analysis, Universities of Medical Sciences of Iran, Data Envelopment Analysis, Performance security margin,

Abstract :

Part of data envelopment analysis, is the analysis of the sensitivity of a set of efficient units to changes in input and output values. In general, the first issue that sensitivity analysis addresses is the sensitivity of the amount of performance to each of the factors affecting performance. Hospitals are known as the largest and most expensive operating units of the health care system and account for a high percentage of health sector resources. Therefore, performance evaluation in these units is very important. Therefore, in order to increase the efficiency and effective use of resources and inputs and reduce hospital costs, a sensitivity analysis algorithm is presented to determine the excess amount of inputs in inefficient hospitals. This algorithm also determines the security margin of the efficiency of efficient hospitals, in the sense that if the efficiency of efficient hospitals is threatened by improving the performance of inefficient hospitals, it will provide them with a security margin. For this purpose, using data envelopment analysis models, the efficiency of 15 hospitals of Iran University of Medical Sciences was evaluated, of which 6 were inefficient and 9 were efficient. Unlike the resources allocated to hospitals, there was a significant gap between the growth of available resources and the resources needed in this department, which was determined by the sensitivity analysis algorithm of excess amounts of inputs for example in Farshchian inefficient hospital. That hospital managers can achieve maximum efficiency by reducing inputs and better allocating resources