Factors Effective on Technical Efficiency and Ranking of Efficient Units in Social Security Hospitals

Document Type : Original Article

Authors
Hamid Sepehrdoust 1
Elham Rajabi 2
1 Assistant Professor, Economics, Boo Ali Sina University, Hamedan, Iran.
2 Economics, School of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran
Abstract
Introduction: Iran's social security organization provides hospital services through direct treatment
system (hospitals owned by the organization) and indirect treatment system (purchasing of hospital
services and other health care services from other providers). The current research aims to assess technical
performance and determine the relationship between activity size and efficiency level of social security
hospitals in Iran.
Methods: This descriptive-analytical study was performed on 65 active social security hospitals that were
selected for Data Envelopment Analysis during the period of 2007–2009. In order to measure the technical
efficiency of hospitals the input-output model and data envelopment analysis (DEA) were used.
Furthermore, statistical tests were used to study the significance of the effect of activity scale on the
efficiency level of the hospitals.
Results: About 28.5% of small scale social security hospitals and 16.2% of large scale social security
hospitals were found to be working with full efficiency. Statistical analysis showed a significant difference
between the mean efficiency of small scale and large scale hospitals (Sig. = 0.029).
Conclusion: It is expected that, through improvement of managerial techniques in efficient input use, the
managerial inefficiency level be reduced by 6%, and a 5% increment be achieved in the output services
scale of hospitals through the efficient use of existing resources.

Keywords

1. Abdoli Gh. Determinants of treatment expenditures in social security hospitals. J Social Welfare 2008; 7(27):
235-52. [In Persian].
2. Dyson RG. Performance measurement and data envelopment analysis - Ranking are rank! OR Insight 2001;
13(4): 3-8.
3. Kirigia JM, Emrouznejad A, Sambo LG, Munguti N, Liambila W. Using data envelopment analysis to measure
the technical efficiency of public health centers in Kenya. J Med Syst 2004; 28(2): 155-66.
4. Akazili J, Adjuik M, Jehu-Appiah C, Zere E. Using data envelopment analysis to measure the extent of technical
efficiency of public health centres in Ghana. BMC Int Health Hum Rights 2008; 8: 11.                                                                     5. Ghaderi H, Goudarzi G, Gohari M. Determination technical efficiency of hospitals affiliated with Iran University
of Medical Science by Data Envelopment Analysis (2000 - 2004). J Health Adm 2007; 9(26): 39-44.
6. Social Security Organization, Deputy of Economic and Programming. Hospitals database for the years 2008-2010
[Online]. 2011; Available from: URL: http://www.tamin.ir/ [In Persian].
7. Cullinane K, Wang T. The efficiency analysis of container port production using DEA panel data approaches. OR
Spectrum 2010; 32(3): 717-38.
8. Mehregan MR, Arouneh M. Measurement of organization's performance; using DEA. Tehran, Iran: University of
Tehran Press, School of Management; 2004. [In Persian].
9. Azar A, Motameni AR. Productivity Measuring in Companies by Date Envelopment Analysis (DEA). Daneshvar
Raftar 2004; 11(8): 41-54. [In Persian].
10. Emamimeibodi A. Principles of applied efficiency and productivity measurement. Tehran, Iran: Institute of Trade
Studies and Research; 2005. [In Persian].
11. Social Security Organization, Treatment Section. Statistics of human resource working in the Central Treatment
Quarters of the Organization [Online]. 2009; Available from: URL: http://www.tamin.ir/[In Persian].
Health Information Management
Volume 9, Issue 6
Winter 2012
Pages 887-894