Volume 10, Issue 3 (26 2013)
sjsph 2013, 10(3): 91-99 |
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Sepehrdust H, Rajabi E. Technical Efficiency Measurement of Social Security Hospitals. sjsph 2013; 10 (3) :91-99
URL: http://sjsph.tums.ac.ir/article-1-16-en.html
URL: http://sjsph.tums.ac.ir/article-1-16-en.html
1- , hamidbasu1340@gmail.com
Abstract: (8685 Views)
Background and Aim: Hospitals as one of the major institutions providing health care services within the health sector utilize a high percentage of the sector's key resources to respond to the needs of consumers. The aim of the present study was to identify factors affecting technical, scale and management efficiency of the Social Security Organization (SSO) hospitals during the period 2007-2009 and find ways to improve the efficiency of inefficient hospitals.
Materials and Methods: A total of 65 SSO hospitals active during the period 2007-2009 were included in the study. Data envelopment analysis was used assuming constant return to scale of production (CRS). To distinguish between management and scale efficiency of hospital units, the study used input-oriented model (BCC) assuming variable return to scale (VRS).
Results: The findings showed that small hospitals with less than, and large hospitals with more than, 100 active beds have 11% and 8.8% surplus inputs, respectively, the surplus inputs being medical and nursing staff, other personnel, as well as active beds for hospital services. In addition, the impact factors of medical staff, nursing staff, other personnel, and active beds were 24%, 9.8%, 11.7% and 16.8% for small hospitals' efficiency and 25.7%, 18%, 21.7% and 30.7% for large hospitals' efficiency, respectively..
Conclusion: Considering the average scale and management scores derived for efficiency measurement, it is recommended that the Social Security Organization hospitals reduce their surplus costs and increase their output products and services to achieve the optimum level of efficiency.
Materials and Methods: A total of 65 SSO hospitals active during the period 2007-2009 were included in the study. Data envelopment analysis was used assuming constant return to scale of production (CRS). To distinguish between management and scale efficiency of hospital units, the study used input-oriented model (BCC) assuming variable return to scale (VRS).
Results: The findings showed that small hospitals with less than, and large hospitals with more than, 100 active beds have 11% and 8.8% surplus inputs, respectively, the surplus inputs being medical and nursing staff, other personnel, as well as active beds for hospital services. In addition, the impact factors of medical staff, nursing staff, other personnel, and active beds were 24%, 9.8%, 11.7% and 16.8% for small hospitals' efficiency and 25.7%, 18%, 21.7% and 30.7% for large hospitals' efficiency, respectively..
Conclusion: Considering the average scale and management scores derived for efficiency measurement, it is recommended that the Social Security Organization hospitals reduce their surplus costs and increase their output products and services to achieve the optimum level of efficiency.
Keywords: Hospital, Social Security, Data Envelopment Analysis, Technical Efficiency, Scale Efficiency
Type of Study: Research |
Subject:
General
Received: 2011/05/16 | Accepted: 2012/09/8 | Published: 2013/08/8
Received: 2011/05/16 | Accepted: 2012/09/8 | Published: 2013/08/8
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