Iranian Journal of

Background and Objectives: Productivity and efficiency are the most important and the most common mechanisms of evaluation and measurement of the performance of an enterprise including the Social Security Organization. In the past decades, performance evaluation of various economic sectors has been attractive to researchers in different disciplines. Thus, the aim of this study was to measure the efficiency of the direct treatment section of treatment management units of Social Security Organization by data envelopment analysis method. 

Methods: This descriptive- analytic study was conducted to measure the efficiency of the direct treatment section of treatment management units of Social Security Organization through the data envelopment analysis (DEA) method in 2014. Data and relevant statistics were collected from the Statistical Center of Social Security Organization. The Deap2.1 software was used to calculate the efficiency and the EMS software was used to calculate the super efficiency. Then, the hypotheses of the research were studied using the Stata software.

Results: The average technical efficiency, managerial efficiency, and scale efficiency in 2014 was 0.924, 0.992, and 0.932, respectively. Twelve decision making units (DMUs) had the maximum technical efficiency (1), 16 DMUs had technical efficiency between 0.8 and 1, and 3 units had technical efficiency less than 0.8.

Conclusion: This study introduces a functional pattern to managers of Social Security Organization that enables them to have more accurate planning for the development and saving of resources.

Background and Objectives: Efficiency measurement can be used for all decision-makers and planners for useful resource allocation. Social Security Organization as a health service provider, provides part of health care services in indirect sector. This study aimed to assess the performance of provincial units of Social Security Organization in the indirect health services sector.

Methods: This descriptive analytical study was conducted based on the available data of Social Security Organization in 2014. To assess efficiency and super-efficiency, the DEA-VRS and Anderson-Peterson rating model were used, respectively. Factors affecting the efficiency was evaluated using multivariate regression.

Results: The primary efficacy analysis showed that 61% of the provincial units of Social Security had maximum efficiency. Average efficiency was 0.94. After super-efficiency analysis, it was found that Markazi and Kerman provincial units were the most efficient and the most inefficient units, respectively. Additionally, none of the variables had a significant impact on the efficiency.

Conclusion: Evaluation of the general performance of provincial units reflected the good state of technical efficiency in the indirect health service sector. On the other hand, the scale efficiency of inefficient units compared with managerial efficiency had a higher share of inefficiency. Optimum performance can be achieved through modification of managerial practices for optimal utilization of resources and factors.