Showing 5 results for Efficiency
E Ghasemi, M Barooni, R Dehnavieh, M Jafari Sirizi , Mh Mehrolhassani,
Volume 12, Issue 0 (3-2017)
Abstract
Background and Objectives: Health insurance would guarantee people security against disease and health problems. Given the key role of health insurance in achieving the goals of justice and reducing the out-of-pocket payment, this study aimed to evaluate the performance of Iran health insurance using the DEA model in 2014.
Methods: This was a cross sectional study. The study population included all Iran health insurance organizations. DEA input and output criteria were selected by targeted library and documentary review and the data were collected accordingly. The determinants of efficiency were evaluated using liner regression.
Results: The mean technical, management, and scale efficiency of Iran health insurance head offices was 0.593, 0.761, and 0.721, respectively. Considering the findings, the capacity of efficiency promotion at these head offices was approximately 41%. Regarding technical efficiency, 5 head offices had the maximum efficiency (1), 7 head offices had efficiency between 0.5 and 1, and 19 head offices had efficiency less than 0.5. In addition, the variables of population and total number of institutions had a significant impact on efficiency.
Conclusion: Based on defined variables, input oriented AP-DEA model was appropriate. The results showed a great capacity for increasing technical efficiency in the Iranian health insurance organizations which could be increased by benchmarking efficient and reference organizations and also adjusting their input. For this purpose, downsizing and agility of the Iranian health insurance organizations based on the e-government clause are proposed for administrative system reform.
F Esmaili, Mh Mehrolhassani, M Barooni, R Goudarzi ,
Volume 12, Issue 0 (3-2017)
Abstract
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.
R Goudarzi, Mh Mehrolhassani, R Dehnavieh, A Darvishi,
Volume 12, Issue 0 (3-2017)
Abstract
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.
Mh Mehrolhassani, R Goudarzi, V Yazdi Feyzabadi , Ss Pourhosseini, A Darvishi,
Volume 14, Issue 0 (1-2019)
Abstract
Background and Objectives: Improving the efficiency and productivity of the higher education, especially in the field of research on health sciences, is one of the characteristics of sustainable development in today's societies. This study aimed to measure the efficiency and productivity of Iran's Medical Sciences Universities (MSU) in the research function.
Methods: In a descriptive study, the research function of fourty five MSUs in Iran was evaluated using data envelopment analysis (DEA) method and Malmquist index in 2010, 2013, and 2016 years. Measurement of both efficiency and Malmquist index was developed and modeled based on the assumption of variable returns to scale (VRS) and output-oriented. Also, the ranking of efficient units was done using Anderson-Patterson's model.
Results: The mean research efficiency was estimated to be 0.86. Findings of Malmquist index showed that between 2010 and 2013, there was a 6% growth in the productivity; while the performance of universities had a 12% drop in research function from 2013 to 2016. Also, the average total productivity during two periods is 0.96, indicating 4% reduction in research efficiency which technology efficiency growth has dropped by 8% and other components of total productivity had a positive growth.
Conclusion: The results of the study showed that universities do not work efficiently and average productivity has been decreasing which was mainly due to a decline in the efficiency of technology, which despite the development of technology in recent years could be the result of the lack of effective use of it.
Mh Mehrolhassani, R Goudarzi, V Yazdi Feyzabadi, Ss Pourhosseini, A Darvishi,
Volume 14, Issue 0 (1-2019)
Abstract
Background and Objectives: The higher education system plays an important role in the socio-economic development of the country due to its mission in training the required human resources. Therefore, performance evaluation of different sectors of higher education is of great importance. The present study was conducted to evaluate the educational efficiency and productivity changes of Iranian medical sciences universities.
Methods: This descriptive study was conducted in 2011, 2014, and 2017 to evaluating the performance of 43 Iranian medical universities using Data Envelopment Analysis and output oriented approach. In addition, productivity changes were measured using the Malmquist index. For this purpose, Deap 2.1 software was used. The Anderson Patterson Model and EMS software were also used to rate the units accurately.
Results: The average educational efficiency of medical universities was 0.97 in the study years. The average total productivity based on the Malmquist Index was 1.05, and educational productivity of the universities showed an average growth of 5% over the study years. This growth was 1% from 2011 to 2014 and 10% from 2011 to 2017.
Conclusion: The results of the study showed the acceptable efficiency of the education sector of Iranian medical sciences universities. Moreover, a positive increasing trend was observed in the productivity of the education sector during the study years. Further research using quality and quantity measures are necessary to assess the educational performance of medical universities more accurately.
