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Ansari Samani H, Khabbazi Khanaghah M. Health System Efficiency in Iran and Its Influencing Factors. JCHR 2024; 13 (1) :221-227
URL: http://jhr.ssu.ac.ir/article-1-1059-en.html
URL: http://jhr.ssu.ac.ir/article-1-1059-en.html
1- Department of Economics - Faculty of Economics, Management and Accounting - Yazd University - Yazd - Iran , Ha.ansarisa@gmail.com
2- Department of Economics - Faculty of Economics, Management and Accounting - Yazd University - Yazd - Iran
2- Department of Economics - Faculty of Economics, Management and Accounting - Yazd University - Yazd - Iran
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References
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2. Gómez-Gallego JC, Gómez-Gallego M, García-García JF, et al, editors. Evaluation of the efficiency of European health systems using fuzzy data envelopment analysis. Healthcare; 2021: MDPI.
3. Lupu D, Tiganasu R. COVID-19 and the efficiency of health systems in Europe. Health Economics Review. 2022; 12(1): 14.
4. Oliaeimanesh A, Takian A, Mouhamadi E. Assessing the health system efficiency in the Islamic Republic of Iran. 1, editor. tehran: sharif publisher; 2021. [Persian]
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7. Gong G, Chen Y, Gao H, et al. Has the efficiency of China’s healthcare system improved after healthcare reform? A network data envelopment analysis and tobit regression approach. International journal of environmental research and public health. 2019; 16(23): 4847.
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| Health System Efficiency in Iran and Its Influencing Factors |
Department of Economics, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran.
| ARTICLE INFO | ABSTRACT | |
| Original Article Received: 20 Jun 2024 Accepted: 08 Oct 2024 |
Background: Given the importance of public health, evaluating the performance of the health system and striving to address its shortcomings is a concern for policymakers and health officials. The aim of this study is to examine the health system efficiency in Iran and investigate the impact of economic variables on the health system efficiency. Methods: In this study, the Stochastic Frontier Analysis (SFA) method was used to evaluate the health system efficiency in Iran, using data from Iranian provinces in 2016. The Stata software was used to evaluate the health system efficiency and investigate the impact of economic variables on the health system efficiency. Results: According to findings, the highest level of efficiency belonged to Alborz and Mazandaran provinces, while the lowest level of efficiency belonged to Sistan and Baluchestan and Ilam provinces. Regression estimates using the Tobit method indicated that the coverage of social insurance and the private sector share of healthcare costs have a positive effect on efficiency, while per capita production has a negative effect on the health system efficiency. Also, the coefficients obtained for GDP per capita, the population covered by insurance and the share of the private sector were -0.00049, 0.00602, and 0.00640, respectively. Conclusion: The average health system efficiency in the provinces varies significantly, suggesting that there is a considerable gap from optimal efficiency. It is recommended to expand the coverage of social insurance, which includes healthcare insurance, in order to improve the health system efficiency, so that more people can benefit from its services. The second suggestion is to pay more attention to the private sector in the health sector. Keywords: Health System, Efficiency, Stochastic Frontier Analysis, Tobit, Iran |
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Corresponding Author: Habib Ansarisamani Ha.ansarisa@gmail.com |
How to cite this paper:
Ansarisamani H, Khabbazikhanaghah M. Health System Efficiency in Iran and Its Influencing Factors. J Community Health Research 2024; 13(1): 221-227.
Ansarisamani H, Khabbazikhanaghah M. Health System Efficiency in Iran and Its Influencing Factors. J Community Health Research 2024; 13(1): 221-227.
Introduction
All organizations and companies strive to examine the efficiency of their subsidiaries by monitoring their performance and addressing existing shortcomings, while also preserving and strengthening existing strengths (1). In general, health systems around the world have three main objectives, which include improving the overall health of the community, providing services equitably, and being responsive to questions regarding the performance and effectiveness of the system (2).
Evaluating healthcare systems performance and efficiency is a key focus of development programs. By analyzing various indicators, we can determine if the healthcare system meets its goals. This assessment includes the role of human resources and facilities in affecting the population overall health (3). With the increase in the efficiency of the healthcare system, the quality of health for individuals in society improves and leads to increased citizen satisfaction. Increasing efficiency is an important economic and social goal. This goal will be achieved by considering human resources and other accessible facilities. The expectation from the healthcare system is to assess the level of achieving the intended goals and address any shortcomings found (4).
There is abundant evidence that inefficiency is a major problem in healthcare systems in most countries worldwide. Health policymakers consider efficiency as one of their primary concerns and strive to reduce inefficiency through sound decision-making. Inefficiency can lead to negative consequences for society and jeopardize the health status of individuals in the community. Furthermore, inefficiency in the healthcare system can divert resources from other productive sectors of the economy, thereby having a doubly negative impact (5). Kang et al. (2023) calculated efficiency using data envelopment analysis (DEA) and stochastic frontier analysis (SFA) methods for China and ASEAN countries. Using the Tobit regression model, they estimated factors affecting the efficiency of the health care system in these countries. The results showed that GDP per capita has a positive effect on efficiency, while urban population has a negative effect on efficiency in these countries (6). Gong et al., in their study, first calculated the efficiency of China health system after the reforms, then using Tobit regression, they calculated the effect of various factors on efficiency. The results showed the negative effect of public hospitals and social health and higher education costs on the efficiency (7). Khan and Nasrulddin (2022) examined the move towards privatization and its impact on the hospitals efficiency. The results show that private hospitals achieve a more appropriate ratio of efficiency (8). Ismaeili et al. (2019) investigated the efficiency of the healthcare sector of the Social Security Organization during 1387 to 1394 using the SFA method. The results showed that the average efficiency in the studied units was 0.816. The analysis of the impact of variables on efficiency indicated that the number of insured individuals and the number of healthcare centers had a significant relationship with efficiency (9). In the study by Sadeqi et al. (2019), the efficiency of Iran healthcare system was compared to that of member countries of the Organization for Economic Cooperation and Development. The results showed that the most efficient countries were Canada and Chile, while the least efficient countries were Slovakia and Hungary. Iran healthcare system performed relatively well compared to these countries (10). Godarzi et al. (2017) estimated hospitals efficiency in Kerman province using the SFA method. The results showed that the average efficiency of hospitals in Kerman province was 64.8, indicating that there is potential to improve efficiency in these hospitals by 35.2 (11).
Considering the importance of the subject, several studies have been conducted to examine the efficiency of the healthcare system. These studies have investigated the efficiency of the healthcare system using various methods and have examined the impact of different variables on its efficiency. Despite the conducted studies, the influence of variables such as the level of health insurance coverage and the private sector on the efficiency of the healthcare system in Iran has received less attention. In this study, the efficiency of the healthcare system in Iranian provinces was first obtained using SFA, and then the impact of variables such as the level of health insurance coverage, per capita production, the share of the private sector in healthcare expenditures, and so on, on the efficiency of the healthcare system was estimated.
Methods
The present study falls into the category of applied research. The required data was collected from the database of the Statistical Center of Iran. The data used in this study was cross-sectional data of the provinces of Iran in 2016. The main objective of this study was to examine the effects of variables such as the level of coverage by social insurance, per capita income, the share of the private sector in healthcare, etc. on efficiency.
Stochastic frontier analysis
SFA is an econometric technique that is widely used in health system efficiency studies. The difference between the actual output and the estimated maximum potential after accounting for random variation indicated the level of inefficiency in production. In the context of health production, efficiency was defined as the ratio of the actual health outcomes achieved to the maximum potential achievable with the resources used (12).
In the SFA method, by considering the frontier production function that represents the efficient firms' geometric locations and using econometric models, the efficiency of firms was estimated. In this method, the difference between actual production and frontier production was due to inefficiency and the other part was due to random factors. Generally, the stochastic frontier production function can be represented as Equation (13).
Yi = β´ Xi + vi – ui
So that
vi ~ N (0 , σ2 v)
ui = │ui│ , ui ~ N (0 , σ2 u)
In this equation, ui represents the inefficiency values of firm i. Yi represents the amount of production produced by firm X. β is the parameter vector, and vi shows the disturbance term. In estimating the stochastic frontier function, the error term consists of two components; one is the stochastic error term vi and the other is the one-sided error term ui, which represents inefficiency (13).
In the SFA method, the input and output variables need to be determined and the production function is then formed based on them. In this study, for the health production function, the life expectancy was considered as an output variable, and input variables such as the number of physicians, the number of active beds, and healthcare expenses were considered.
Factors affecting on the health system efficiency
Health system efficiency can be explained by social and economic factors. Therefore, variables such as per capita production, education, percentage of social insurance coverage, and the private sector's share of healthcare costs were considered as independent variables, and the variable of health system efficiency was considered as the dependent variable. The research equation was selected as follows based on the available data and research background.
TEi = β0+ β1 (GDPpci) + β2 (EDCi) + β2 (SPi) + β4 (INSi) + Ui
TE: Efficiency achieved by SFA
GDPpc: Gross Domestic Product per capita (in million rials)
EDC: Education variable, which in this study is the capacity of medical universities in each province relative to the population of that province.
SP: Share of private sector in health expenditures.
INS: Percentage of population covered by social insurance.
In most studies examining the factors affecting the efficiency of the health and medical system, the Tobit regression model has been used. Therefore, in this research, the Tobit regression model was used to estimate the model (6, 14-16).
The Tobit regression model is the following equation:
θit = zitδ +εit
where θit denotes the technical efficiency score for i observed at time period t, zit is the vector of economic variables, δ represents the vector
of parameters to be estimated, and εit is the error term (17).
Results
The summary of efficiency obtained for the provinces of Iran is as follows.
Evaluating healthcare systems performance and efficiency is a key focus of development programs. By analyzing various indicators, we can determine if the healthcare system meets its goals. This assessment includes the role of human resources and facilities in affecting the population overall health (3). With the increase in the efficiency of the healthcare system, the quality of health for individuals in society improves and leads to increased citizen satisfaction. Increasing efficiency is an important economic and social goal. This goal will be achieved by considering human resources and other accessible facilities. The expectation from the healthcare system is to assess the level of achieving the intended goals and address any shortcomings found (4).
There is abundant evidence that inefficiency is a major problem in healthcare systems in most countries worldwide. Health policymakers consider efficiency as one of their primary concerns and strive to reduce inefficiency through sound decision-making. Inefficiency can lead to negative consequences for society and jeopardize the health status of individuals in the community. Furthermore, inefficiency in the healthcare system can divert resources from other productive sectors of the economy, thereby having a doubly negative impact (5). Kang et al. (2023) calculated efficiency using data envelopment analysis (DEA) and stochastic frontier analysis (SFA) methods for China and ASEAN countries. Using the Tobit regression model, they estimated factors affecting the efficiency of the health care system in these countries. The results showed that GDP per capita has a positive effect on efficiency, while urban population has a negative effect on efficiency in these countries (6). Gong et al., in their study, first calculated the efficiency of China health system after the reforms, then using Tobit regression, they calculated the effect of various factors on efficiency. The results showed the negative effect of public hospitals and social health and higher education costs on the efficiency (7). Khan and Nasrulddin (2022) examined the move towards privatization and its impact on the hospitals efficiency. The results show that private hospitals achieve a more appropriate ratio of efficiency (8). Ismaeili et al. (2019) investigated the efficiency of the healthcare sector of the Social Security Organization during 1387 to 1394 using the SFA method. The results showed that the average efficiency in the studied units was 0.816. The analysis of the impact of variables on efficiency indicated that the number of insured individuals and the number of healthcare centers had a significant relationship with efficiency (9). In the study by Sadeqi et al. (2019), the efficiency of Iran healthcare system was compared to that of member countries of the Organization for Economic Cooperation and Development. The results showed that the most efficient countries were Canada and Chile, while the least efficient countries were Slovakia and Hungary. Iran healthcare system performed relatively well compared to these countries (10). Godarzi et al. (2017) estimated hospitals efficiency in Kerman province using the SFA method. The results showed that the average efficiency of hospitals in Kerman province was 64.8, indicating that there is potential to improve efficiency in these hospitals by 35.2 (11).
Considering the importance of the subject, several studies have been conducted to examine the efficiency of the healthcare system. These studies have investigated the efficiency of the healthcare system using various methods and have examined the impact of different variables on its efficiency. Despite the conducted studies, the influence of variables such as the level of health insurance coverage and the private sector on the efficiency of the healthcare system in Iran has received less attention. In this study, the efficiency of the healthcare system in Iranian provinces was first obtained using SFA, and then the impact of variables such as the level of health insurance coverage, per capita production, the share of the private sector in healthcare expenditures, and so on, on the efficiency of the healthcare system was estimated.
Methods
The present study falls into the category of applied research. The required data was collected from the database of the Statistical Center of Iran. The data used in this study was cross-sectional data of the provinces of Iran in 2016. The main objective of this study was to examine the effects of variables such as the level of coverage by social insurance, per capita income, the share of the private sector in healthcare, etc. on efficiency.
Stochastic frontier analysis
SFA is an econometric technique that is widely used in health system efficiency studies. The difference between the actual output and the estimated maximum potential after accounting for random variation indicated the level of inefficiency in production. In the context of health production, efficiency was defined as the ratio of the actual health outcomes achieved to the maximum potential achievable with the resources used (12).
In the SFA method, by considering the frontier production function that represents the efficient firms' geometric locations and using econometric models, the efficiency of firms was estimated. In this method, the difference between actual production and frontier production was due to inefficiency and the other part was due to random factors. Generally, the stochastic frontier production function can be represented as Equation (13).
Yi = β´ Xi + vi – ui
So that
vi ~ N (0 , σ2 v)
ui = │ui│ , ui ~ N (0 , σ2 u)
In this equation, ui represents the inefficiency values of firm i. Yi represents the amount of production produced by firm X. β is the parameter vector, and vi shows the disturbance term. In estimating the stochastic frontier function, the error term consists of two components; one is the stochastic error term vi and the other is the one-sided error term ui, which represents inefficiency (13).
In the SFA method, the input and output variables need to be determined and the production function is then formed based on them. In this study, for the health production function, the life expectancy was considered as an output variable, and input variables such as the number of physicians, the number of active beds, and healthcare expenses were considered.
Factors affecting on the health system efficiency
Health system efficiency can be explained by social and economic factors. Therefore, variables such as per capita production, education, percentage of social insurance coverage, and the private sector's share of healthcare costs were considered as independent variables, and the variable of health system efficiency was considered as the dependent variable. The research equation was selected as follows based on the available data and research background.
TEi = β0+ β1 (GDPpci) + β2 (EDCi) + β2 (SPi) + β4 (INSi) + Ui
TE: Efficiency achieved by SFA
GDPpc: Gross Domestic Product per capita (in million rials)
EDC: Education variable, which in this study is the capacity of medical universities in each province relative to the population of that province.
SP: Share of private sector in health expenditures.
INS: Percentage of population covered by social insurance.
In most studies examining the factors affecting the efficiency of the health and medical system, the Tobit regression model has been used. Therefore, in this research, the Tobit regression model was used to estimate the model (6, 14-16).
The Tobit regression model is the following equation:
θit = zitδ +εit
where θit denotes the technical efficiency score for i observed at time period t, zit is the vector of economic variables, δ represents the vector
of parameters to be estimated, and εit is the error term (17).
Results
The summary of efficiency obtained for the provinces of Iran is as follows.
Table 1. Efficiency summary
| Mean | STD Dev | Min | Max | Observations | Symbol |
| 0.4743 | 0.1493 | 0.0908 | 0.7793 | 31 | Te |
Figure 1. Map diagram of health system efficiency 1395
The average efficiency achieved in the provinces of the country was 0.4743. The lowest efficiency was related to Sistan and Baluchestan province, and the highest efficiency was related to Alborz, Mazandaran, Zanjan, and Markazi provinces.
Tobit regression results
To estimate the factors affecting the health system efficiency, the efficiency variable obtained in the previous stage was considered as the dependent variable, and the other mentioned economic factors were considered as independent variables. The Tobit method was used to estimate the model. The estimation results are as follows.
Tobit regression results
To estimate the factors affecting the health system efficiency, the efficiency variable obtained in the previous stage was considered as the dependent variable, and the other mentioned economic factors were considered as independent variables. The Tobit method was used to estimate the model. The estimation results are as follows.
Table 2. Estimation results
| Coef. | T | Prob | Variable |
| -0.00049 | -1.72 | 0.096 | GDP per capita |
| 0.00602 | 2.68 | 0.012 | Population Covered by Insurance |
| 0.00640 | 2.30 | 0.030 | Private Sector Share of Health Expenditure |
| -0.00020 | -0.29 | 0.777 | Medical Student Admission Capacity |
| Prob chi2: 0.0008 Paeudo R2: 0.6824 | |||
The obtained coefficients for GDP per capita, Population Covered by Insurance and Private Sector Share of Health were significant at -0.00049 at the 90% confidence level, 0.00602 and 0.00640 at the 95% confidence level, respectively.
The results indicated that per capita production had a negative and significant effect on the health system efficiency, while the level of coverage of social insurance and the share of the private sector in healthcare costs had a positive and significant effect on the health system efficiency. Additionally, the results suggest that in this study, the variable of medical student capacity in universities did not have a significant effect on the health system efficiency.
Discussion
In this study, the efficiency of Iran health system has been calculated using the SFA method, then the effect of factors such as social security insurance, private sector, etc. on the efficiency has been investigated. According to the obtained results, provinces such as Sistan and Baluchistan and Ilam have had the least efficiency, which can be due to the difference in the low quality of medical centers and services provided in these provinces.
In this study, GDP per capita did not have a positive relationship with the health system efficiency, contrary to previous research. It is usually expected that as per capita income increases, the health system efficiency will also increase. However, an increase in per capita income can lead to an increase in demand for healthcare services, which can put pressure on the health system and reduce the quality of its services. Moreover, when healthcare resources are distributed unevenly, an increase in per capita income may not necessarily improve access to healthcare for all individuals.
On the other hand, the results showed that an increase in the coverage of social health insurance had a positive relationship with the health system efficiency, which is similar to the findings of Arhin et al. (2023), Esmaili et al. (2019), Medarevic and Vukovic (2021), and Yang et al. (2020) (9, 18-20).With an increase in the population covered by health insurance, more individuals will have access to more affordable healthcare facilities, increasing the possibility of diagnosis and treatment for insured individuals. This not only improves the overall health of society but also reduces the financial burden of diseases on individuals and families. As more people gain health insurance coverage, the existing inefficiencies in the healthcare system will diminish. This will enable health services to be provided more equitably, ensuring that a larger number of individuals have access to essential services. Additionally, an increase in income from health insurance can lead to increased investment in the healthcare sector, including treatment and prevention, thereby improving the performance of the healthcare system.
Increasing the share of the private sector in sectors such as healthcare, education, and security has both supporters and opponents. This study showed that increasing the share of the private sector in healthcare expenses has a positive relationship with the efficiency of the healthcare system, which is similar to the findings of Gong et al. (2019) and Khan and Nasrulddin (2022) (7, 8). By enhancing the involvement of the private sector in the health domain, individuals with insurance availability are presented with a broader range of health services. This expansion of options can facilitate the delivery of services that are customized to meet individual needs and preferences. A prevalent challenge within public health systems is the extended waiting periods to access services. By boosting capacity and fostering competition within the private sector, it becomes feasible to diminish wait times and enhance accessibility to health services. By augmenting financial contributions from the private sector, the Ministry of Health can implement more initiatives focused on preventive health and educational programs, thereby mitigating the incidence of disease.
Due to the absence of recent census data in Iran, the latest available information is from 2016. As a result, the health data is somewhat outdated. This issue can doubt the validity of the results. The solution to this problem is to conduct the census on time.
In past studies, less attention has been paid to the calculation of the efficiency of the health system using data from the panels of Iranian provinces and it was mostly based on the data of hospitals. Also, in this study, the importance of health insurance and the private sector in health was emphasized.
Conclusion
Based on the research findings, increasing the population covered by social insurance, including healthcare insurance, has led to increased efficiency in the healthcare system. Additionally, increasing private sector participation and the share of healthcare and treatment costs covered by the private sector has improved the efficiency of the healthcare system. Based on the results obtained in this study, it is suggested to increase the level of coverage of social insurance, especially in deprived areas, and to take further steps to increase the private sector's share in the healthcare sector by designing necessary programs and implementing appropriate policies to enhance the efficiency of the healthcare system. The government can encourage the private sector to invest in the health sector by providing appropriate facilities and creating tax exemptions. Also, the government can help to increase the quality of services, increase efficiency, and reduce health costs by establishing joint cooperation between the private and public sectors in health.
Acknowledgments
The authors would like to thank those who helped in conducting this study.
Conflicts of interest
There are no conflicts of interest related to this article.
Funding
This study was not supported by any sponsor or funder.
Ethical considerations
Ethical considerations were completely addressed and implemented in the study. Data used is freely available on the Internet, books or other public forum, permission for further use and analysis is implied.
Code of ethics
Maintained during the entire study.
Authors' contributions
H. A and M. K, had an equal contribution in all aspects including literature review, study design, data collection, data analysis, and manuscript preparation.
Open access policy
JCHR does not charge readers and their institution for access to its papers. Full text download of all new and archived papers are free of charge.
The results indicated that per capita production had a negative and significant effect on the health system efficiency, while the level of coverage of social insurance and the share of the private sector in healthcare costs had a positive and significant effect on the health system efficiency. Additionally, the results suggest that in this study, the variable of medical student capacity in universities did not have a significant effect on the health system efficiency.
Discussion
In this study, the efficiency of Iran health system has been calculated using the SFA method, then the effect of factors such as social security insurance, private sector, etc. on the efficiency has been investigated. According to the obtained results, provinces such as Sistan and Baluchistan and Ilam have had the least efficiency, which can be due to the difference in the low quality of medical centers and services provided in these provinces.
In this study, GDP per capita did not have a positive relationship with the health system efficiency, contrary to previous research. It is usually expected that as per capita income increases, the health system efficiency will also increase. However, an increase in per capita income can lead to an increase in demand for healthcare services, which can put pressure on the health system and reduce the quality of its services. Moreover, when healthcare resources are distributed unevenly, an increase in per capita income may not necessarily improve access to healthcare for all individuals.
On the other hand, the results showed that an increase in the coverage of social health insurance had a positive relationship with the health system efficiency, which is similar to the findings of Arhin et al. (2023), Esmaili et al. (2019), Medarevic and Vukovic (2021), and Yang et al. (2020) (9, 18-20).With an increase in the population covered by health insurance, more individuals will have access to more affordable healthcare facilities, increasing the possibility of diagnosis and treatment for insured individuals. This not only improves the overall health of society but also reduces the financial burden of diseases on individuals and families. As more people gain health insurance coverage, the existing inefficiencies in the healthcare system will diminish. This will enable health services to be provided more equitably, ensuring that a larger number of individuals have access to essential services. Additionally, an increase in income from health insurance can lead to increased investment in the healthcare sector, including treatment and prevention, thereby improving the performance of the healthcare system.
Increasing the share of the private sector in sectors such as healthcare, education, and security has both supporters and opponents. This study showed that increasing the share of the private sector in healthcare expenses has a positive relationship with the efficiency of the healthcare system, which is similar to the findings of Gong et al. (2019) and Khan and Nasrulddin (2022) (7, 8). By enhancing the involvement of the private sector in the health domain, individuals with insurance availability are presented with a broader range of health services. This expansion of options can facilitate the delivery of services that are customized to meet individual needs and preferences. A prevalent challenge within public health systems is the extended waiting periods to access services. By boosting capacity and fostering competition within the private sector, it becomes feasible to diminish wait times and enhance accessibility to health services. By augmenting financial contributions from the private sector, the Ministry of Health can implement more initiatives focused on preventive health and educational programs, thereby mitigating the incidence of disease.
Due to the absence of recent census data in Iran, the latest available information is from 2016. As a result, the health data is somewhat outdated. This issue can doubt the validity of the results. The solution to this problem is to conduct the census on time.
In past studies, less attention has been paid to the calculation of the efficiency of the health system using data from the panels of Iranian provinces and it was mostly based on the data of hospitals. Also, in this study, the importance of health insurance and the private sector in health was emphasized.
Conclusion
Based on the research findings, increasing the population covered by social insurance, including healthcare insurance, has led to increased efficiency in the healthcare system. Additionally, increasing private sector participation and the share of healthcare and treatment costs covered by the private sector has improved the efficiency of the healthcare system. Based on the results obtained in this study, it is suggested to increase the level of coverage of social insurance, especially in deprived areas, and to take further steps to increase the private sector's share in the healthcare sector by designing necessary programs and implementing appropriate policies to enhance the efficiency of the healthcare system. The government can encourage the private sector to invest in the health sector by providing appropriate facilities and creating tax exemptions. Also, the government can help to increase the quality of services, increase efficiency, and reduce health costs by establishing joint cooperation between the private and public sectors in health.
Acknowledgments
The authors would like to thank those who helped in conducting this study.
Conflicts of interest
There are no conflicts of interest related to this article.
Funding
This study was not supported by any sponsor or funder.
Ethical considerations
Ethical considerations were completely addressed and implemented in the study. Data used is freely available on the Internet, books or other public forum, permission for further use and analysis is implied.
Code of ethics
Maintained during the entire study.
Authors' contributions
H. A and M. K, had an equal contribution in all aspects including literature review, study design, data collection, data analysis, and manuscript preparation.
Open access policy
JCHR does not charge readers and their institution for access to its papers. Full text download of all new and archived papers are free of charge.
References
1. Bahadori MK, Abolghasemi K, Teymourzadeh E. Performance evaluation and ranking of selective wards in a military hospital using DEA and promethee method. Journal of military medicine. 2017; 18(4): 325-34. [Persian]
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Review: Research |
Subject:
Health care management
Received: 2024/06/20 | Accepted: 2024/10/8 | Published: 2024/11/22
Received: 2024/06/20 | Accepted: 2024/10/8 | Published: 2024/11/22
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