Technical efficiency in health production: A comparison between Iran and other upper middle-income countries (original) (raw)
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Background: Building upon decades of continuous reforms, Iran has been implementing various initiatives to reach universal health coverage (UHC). Improving efficiency is a crucial intermediate policy objective for UHC. Therefore, this article aimed to measure the efficiency and productivity changes of the Iranian health system in making progress towards UHC during 2010-2015 in comparison with 36 selected other upper-middle-income countries.Methods: We used panel data to measure the variations in technical efficiency (TE) and total factor productivity (TFP) through an extended data envelopment analysis (EDEA) and Malmquist productivity index, respectively. General Government Health Expenditure (GGHE) per capita (International dollar) was selected as the input variable. Service coverage of diphtheria, tetanus and pertussis; family planning; antiretroviral therapy; skilled attendants at birth; Tuberculosis treatment success rate; and GGHE as % of Total Health Expenditure (THE) were con...
Global Health Research and Policy
Background: The pursuit of efficiency and productivity is one of the goals of health systems. In the era of Sustainable Development Goals and particularly the move towards universal health coverage, it is imperative to curb wastage of resources to ensure sustainable access of the population to needed and effective health services without enduring financial hardship. This study aims to assess total factor productivity change of national health systems of 20 countries in the WHO's Eastern Mediterranean Region. Methods: Data Envelopment Analysis (DEA)-based Malmquist index is used to assess total factor productivity change and its componentsefficiency change and technical change. To assess the robustness of the Malmquist index estimates, bootstrapping was performed. Outputs used are life expectancy at birth for both sexes and infant mortality; while total expenditure on health per capita in international dollars (PPP) is used as a measure of input. Panel data for the period 2003-2014 was extracted from databases of the WHO and the World Bank. Results: In all but five countries covered in the study, a decline in the mean total factor productivity is observed during the period 2003-2014. The decline is driven by technical regress. In all countries, the technical change component of the Malmquist TFP index is less than unity (range: 0.896 to 0.945). All countries exhibited growth in efficiency (efficiency change exceeding one) except two countries (Djibouti and Iraq). The growth in efficiency was mainly due to change in scale efficiency. Overall, total factor productivity in the region declined by 3.8%. This was due to a 9.1% decline in technical change, which overshadowed the 5.8% increase in efficiency. Three countries-Libya, Qatar and Yemenshowed a marginal growth in total factor productivity. There was no change in total factor productivity in Kuwait and Lebanon. Conclusion: The decline in total factor productivity over the study period is likely to hamper achieving the targets of Sustainable Development Goal 3 of ensuring healthy lives and promoting well-being for all at all ages. It is recommended that country-level studies on efficiency and productivity of health systems be conducted in order to intensively examine the determinants of inefficiency and productivity decline and implement appropriate interventions that could enhance efficiency and productivity.
2014
Background Improving efficiency of health sector is of particular importance in all countries. To reach this end, it is paramount to measure the efficiency. On the other hand, there are many factors that affect the efficiency of health systems. This study aimed to measure the Technical Efficiency (TE) of health systems in Economic Cooperation Organization (ECO) countries during 2004–10 and to determine the factors affecting their TE. Methods This was a descriptive-analytical and panel study. The required data were gathered using library and field studies, available statistics and international websites through completing data collection forms. In this study, the TE of health systems in 10 ECO countries was measured using their available data and Data Envelopment Analysis (DEA) through two approaches. The first approach used GDP per capita, education and smoking as its inputs and life expectancy and infant mortality rates as the outputs. The second approach, also, used the health expenditures per capita, the number of physicians per thousand people, and the number of hospital beds per thousand people as its inputs and life expectancy and under-5 mortality rates as the outputs. Then, the factors affecting the TE of health systems were determined using the panel data logit model. Excel 2010, Win4Deap 1.1.2 and Stata 11.0 were used to analyze the collected data. Results According to the first approach, the mean TE of health systems was 0.497 and based on the second one it was 0.563. Turkey and Turkmenistan had, respectively, the highest and lowest mean of efficiency. Also, the results of panel data logit model showed that only GDP per capita and health expenditures per capita had significant relationships with the TE of health systems. Conclusion In order to maximize the TE of health systems, health policy-makers should pay special attention to the proper use of healthcare resources according to the people’s needs, the appropriate management of the health system resources, allocating adequate budgets to the health sector, establishing an appropriate referral system to provide better public access to health services according to their income and needs, among many others.
2020
Background: Aiming to enhance quality of care and increase efficiency, public hospitals have undergone several reforms in the course of last two decades in Iran. This paper reports the result of a national research that aimed to measure the technical efficiency and productivity change of public hospitals during 2012-2016 in Iran. Methods: We used Extended Data Envelopment Analysis (Extended-DEA) (an innovative modification to conventional DEA) to measure technical efficiency and productivity of 568 public hospitals. Nationally representative data were extracted from the official annual health reports. Data were analysed using GAMS software 24.3. Results: The average efficiency score of all hospitals was 0.733. 10.1% of all hospitals were efficient while 2.68% of them were under 0.2. The Malmquist Productivity Index (MPI) progressed in 49.3% of hospitals, remained constant in 2.3%, while 48.2% of hospitals regressed during 2015-2016. The average of MPI was 1.07 over the period of ana...
Applied Economics 48(37): 3497–3507, 2016
This study aims to assess the efficiency of health sectors of 34 OECD countries by employing input-oriented data envelopment analysis (DEA) method both under constant and variable returns to scale assumptions. In the analysis, the number of doctors, number of patient beds and health expenditure per capita were used as input variables and life expectancy at birth and infant mortality rate were used as outputs. At the first stage, DEA analysis was performed for 34 countries, and at the second stage outlier 8 countries were eliminated to form a more homogeneous group and to achieve more accurate results. 11 of the 26 countries were found to have efficient health systems, and there is room for efficiency improvements in health sector in the remaining 15 countries.
Muhammad M Bala, 2021
This study assesses and compares the productive efficiency of the national healthcare system of the ASEAN region which includes Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam amidst rising mortality rate from noncommunicable diseases (NCDs) in the Sustainable Development Goals (SDGs) era. Nonparametric data envelopment analysis technique based on the Malmquist Productivity Index is performed and its components, total factor productivity change, technical change and technological change are compared across the region. Two different models are considered in assessing and comparing the technical efficiency of the national healthcare system across the region with life expectancy at birth and mortality rate from NCDs as parallel health care output for both the models. The mean value of total factor productivity is 0.983 and 0.974 which suggests that national healthcare system productivity efficiency decays by 1.7% for Model I and 2.6% for Model II, respectively. This suggests that the health care system inefficiencies across the ASEAN region have not made life expectancy to improve as much as it should be and curtailed the mortality rate from growing chronic NCDs within a decade. The region is likely to lag behind in achieving SDGs 3 target 4 on reducing by one-third premature mortality from chronic NCDs unless the health care system's technical efficiency is improved across the region. The finding suggests a microlevel study on each country to identify major sources of healthcare system inefficiency in a bid to ameliorate it.
Review of Economics and Political Science
Purpose This paper aims to evaluate the technical efficiency of the health-care systems in 21 selected middle-income countries during the period (2000–2017) and determine the source of inefficiency whether it is transient (short run) or persistent (long run). Design/methodology/approach The study uses the stochastic frontier analysis technique through employing the generalized true random effects model which overcomes the drawbacks of the previously introduced stochastic frontier models and allows for the separation between unobserved heterogeneity, persistent inefficiency and transient inefficiency. Findings Persistent efficiency is lower than the transient efficiency; hence, there are more efficiency gains that can be made by the selected countries by adopting long-term policies that aim at reforming the structure of the health-care system in the less efficient countries such as South Africa and Russia. The most efficient countries are Vietnam, Mexico and China which adopted a soc...
Measuring the efficiency of health systems in Asia: a data envelopment analysis
BMJ Open, 2019
ObjectiveThis study aims to estimate the technical efficiency of health systems in Asia.SettingsThe study was conducted in Asian countries.MethodsWe applied an output-oriented data envelopment analysis (DEA) approach to estimate the technical efficiency of the health systems in Asian countries. The DEA model used per-capita health expenditure (all healthcare resources as a proxy) as input variable and cross-country comparable health outcome indicators (eg, healthy life expectancy at birth and infant mortality per 1000 live births) as output variables. Censored Tobit regression and smoothed bootstrap models were used to observe the associated factors with the efficiency scores. A sensitivity analysis was performed to assess the consistency of these efficiency scores.ResultsThe main findings of this paper demonstrate that about 91.3% (42 of 46 countries) of the studied Asian countries were inefficient with respect to using healthcare system resources. Most of the efficient countries b...
2020
Background Building upon decades of continuous reforms, since 2014 under the banner of health transformation plan (HTP), Iran has been implementing various initiatives to strengthen its health system. Improving efficiency of the health system is fundamental to achieve better performance and reach universal health coverage (UHC). This article aimed to measure the efficiency and productivity changes in the Iranian health system during 2010-2015 in comparison with 36 selected other upper-middle income countries. Methods We used panel data to measure the variations in technical efficiency (TE) and total factor productivity (TFP) through an extended data envelopment analysis (EDEA) and Malmquist productivity index, respectively. General Government Health Expenditure (GGHE) per capita (International dollar) was selected as input variable. Service coverage of diphtheria, tetanus and pertussis; family planning; antiretroviral therapy; skilled attendants at birth; Tuberculosis treatment succ...
Health System Efficiency: A Fragmented Picture Based on OECD Data
PharmacoEconomics - Open, 2017
Background Globally, health expenditure as a percentage of GDP has increased in recent years, so evaluating the health care systems used in different countries is an important tool for identifying best practices and improving inefficient health care systems. Objective We investigate health system efficiency at the country level based on OECD health data. We focus on several aspects of health care systems to identify specific inefficiencies within them. This information hints at potential policy interventions that could improve specific parts of a country's health care system. Methods A discussion is provided of ideal-typical evaluations of health systems, ignoring data restrictions, which provide the theoretical basis for an analysis performed under factual data restrictions. This investigation includes health care systems in 34 countries and is based on OECD health data. Health care system efficiency scores are obtained using data envelopment analysis (DEA). Relative productivity measures are calculated based on average DEA prices. Given the severe data limitations involved, instead of performing an all-encompassing analysis of each health care system, we focus on several aspects of each system, performing five partial analyses. Results For each country, the efficiencies yielded by the five partial analyses varied considerably, resulting in an ambiguous picture of the efficiencies of the various health care systems considered. A synopsis providing comprehensive rankings of the analyzed countries is provided. Conclusion Analysis of several aspects of the health care systems considered here highlights potential improvements in specific areas of these systems, thereby providing information for policymakers on where to focus when aiming to improve a country's health care system.