Technical efficiency in the use of health care resources: a comparison of OECD countries (original) (raw)
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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.
2017
It has been proposed that cross-country comparisons of the technical efficiency of health production, estimated using data envelopment analysis (DEA), have useful applications for policy makers. In theory such an analysis utilises measures of the socioeconomic determinants of health relevant to all social policy, not just health policy. Using OECD and WHO data, this paper critically analyses a number of outstanding theoretical questions regarding the use of DEA in this setting. It concludes that until such questions are addressed, the resultant implications for policy will be based on misleading information.
Comparing efficiency of health systems across industrialized countries: a panel analysis
BMC Health Services Research, 2015
Background: Rankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data. Methods: We primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors. Results: The US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank. Discussion: Our study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions. Conclusions: Future international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency.
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.
Relative Efficiency of Health Provision: A DEA Approach with Non-Discretionary Inputs
SSRN Electronic Journal, 2000
We estimate a semi-parametric model of health production process using a two-stage approach for OECD countries. By regressing data envelopment analysis output efficiency scores on non-discretionary variables, both using Tobit analysis and a single and double bootstrap procedure, we show that inefficiency is strongly related to GDP per head, the education level, and health behaviour such as obesity and smoking habits. The used bootstrapping procedure corrects likely biased DEA output scores taking into account that environmental variables are correlated to output and input variables.
Health Policy and Technology, 2020
Objectives: To achieve sustainable health development, health systems need to constantly enhance their efficiency, through for instance reducing waste of resources. This study aimed to measure the efficiency in producing health in Upper Middle-Income Countries (UMICs) with a focus on Iran. Method: A modified data envelopment analysis (DEA)-based Malmquist Productivity Index (MPI) was used to assess the changes in health productivity. Panel data was extracted from databases of the World Health Organization and the World Bank for the period of 2009-2015. Results: The efficiency score of 13% of countries was higher than 0.8, while the score of all countries was above 0.5. The average score of Iran performance was 0.791 during the period. On average, performance improved in 15 countries, while it declined in 20 countries during the study period. Conclusion: Different countries have implemented various health reforms to improve efficiency. We envisage, policy makers in the UMICs locate their health system performance and plan to improve it in line with the local specifications, along with the global pathway towards universal health coverage and sustainable health development ultimately.
Comparison of Healthcare System Performances in Oecd Countries
International Journal of Health Services Research and Policy
Health spending is increasing every day around the world. Because of this, efficient use of resources (human, technology, material, etc.) becomes more important. This study aimed to compare the health efficiencies of the Organization for Economic Cooperation and Development (OECD) countries. In order to consider the trend of efficiency of the countries in the observed period (2014-2018), window analysis is chosen as the most appropriate input-oriented Data Envelopment Analysis (DEA) technique. The DEA window method was chosen since it leads to increased discrimination on findings and enables year-by-year comparisons. Input and output variables used in the study were determined by examining other studies in the literature. In this respect, the input variables were identified as the number of physicians per thousand people, the number of nurses per thousand people, the number of hospital beds per thousand people, health spendings (% of GDP); and output variables were expected life expectancy at birth, and rate of surviving infants. According to the results of the DEA window analysis, only Mexico was found to be efficient. Other countries with an efficiency score of more than 90% are Turkey (0.999), Japan (0.991), Korea (0.974), Luxembourg (0.937). On the other hand; Austria (0.591), Switzerland (0.545), and Germany (0.511) were the last countries in the efficiency score ranking. In these countries, which produce high health output, their inputs are also high, so they are at the end of the ranking of efficiency scores.
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...
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.