The Efficiency of Healthcare Systems in Europe: A Data Envelopment Analysis Approach

Efficiency evaluation of 28 health systems by MCDA and DEA

BACKGROUND

Policymakers, who are constantly discussing growing health expenditures, should know whether the health system is efficient. We can provide them with such information through international health system efficiency evaluations. The main objectives of this study are: (a) to evaluate the efficiency of health systems in 28 developed countries by multiple-criteria decision analysis (MCDA) and data envelopment analysis (DEA) and (b) to identify reasonable benchmark countries for the Czech Republic, for which we collect information on the relative importance of health system inputs and outputs.

METHODS

We used MCDA and DEA to evaluate the efficiency of the health systems of 28 developed countries. The models included four health system inputs (health expenditure as a relative share of GDP, the number of physicians, nurses, and hospital beds) and three health system outputs (life expectancy at birth, healthy life expectancy, and infant mortality rate). The sample covers 27 OECD countries and Russia, which is also included in the OECD database. To determine the input and output weights, we used a questionnaire sent to health policy experts in the Czech Republic.

RESULTS

We obtained subjective information on the relative importance of the health system inputs and outputs from 27 Czech health policy experts. We evaluated health system efficiency using four MCDA and two DEA models. According to the MCDA models, Turkey, Poland, and Israel were found to have efficient health systems. The Czech Republic ranked 16th, 19th, 15th, and 17th. The benchmark countries for the Czech Republic's health system were Israel, Estonia, Luxembourg, Italy, the UK, Spain, Slovenia, and Canada. The DEA model with the constant returns to scale identified four technically efficient health systems: Turkey, the UK, Canada, and Sweden. The Czech Republic was found to be one of the worst-performing health systems. The DEA model with the variable returns to scale identified 15 technically efficient health systems. We found that efficiency results are quite robust. With two exceptions, the Spearman rank correlations between each pair of models were statistically significant at the 0.05 level.

CONCLUSIONS

During the model formulation, we investigated the pitfalls of efficiency measurement in health care and used several practical solutions. We consider MCDA and DEA, above all, as exploratory methods, not methods providing definitive answers.

An examination of health care efficiency in Canada: a two-stage semi-parametric approach

Using data envelopment analysis, we examine the efficiency of Canada's universal health care system by considering a set of labour (physicians) and capital (beds) inputs, which produce a level of care (measured in terms of health quality and quantity) in a given region. Data from 2013-2015 were collected from the Canadian Institute for Health Information regarding inputs and from the Canadian Community Health Survey and Statistics Canada regarding our output variables, health utility (quality) and life expectancy (quantity). We posit that variation in efficiency scores across Canada is the result of regional heterogeneity regarding socioeconomic and demographic disparities. Regressing efficiency scores on such covariates suggests that regional unemployment and an older population are quite impactful and associated with less efficient health care production. Moreover, regional variation indicates the Atlantic provinces (Newfoundland, Prince Edward Island, Nova Scotia, New Brunswick) are quite inefficient, have poorer economic prospects, and tend to have an older population than the rest of Canada. Oaxaca-Blinder decompositions suggest that the latter two factors explain about one-third of this efficiency gap. Based on our two-stage semi-parametric analysis, we recommend Canada adjust their transfer payments to reflect these disparities, thereby potentially reducing inequality in regional efficiency.

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals. We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

Evaluating health systems' efficiency towards universal health coverage: A data envelopment analysis

To estimate the technical efficiency of health systems toward achieving universal health coverage (UHC) in 191 countries. We applied an output-oriented data envelopment analysis approach to estimate the technical efficiency of the health systems, including the UHC index (a summary measure that captures both service coverage and financial protection) as the output variable and per capita health expenditure, doctors, nurses, and hospital bed density as input variables. We used a Tobit simple-censored regression with bootstrap analysis to observe the socioeconomic and environmental factors associated with efficiency estimates. The global UHC index improved from the 2019 estimates, ranged from 48.4 (Somalia) to 94.8 (Canada), with a mean of 76.9 (std. dev.: ±12.0). Approximately 78.5% (150 of 191) of the studied countries were inefficient (ϕ < 1.0) with respect to using health system resources toward achieving UHC. By improving health system efficiency, low-income, lower-middle-income, upper-middle-income, and high-income countries can improve their UHC indices by 4.6%, 5.5%, 6.8%, and 4.1%, respectively, by using their current resource levels. The percentage of health expenditure spent on primary health care (PHC), governance quality, and the passage of UHC legislation significantly influenced efficiency estimates. Our findings suggests health systems inefficiency toward achieving UHC persists across countries, regardless of their income classifications and WHO regions, as well as indicating that using current level of resources, most countries could boost their progress toward UHC by improving their health system efficiency by increasing investments in PHC, improving health system governance, and where applicable, enacting/implementing UHC legislation.

Non-homogeneity in the efficiency evaluation of health systems

BACKGROUND

An international comparison of health system performance is a popular tool of health policy analysis. However, the efficiency evaluation of health systems is a practical example of an international comparison in which non-homogeneity is expected. The objective of this paper is to evaluate the efficiency of health systems by models in which a degree of non-homogeneity among countries is considered.

METHODS

We study the problem of non-homogeneity of health systems in the theoretical framework of the data envelopment analysis (DEA), which is a popular method of efficiency evaluation with hundreds of applications from various fields. DEA assume the homogeneity of production units and the homogeneity of the environment in which the production units operate. Hence, we compiled a summary of 14 recommendations on how to deal with the non-homogeneity in the DEA models. The analysed sample includes 38 OECD member countries. The data are from the year 2019.

RESULTS

As an example, we evaluated the health system efficiency of the Czech Republic. We used the DEA models with the neighbourhood measure of distance and the constraint limiting the comparison of countries with different levels of economic development. The health system inputs were the numbers of physicians, nurses, and hospital beds. In the production of the intermediate outputs (doctor consultations, inpatient care discharges), the Czech Republic should look at Poland, Slovakia and Slovenia. In the production of health outcomes (life expectancy), the peer countries are France, Italy and Switzerland.

CONCLUSIONS

The results of the DEA analysis are only indicative because no single analytical method can determine whether a health system is better or worse than others. We need to combine different methods, and DEA is one of them. We consider DEA as an exploratory method, not a method providing definitive answers.

The state and significant drivers of health systems efficiency in Africa: A systematic review and meta-analysis

Background

Low-and-middle-income countries, especially in Africa, lack the capacity to adequately invest in health systems to attain universal health coverage (UHC). As such, countries must improve efficiency and provide more services within the available resources. This systematic review synthesised evidence on the efficiency of health systems in the African region and its drivers.

Methods

We conducted a systematic literature review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Related studies were grouped and meta-analysed, while others were descriptively analysed. We employed a qualitative content synthesis for synthesising the drivers of efficiency.

Results

Overall, 39 studies met a predetermined inclusion criterion and were included from a possible 4 609 records retrieved through a rigorous search and selection process. Using a random effects restricted maximum likelihood method, the pooled efficiency score for the Africa region was estimated to be 0.77, implying that on the flip side, health system inefficiency across countries in the African region was approximately 23%. Across 22 studies that used data envelopment analysis to examine efficiency at the level of health facilities and sub-national entities, the efficiency level was 0.67. Facility-level studies tended to estimate low levels of efficiency compared to health system-level studies. Across the 39 studies, 21 significant drivers of inefficiency were reported, including population density of the catchment area, governance, health facility ownership, health facility staff density, national economic status, type of health facility, education index, hospital size and bed occupancy rate.

Conclusion

With approximately 23% of the inefficiency of health systems in Africa, improving efficiency alone will yield an average of 34% improvement in resource availability, assuming all countries are performing similarly to the frontier countries. However, with the low level of health expenditure per capita in Africa, the efficiency gains alone will be insufficient to meet the minimum funding requirement for UHC.

Registration

PROSPERO: CRD42022318122.

The influence of SYRIZA-ANEL Greek health policies on hospital efficiency

BACKGROUND

We analyse the impact of the three following categories of Health Policies (HP) carried out by the Greek SYRIZA-ANEL governments on the efficiency of Greek public general hospitals. These governments have implemented policies intended to change the rate of contributions to publicly funded healthcare (PCnH), policies to affect the volume and quality of publicly funded health care (PVQH) and those intended to affect the costs of publicly funded healthcare (PCH). A literary review of the PCnH. PVQH and PCH policies of the Greek SYRIZA-ANEL governments was carried out and an efficiency window-DEA study was executed using data from the Ministry of Health (MoH) and the Greek Statistical Authority (ELSTAT).

METHODS

The study was designed to assess the impact of PCnH. PVQH and PCH policies by the Greek SYRIZA-ANEL governments on the efficiency of Greek general hospitals. The data was collected from HEAL-Link scientific journals. Information on HPs was extracted from the work collected. The values of inputs and outputs used for the efficiency study were obtained from ELSTAT and Greek MoH databases.

RESULTS

HPs of the Greek SYRIZA-ANEL governments extend to all three HP categories of the sample used. These policies have a dual effect on both the inputs and outputs used in efficiency. Efficiency values exhibit fluctuations with good and bad years. The SYRIZA-ANEL governments seek to ensure more equality in access to health services. Some of the policies reduce costs and have a positive impact on efficiency, while others have the opposite effect. The increase in outputs achieved as a result of health policies is counter balanced by an increase in inputs.

CONCLUSIONS

The PCnH, PVQH and PCH policies of the SYRIZA-ANEL governance seem to have a dual orientation: some policies reduce the cost of a category and contain the total cost, thus positively contributing to an increase in efficiency. Certain policies are aimed more at fulfilling the criterion of equality in the provision of health services and thus the cost inevitably increases. From the window-DEA study, three relatively "good" years emerge (2015, 2016, 2018) and two "bad years" (2017, 2019). This analysis will be useful for further research on the effect of health policies on hospital efficiency in other countries and periods.

Country-level predictors of COVID-19 mortality

This study aimed to identify country-level predictors of COVID-19 mortality, after controlling for diverse potential factors, and utilizing current worldwide mortality data. COVID-19 deaths, as well as geographic, demographic, socioeconomic, healthcare, population health, and pandemic-related variables, were obtained for 152 countries. Continuous variables were examined with Spearman's correlation, categorical variables with ANOVA or Welch's Heteroscedastic F Test, and country-level independent predictors of COVID-19 mortality identified by weighted generalized additive models. This study identified independent mortality predictors in six limited models, comprising groups of related variables. However, in the full model, only WHO region, percent of population ≥ 65 years, Corruption Perception Index, hospital beds/100,000 population, and COVID-19 cases/100,000 population were predictive of mortality, with model accounting for 80.7% of variance. These findings suggest areas for focused intervention in the event of similar future public health emergencies, including prioritization of the elderly, optimizing healthcare capacity, and improving deficient health sector-related governance.

Classification of industrial engineering programs in Colombia based on state tests

This article proposes an approach for the classification of industrial engineering programs offered by different higher education institutions (HEIs) in Colombia, using data envelopment analysis (DEA) and validating the results with cluster analysis. To perform this classification, data from 5318 industrial engineering students from 93 higher education institutions are used as a basis for classification based on the Saber11 and SaberPro state tests. The state tests are used to measure graduates' academic performance in the data envelopment analysis. With the efficiency results it was possible to classify higher education institutions (HEIs) into three large groups. Subsequently, this classification was validated through cluster analysis. The results show a correct classification of 77%.

Benchmarking the operational efficiency of Mexican hospitals – a longitudinal study

Purpose

This study aims to benchmark the operational efficiency of fifty-eight public hospitals across Mexico between 2015 and 2018 and identifies the most critical inputs affecting their efficiency. In doing so, the study analyzes the impact of policy changes in the Mexican healthcare system introduced in recent years.

Design/methodology/approach

To measure the operational efficiency of Mexican public hospitals, data envelopment analysis (DEA) window analysis variable returns to scale (VRS) methodology using longitudinal data collected from the National Institute for Transparency and Access to Information (IFAI). Hospital groups are developed and compared using a categorization approach according to their average and most recent efficiency.

Findings

Results show that most of the hospitals in the study fall in the moving ahead category. The hospitals in the losing momentum or falling behind categories are mostly large units. Hospitals with initially low efficiency scores have either increased their efficiency or at least maintained a steady improvement. Finally, the findings indicate that most hospitals classified as moving ahead focused on a single care area (cancer, orthopedic care, child care and trauma).

Research limitations/implications

This study examined the technical efficiency of the Mexican healthcare system over a four-year period. Contrary to conventional belief, results indicate that most public Mexican hospitals are managed efficiently. However, recent changes in public and economic policies that came into effect in the current administration (2018) will likely have long-lasting effects on the hospitals' operational efficiency, which could impact the results of this study.

Originality/value

To the best of authors’ knowledge, this is the first study that examines the efficiency of the complex Mexican healthcare system using longitudinal data.

Analysis of the effect of patients' health status on efficiency: Application of data envelopment analysis in healthcare

The effective and efficient operation of public healthcare systems is more and more important as a consequence of the increasing amount of money spent on their operation. For this reason, accurate and science-based efficiency information is needed for managers and healthcare policy makers. The evaluation of the efficiency in this sector is particularly difficult because several measures and indicators are used. Data envelopment analysis (DEA) can provide aggregate and overall measures of efficiency. The purpose of this paper is the examination of the efficiency of in-patient rehabilitation units curing musculoskeletal disorders in Hungary. The research presented focuses on rehabilitation units which attend to patients recovering from stroke or other acquired brain injuries. Output-oriented, slack-based DEA models are applied for the evaluation of in-patient rehabilitation units using data of a national survey. The novelty of the method presented is the consideration of the change in patients' functional status when efficiency is evaluated using DEA.

Efficiency and Productivity Differences in Healthcare Systems: The Case of the European Union

This study aims to identify significant differences between the countries of the European Union, follow the course of achievement of the convergence objectives, assess developments against specific common characteristics of the countries, and propose possible measures that could improve the state of health in the EU as a whole by implementing standard cohesion policies. To compare efficiency and productivity among the states of the European Union, we used data envelopment analysis (DEA) and the Malmquist productivity index (MPI). On the basis of our findings, even countries that joined the EU later achieve high technical efficiency values. However, it should be noted that it is in these countries that technical efficiency values tend to decline. The values of the Malmquist productivity index broadly indicate stagnation in western countries and productivity decline in central and eastern European countries. This decline is mainly due to a negative shift in the technological frontier in these countries.

The impact of human resources for health on the health outcomes of Chinese people

Human resources for health (HRH) is a cornerstone in the medical system. This paper combined data envelopment analysis (DEA) with Tobit regression analysis to evaluate the efficiency of health care services in China over the years between 2007 and 2019. Efficiency was first estimated by using DEA with the choice of inputs and outputs being specific to health care services and residents' health status. Malmquist index model was selected for estimating the changes in total factor productivity of provinces and exploring whether their performance had improved over the years. Tobit regression model was then employed in which the efficiency score obtained from the DEA computations used as the dependent variable, and HRH was chosen as the independent variables. The results showed that all kinds of health personnel had a significantly positive impact on the efficiency, and more importantly, pharmacists played a critical role in affecting both the provincial and national efficiency. Therefore, the health sector should pay more attention to optimizing allocation of HRH and focusing on professional training of clinical pharmacists.

Vertical integration in healthcare: What does literature say about improvements on quality, access, efficiency, and costs containment?

INTRODUCTION

Vertical integration models involve integrating services from different levels of care (e.g., primary care, acute care, post-acute care). Therefore, one of their main objectives is to increase continuity of care, potentially improving outcomes like efficiency, quality, and access or even enabling cost containment.

OBJECTIVES

This study conducts a literature review and aims at contributing to the contentious discussion regarding the effects of vertical integration reforms in terms of efficiency, costs containment, quality, and access.

METHODS

We performed a systematic search of the literature published until February 2020. The articles respecting the conceptual framework were included in an exhaustive analysis to study the impact of vertical integration on costs, prices of care, efficiency, quality, and access.

RESULTS

A sample of 64 papers resulted from the screening process. The impact of vertical integration on costs and prices of care appears to be negative. Decreases in technical efficiency upon vertical integration are practically out of the question. Nevertheless, there is no substantial inclination to visualise a positive influence. The same happens with the quality of care. Regarding access, the lack of available articles on this outcome limits conjectures.

CONCLUSIONS

In summary, it is not clear yet whether vertically integrated healthcare providers positively impact the overall delivery care system. Nevertheless, the recent growing trend in the number of studies suggests a promising future on the analysis of this topic.

Efficiency analysis in the management of COVID-19 pandemic in India based on data envelopment analysis

Purpose: This article measured the performance of 32 states and union territories (UTs) of India against COVID-19 disease using efficiency score which was calculated by data envelopment analysis (DEA) and compared the efficiency score with the different models which are used in many articles to evaluate the efficiency of healthcare system. Here the input parameters are taken as public health expenditure in a million, number of hospitals, number of hospital beds, percentage of health workers, population density, and number of infected, and output parameters divided into good and bad categories such as the number of recovered are taken as good output. The number of death is taken as bad outputs. The modified undesirable output model is used to calculate efficiency score and compared the efficiency score with Charnes, Cooper, and Rhodes (CCR) and Banker, Charnes, and Cooper (BCC) models. Finally, the states & UTs are completely ranked with the help of efficiency score and Maximal Balance Index, and evaluated benchmarking for each states & UTs. Data Source: Secondary data were collected from Census 2011 and the Ministry of health & family welfare, Government of India on 32 stats & UTs (NHAC, 2018; NHP, 2019; COVID19India, 2021). Results: According to Undesirable model results, 16 (50%) of 32 Indian states & UTs s were found to be efficient. Among the efficient DMUs, Chandigarh is the most efficient unit and Meghalaya is the most inefficient unit. Rajasthan was the most referenced state for inefficient states. Limitation: The efficiency score is affected by changing the number of inputs and outputs. The lack of more effective parameters are used to evaluate performance and enable qualitative variable comparison.

Evaluation of the Efficiency of European Health Systems Using Fuzzy Data Envelopment Analysis

Many studies that assess efficiency in health systems are based on output mean values. That approach ignores the representativeness of the average statistic, which can become a serious problem in estimation. To solve this question, this research contributes in three different ways: the first aim is to evaluate the technical efficiency in the management of European health systems considering a set of DEA (Data Envelopment Analysis) and FDEA (Fuzzy Data Envelopment Analysis) models. A second goal is to assess the bias in the estimation of efficiency when applying the conventional DEA. The third objective is the evaluation of the statistical relationship between the bias in the efficiency estimation and the macroeconomic variables (income inequality and economic freedom). The main results show positive correlations between DEA and FDEA scores. Notwithstanding traditional DEA models overestimate efficiency scores. Furthermore, the size of the bias is positively related to income inequality and negative with economic freedom in the countries evaluated.

Clustering the countries for quantifying the status of Covid-19 through time series analysis

Purpose

This study aims to use financial stability and health facilities of countries, to cluster them for making a more consensus environment for manifesting the status of Covid-19 in a justifiable manner. The scarcity of the categorisation of the countries of the world in a common platform, and the requirement of manifesting the pandemic status such as Covid-19 in a justifiable manner create the demanding requirement. This study mainly focusses on assisting to generate a liable manifesto to criticise the span of viral infection of the severe acute respiratory syndrome coronavirus-2 over the globe.

Design/methodology/approach

Data for this study has been gathered from official websites of the World Bank, and the world in data. The Louvain clustering method has been used to cluster the countries based on their financial strength and health facilities. The resulted clusters are visualised using Silhouette plots. The anomalies of the clusters had been used to quantify the pandemic situation. The status of Covid-19 has been manifested with the time series analysis through python programming.

Findings

The countries of the world have been clustered into seven, where developed countries divided into three clusters and the countries with transition economies and developing clustered together into four clusters. The time series analysis of recognised anomalies of the clusters assist to monitor the government responses and analyse the efficiency of used safety measures against the pandemic.

Originality/value

This study’s resulted clusters are highly valuable as a division of countries of the whole world for evaluating the health systems and for the regional levels. Further, the results of time series analysis are beneficial in monitoring the government responses and analysing the efficiency of used safety measures against the pandemic.

Evaluation of Tobacco Control Measures in the Organization for Economic Co-operation and Development Countries: A Comparative Study Using Data Envelopment Analysis

BACKGROUND

This study aimed to measure the efficiency and productivity of tobacco control policies across 16 selected Organization for Economic Co-operation and Development (OECD) countries from 2008 to 2014.

STUDY DESIGN

A panel-data study.

METHODS

Data envelopment analysis was used in this study. Taxation on tobacco products and pictorial warning labels were chosen as the inputs. Percentage of the population of daily smokers above 15 years old and the number of cigarettes used per smoker per day were output variables. Additionally, the Malmquist total factor productivity (TFP) was used to analyze the panel data and measure productivity change and technical efficiency changes over time.

RESULTS

The highest technical efficiency score (1.05) was attributed to Norway, while the lowest (0.91) belonged to the UK. Technological change with a total mean of 1.06 implied that the technology and creativity have increased, while countries have been able to promote their creativity over the studied period. Norway with the TFP score of 1.15 was the most productive country, while the UK and Turkey with TFP scores of 0.95 and 0.98, respectively, were the least productive countries in terms of the implementation of the tobacco control policies.

CONCLUSION

Most OECD countries have productively implemented tax and pictorial warning policies to reduce tobacco use. To achieve the optimum outcome of the tobacco control policies and overcome the challenges of smoking use, countries need to tackle the difficult underlying factors, i.e. tobacco industry opposition and lobbyists, smuggling, and low socioeconomic status.

Health care system efficiency and life expectancy: A 140-country study

Despite the evidence of links between health expenditure and health care efficiency, it is still unclear why countries with similar levels of health expenditures experience different outputs in terms of life expectancy at birth. Health care system efficiency might shed some light on the question. Using output-oriented data envelopment analysis, we compared the health systems of 140 countries in terms of attained life expectancy. Efficiency is determined by the distance from the closest country on the best practice frontier, which identifies the highest attainable life expectancy observed for any given level of health care spending. By using national data form the Human Development Data, we built the efficiency frontier and computed the potential life expectancy increase for each country. The potential improvement was, on average, 5.47 years [95%CI: 4.71-6.27 years]. The least efficient countries (10th percentile of the efficiency score) could improve by 11.78 years, while the most efficient countries (90th percentile of the efficiency score) could only improve by 0.83 years. We then analyzed, with regression analysis stratified by average education level, and by the role of health-related variables in differentiating efficient and inefficient countries from each other. The results suggest that, among countries with lower levels of education, decreasing unemployment and income inequality increases average life expectancy, without increasing health expenditure levels.

Performance Evaluation of the Chinese Healthcare System

This study aims to evaluate the performance of the Chinese healthcare system. It uses sustainable development goal (SDG) 3, set by the United Nations to ensure healthy lives and promote well-being for all at all ages as a benchmark. It uses data of 17 variables ranging from the year 2000 to 2017 and uses a multistage methodology to evaluate the performance. In the first stage, it uses difference in mean test to know whether or not the indicators show an improvement in the second decade of the 21st century compared to the first decade. In the second phase, simple linear regression has been used to know the rate of change of performance of every indicator over the sample period. The third step compares the performance of the healthcare sector with the sustainable goals set by the UN and the fourth phase attempts to forecast performance for the next five years i.e., 2018 to 2022. As per the results, the Chinese healthcare sector has performed very well on many fronts except alcohol consumption in males, road accidents and the incidence of non-communicable diseases. Alcohol consumption by males is touching dangerous levels. Therefore, the policies should focus on educating males to lower their alcohol consumption to stay fit and healthy.

Efficiency in reducing air pollutants and healthcare expenditure in the Seoul Metropolitan City of South Korea

This study analyzes efficiency in the reduction of air pollutants and the associated healthcare costs using a stochastic frontier cost function panel data approach. For the empirical analysis, we use monthly data covering 25 districts in the Seoul metropolitan city of South Korea observed over the period January 2010 to December 2017. Our results show large variations in air pollution and healthcare costs across districts and over time and their efficiency in reducing air pollutants. The study concludes that efforts are needed to apply the World Health Organization's air quality standards for designing and implementing location-specific customized policies for improving the level of air quality and its equal distribution, provision of health services, and improved efficiency in improving air quality standards. The study identifies a number of determinants of air pollutants and efficiency enhancement which provide useful pointers for policymakers for addressing the current environmental problems in South Korea.

COVID-19 Response and Prospects of Clean/Sustainable Energy Transition in Industrial Nations: New Environmental Assessment

Coronavirus Disease 2019 (COVID-19) became a pandemic around the world and has huge impacts on our economic and social systems, particularly on the healthcare system and the transportation and energy sectors. To examine a relationship between healthcare and energy sectors in the COVID-19 era, we propose a holistic application of Data Envelopment Analysis for Environmental Assessment (DEA-EA) to assess the COVID-19 response performance of 33 OECD (Organization for Economic Co-operation and Development) nations and investigate whether health insurance systems contribute to the performance. We also associate the performance with mobility, which is an energy consumption measure, to test the relationship through statistical analyses. In the DEA-EA, particularly, this study incorporates undesirable outputs (i.e., the number of confirmed cases and that of deaths) as well as desirable outputs (i.e., the number of total recovered people and that of total tested people) during April 2020 as the initial stage of COVID-19. While the former outputs need to be maximized, the latter ones need to be minimized in the assessment of healthcare system performance. This study finds that (a) the COVID-19 response performance of countries is varying and those with higher public health coverage have outperformed others with lower public coverage in terms of combating the COVID-19 outbreak, and (b) the healthcare system performance is significantly associated with mobility. Particularly, the second finding indicates that outperforming nations in the healthcare system are returning to the normal (with less volatility) while underperforming ones are still stagnating in terms of mobility. It implies that outperforming countries need to prepare for continuous commitment to clean/sustainable energy transition.

Measuring operational efficiency of isolation hospitals during COVID-19 pandemic using data envelopment analysis: a case of Egypt

Purpose

This study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.

Design/methodology/approach

To measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.

Findings

Based on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.

Research limitations/implications

The limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.

Originality/value

Despite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

Priority Setting in the Polish Health Care System According to Patients' Perspective

Identification of health priorities is concerned with equitable distribution of resources and is an important part of strategic planning in the health care system. The aim of this article is to describe health priorities in the Polish health care system from the patients’ perspective. The study included 533 patients hospitalized in the Lodz region. The average age of the respondents was 48.5 years and one third (36.6%) had university education. Most of the respondents (64.9%) negatively assessed the functioning of the health care system in Poland. Most of them claimed the following aspects require improvements: financing health services (85.8%), determining priorities in health care (80.3%), the role of health insurance (80.3%), and medical education (70.8%). Over 70% of the respondents agreed the role of politicians in designing and implementing health system reforms should be limited. The fact that the respondents so negatively assessed the Polish health care system implies there is a need for full discussion on redefining health priorities.

Preparing for a "dirty bomb" attack: the optimum mix of medical countermeasure resources

BACKGROUND

In radiological emergencies with radionuclide incorporation, decorporation treatment is particularly effective if started early. Treating all people potentially contaminated ("urgent treatment") may require large antidote stockpiles. An efficacious way to reduce antidote requirements is by using radioactivity screening equipment. We analyzed the suitability of such equipment for triage purposes and determined the most efficient mix of screening units and antidote daily doses.

METHODS

The committed effective doses corresponding to activities within the detection limits of monitoring portals and mobile whole-body counters were used to assess their usefulness as triage tools. To determine the optimal resource mix, we departed from a large-scale scenario (60,000 victims) and based on purchase prices of antidotes and screening equipment in Germany, we calculated efficiencies of different combinations of medical countermeasure resources by data envelopment analysis. Cost-effectiveness was expressed as the costs per life year saved and compared to risk reduction opportunities in other sectors of society as well as the values of a statistical life.

RESULTS

Monitoring portals are adequate instruments for a sensitive triage after cesium-137 exposure with a high screening throughput. For the detection of americium-241 whole-body counters with a lower daily screening capacity per unit are needed. Assuming that 1% of the potentially contaminated patients actually need decorporation treatment, an efficient resource mix includes 6 monitoring portals and 25 mobile whole-body counters. The optimum mix depends on price discounts and in particular the fraction of victims actually needing treatment. The cost-effectiveness of preparedness for a "dirty bomb" attack is less than for common health care, but costs for a life year saved are less than for many risk-reduction interventions in the environmental sector.

CONCLUSION

To achieve economic efficiency a high daily screening capacity is of major importance to substantially decrease the required amount of antidote doses. Among the determinants of the number of equipment units needed, the fraction of the potentially contaminated victims that actually needs treatment is the most difficult to assess. Judging cost-effectiveness of the preparedness for "dirty bomb" attacks is an issue of principle that must be dealt with by political leaders.

Performance assessment of medical diagnostic laboratories: A network DEA approach

RATIONALE, AIMS, AND OBJECTIVES

The main purpose of this paper is to measure the efficiency and ranking of medical diagnostic laboratories by applying a network data envelopment analysis (NDEA).

METHODS

In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU), and an NDEA model is utilized to calculate the efficiency of each medical diagnostic laboratory. Therefore, we design a series of four-stage system composed of three main laboratory processes (the pretest process, the test process, and the posttest process). We also consider sustainability criteria in order to cover social, economic, and environmental problems of health care organizations.

RESULTS

The results show that three of the 22 considered laboratories are efficient. Therefore, the NDEA approach can lead to performance scores and ultimately real ranking. Also, the average efficiency scores show that the decrease of the reception unit's efficiency results in a decrease of the efficiency of each laboratory. Therefore, the laboratories can increase the number of patients. Along with the intermediate values of the reception unit and the sampling unit, the efficiency of the reception unit increases, which results in an increase for the overall efficiency of each laboratory.

CONCLUSION

The proposed model can appropriately help the administrators and managers to identify inefficient units in their laboratory and ultimately improve the laboratory performance.

Multilevel Analysis of the Relationship between Ownership Structure and Technical Efficiency Frontier in the Spanish National Health System Hospitals

Objective: To evaluate the relationship between the ownership structure of hospitals and the possibility of their being positioned on the frontier of technical efficiency in the economic crisis period 2010–2012, adjusting for hospital variables and regional characteristics in the areas where the Spanish National Health System (SNHS) hospitals are located. Methods: 230 National Health System hospitals were studied over the two-year period 2010–2012 according to their ownership structure—public hospitals, private hospitals and public–private partnership (PPP)—data envelopment analysis orientated to inputs was used to measure the overall technical efficiency, pure efficiency and efficiency of scale. A generalised linear mixed model (GLMM) with binomial distribution and logit link function was used to analyse the hospital and regional variables associated with positioning on the frontier. Results: There are substantial differences between the average pure technical efficiency of public, private and PPP hospitals, as well as a greater number of PPP models being positioned on the efficiency frontier (91.67% in 2012). The odds of being positioned on the frontier are 41.7 times higher in PPP models than in public hospitals. The average annual household income per region is related to the greater odds of hospitals being positioned on the frontier of efficiency. Conclusions: During the most acute period of recession in the Spanish economy, PPP formulas favoured hospital efficiency, by increasing the odds of being positioned on the frontier of efficiency when compared to private and public hospitals. The position on the frontier of efficiency of a hospital is related to the wealth of its region.

Measuring the operational and financial efficiency using a Malmquist data envelopment analysis: a case of Egyptian hospitals

Purpose

The efficient use of organizational resources is integral to the existence of prime firms. This study, using Malmquist data envelopment analysis (DEA), aims to assess in the level of operational and financial efficiency and its determinants for ensuring and sustaining excellent performance in 33 Egyptian private hospitals.

Design/methodology/approach

This study adopted a Malmquist DEA approach to assess the changes in operational and financial efficiency in Egyptian hospitals. Tobit regression was also used to identify the significant variables affecting their efficiency. In addition, a sensitivity analysis is carried out for model validations.

Findings

Out of 33 hospitals, 17 were found inefficient due to the decline in their technical efficiency. Moreover, the total value of the software programs and operational expenses and the total number of employees are common factors affecting both operational and financial efficiency. In addition, the number of physicians significantly affects the hospital's financial efficiency.

Practical implications

The study sheds light on the value of using DEA to assess efficiency. DEA in the context of emerging economy such as Egypt's can be a useful tool for decision-makers and practitioners in identifying and addressing performance weaknesses and thus supports continuous improvement in performance.

Originality/value

Several studies have adopted the DEA approach to assess the overall efficiency of hospitals in Europe and the United States. However, in the MENA region, these studies are uncommon. This study is thought to be one of the earliest attempts to assess hospitals' efficiency in Egypt.

Assessing the efficiency of Iran health system in making progress towards universal health coverage: a comparative panel data analysis

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 considered as output variables. The data for each indicator were taken from the Global Health Observatory data repository and World Development Indicator database, for 6 years (2010-2015).

RESULTS

The TE scores of Iran's health system were 0.75, 0.77, 0.74, 0.74, 0.97, and 0.84 in the period 2010-2015, respectively. TFP improved in 2011 (1.02), 2013 (1.01), and 2014 (1.30, generally). The overall efficiency and TFP increased in 2014. Changes made in CCHE per capita and GGHE/THE attributed to the increase of efficiency.

CONCLUSION

There is a growing demand for efficiency improvements in the health systems to achieve UHC. While there are no defined set of indicators or precise methods to measure health system efficiency, EDEA helped us to draw the picture of health system efficiency in Iran. Our findings highlighted the essential need for targeted and sustained interventions, i.e., allocation of enough proportion of public funds to the health sector, to improve universal financial coverage against health costs aiming to enhance the future performance of Iran's health system, ultimately. Such tailored interventions may also be useful for settings with similar context to speed up their movement towards improving efficiency, which in turn might lead to more resources to reach UHC.

"Nomen Omen": Exploring Connected Healthcare through the Perspective of Name Omen

Background: The evolution of names, from "medical informatics" to "connected health", implies that the evolvement of technology in health care has been shifted from technology-oriented to healthcare-oriented implementation. Connected healthcare, a healthcare platform of remote monitoring and self-management through technological measures, is suggested to contribute to the efficiency, cost-effectiveness, and satisfaction of healthcare recipient enhancement. However, limited understanding of related connected health (CH) terminology may constrain its implementation. Whether CH is a buzzword only or a practice that can contribute to an aging society is controversial. Objective: This study aims to distinguish CH-related terminology and to identify the trend of CH through reviewing its definition, initiation, development, and evolvement, in order to offer management insights and implications. The objective is to understand what is connected and who is cared about in the connected health model so that better applications can be addressed for the benefit of society. Method: This study reviews the evolution of names, from "medical informatics" in the 1970s to "connected health" after 2000, as well as relevant literature of CH, including e-health, telemedicine, telehealth, telecare, and m-health, to discover the trend of technology-related healthcare innovations. Results: The current status and issues facing accessibility, quality, and cost were presented. Its future trends will be explored through reviewing how changes in healthcare are managed, in addition to its operation and practice. Pre-conditions and requirements for implementing CH are identified to select a typical case to study. Findings suggest that areas with a complete business ecosystem-isolated locations, advanced information technology, aging in population, integrated health, and social care system-are prevalent for designing friendly CH environments. Conclusion: The evidence and tendency of technological convergence create a demand for innovation and partnering with start-up companies that offer a competitive advantage in innovation.

Sustainable efficiency assessment of private diagnostic laboratories under uncertainty

Purpose

Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty.

Design/methodology/approach

In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business.

Findings

The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading.

Originality/value

The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.

Technical efficiency of provincial public healthcare in South Africa

Background

Forty-nine million people or 83 per cent of the entire population of 59 million rely on the public healthcare system in South Africa. Coupled with a shortage of medical professionals, high migration, inequality and unemployment; healthcare provision is under extreme pressure. Due to negligence by the health professionals, provincial health departments had medical-legal claims estimated at R80 billion in 2017/18. In the same period, provincial health spending accounted for 33 per cent of total provincial expenditure of R570.3 billion or 6 per cent of South Africa’s Gross Domestic Product. Despite this, healthcare outcomes are poor and provinces are inefficient in the use of the allocated funds. This warrants a scientific investigation into the technical efficiency of the public health system.

Methods

The study uses data envelopment analysis (DEA) to assess the technical efficiency of the nine South African provinces in the provision of healthcare. This is achieved by determining, assessing and comparing ways that individual provinces can benchmark their performance against peers to improve efficiency scores. DEA compares firms operating in homogenous conditions in the usage of multiple inputs to produce multiple outputs. Therefore, DEA is ideal for measuring the technical efficiency of provinces in the provision of public healthcare. In DEA methodology, the firms with scores of 100 per cent are technically efficient and those with scores lower than 100 per cent are technically inefficient. This study considers six DEA models using the 2017/18 total health spending and health staff as inputs and the infant mortality rate as an output. The first three models assume the constant returns to scale (CRS) while the last three use the variable return to scale (VRS) both with an input-minimisation objective.

Results

The study found the mean technical efficiency scores ranging from 35.7 to 87.2 per cent between the health models 1 and 6. Therefore, inefficient provinces could improve the use of inputs within a range of 64.3 and 20.8 per cent. The Gauteng province defines the technical efficiency frontiers in all the six models. The second-best performing province is the North West province. Other provinces like KwaZulu-Natal, Limpopo and the Eastern Cape only perform well under the VRS. The other three provinces are inefficient.

Conclusions

Based on the VRS models 4 to 6, the study presents three policy options. Policy option 1 (model 4): the efficiency gains from addressing health expenditure wastage in four inefficient provinces amounts to R17 billion. Policy option 2 (model 5): the potential savings from the same provinces could be obtained from reducing 17,000 health personnel, advisably, in non-core areas. In terms of Policy option 3 (model 6), three inefficient provinces should reduce 6940 health workers while the same provinces, inclusive of KwaZulu-Natal could realise health expenditure savings of R61 million. The potential resource savings from improving the efficiency of the inefficient provinces could be used to refurbish and build more hospitals to alleviate pressure on the public health system. This could also reduce the per capita numbers per public hospital and perhaps their performance as overcrowding is reportedly negatively affecting their performance and health outcomes. The potential savings could also be used to appoint and train medical practitioners, specialists and researchers to reduce the alarming numbers of medical legal claims. Given the existing challenges, South Africa is not ready to implement the National Health Insurance (NHI) Scheme, as it requires additional financial and human resources. Instead, huge improvements in public healthcare provision could be achieved by re-allocating the resources ‘saved’ through efficiency measures by increasing the quality of public healthcare and extending healthcare to more recipients.

Efficiency of acute public hospitals in the region of Murcia, Spain

Aim: To evaluate the level of efficiency of public acute hospitals situated in the region of Murcia (Spain). Materials & methods: Data from nine acute general hospitals of Murcia's Health Service (SMS by its Spanish acronym) were analyzed over the 2012-2014 period. The data were extracted from the In-patient Health Establishment Statistics of the Ministry of Health, Social Services and Equality, from the National Health Service (SNS) portal and the SMS portal. To this end, the data envelopment analysis (DEA)-window method was used, since this extension of the basic DEA model allows to compare the efficiency of a small number of units over different years and analyze changes in efficiency over time. In addition, the model was complemented by smooth bootstrapping and a superefficiency analysis to improve the quality of the data interpretation. Four inputs were used (number of beds, number of operating rooms, personnel costs and operating costs), two undesirable outputs (average stay and rate of return) and three desirable outputs (weighted discharges, emergencies and surgical interventions). Results: The average level of inefficiency was 1.58% over the study period, with a good evolution between 2012 (3.53%) and 2014 (0.20%). This improvement was also reflected in the number of efficient hospitals that rose from two in 2012 to eight in 2014. Moreover, the slack levels detected were small. Conclusion: The management of the public hospitals analyzed was favorable, both regarding average level of efficiency and the number of hospitals qualified as efficient. However, the analysis revealed several ways to increase efficiency by reducing specific inputs and nondesirable outputs (mainly operating and personnel costs as well as average length of stay) while increasing desirable outputs (mostly the number of surgical interventions). To finish, specific policy measures are suggested to improve the performance of these hospitals.

A dataset of healthcare systems for cross-efficiency evaluation in the presence of flexible measure

This article presents the dataset of the healthcare systems indicators of 120 countries during 2010–2017, which is related to the research article “Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems” [1]. The data is collected from the World Bank and selected for the 120 countries. Depending on their role in the performance of the healthcare systems, the indicators are categorized into input (I), output (O) and flexible measure (FM) where the FM measure can play either role of input or output in the healthcare system. The dataset can be used to perform efficiency as well as cross-efficiency analysis of the healthcare systems using methods such as data envelopment analysis (DEA) in the presence of flexible measure.

Health care staff responses to disinvestment-A systematic search and qualitative thematic synthesis

BACKGROUND

Health care services must deliver high-quality, evidence-based care that represents sound value. Disinvestment is the process of withdrawing resources from any existing health care practices that deliver low gain for their cost and reallocating these toward practices that are more effective, efficient, and cost-effective, thus benefiting patients and the community.

PURPOSE

This is the first review to examine the responses of health care staff to disinvestment and investigate the factors that increase the likelihood of these staff accepting disinvestment or reallocation of resources from the health services they provide.

METHODS

We conducted a systematic search of five electronic databases using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) framework. A critical appraisal process of the quality of the included studies was performed by two authors. We undertook a thematic synthesis of the qualitative data to develop an overarching narrative.

RESULTS

Twelve studies were identified for synthesis and all found that the disinvestment process was challenging and controversial for those health care staff involved. Negative staff reactions to disinvestment identified were anxiety, disempowerment, distrust, and feelings of being dismissed and disrespected. Engagement with disinvestment was observed when staff were invited to participate in a process they considered transparent and in the best interests of the community.

PRACTICE RECOMMENDATIONS

Health care staff have a strong professional identity associated with autonomy in their decision making in the provision of health care services. Disinvestment from a service that health care staff can usually choose to provide threatens this identity. Engaging clinical champions to lead change, using rigorous patient outcome data, and transparent decision-making processes may assist health care staff to embrace a new identity as innovators and accept disinvestment in low-value health care.

Estimation of Association between Healthcare System Efficiency and Policy Factors for Public Health

Objective: To assess the association between the healthcare system’s efficiency and policy factors (the types of healthcare systems and various health policy indicators). Methods: In this study, a data envelopment analysis (DEA) with bootstrapping was applied to the healthcare system’s efficiency to correct the bias of efficiency scores and to rank countries appropriately. We analyzed data mainly from the OECD (Organization for Economic Co-operation and Development) Health Data from 2014. After obtaining the efficiency score result, we analyzed which policy factor caused the inefficiency of the healthcare system by Tobit Regression. Results: Based on five types of healthcare system classification, the result suggested that the social health insurance (e.g., Austria, Germany, Switzerland) showed the lowest efficiency score on average when compared to other types of systems, but evidence of a statistically significant difference in healthcare efficiency among four types of healthcare systems was not found. It was shown that the pure technological efficiency of the healthcare system was negatively influenced by two main factors: user choice for basic insurance coverage and degree of decentralization to sub-national governments. Conclusions: Our findings suggest that countries with relatively low healthcare system efficiency may learn from countries that implement policies related to a low level of user choice and a high level of centralization to achieve more economical allocation of their healthcare resources.

Efficiency Analysis of Healthcare System in Lebanon Using Modified Data Envelopment Analysis

The inflow of refugees from Syria into Lebanon necessitates a robust and efficient healthcare system in Lebanon to withstand the growing demand for healthcare service. For this purpose, we evaluate the efficiency of healthcare system in Lebanon from 2000 through 2015 by applying a modified data envelopment analysis (DEA) model. We have selected four output variables: life expectancy at birth, maternal mortality ratio, infant mortality rate, and newly infected with HIV and two input variables: total health expenditure (% of GDP) and number of hospital beds. The findings of the paper show improvement in the efficiency of the healthcare system in Lebanon after the widespread of the health system reform in 2005. It also shows that reduction in health expenditure does not necessarily reduce efficiency if operational and technical aspect of the healthcare system is improved. The study infers that the healthcare system in Lebanon is capable of withstanding the increase in health demand provided further resources are made available and the existing technical and operational improvement are maintained.

Health care service provision in Europe and regional diversity: a stochastic metafrontier approach

■■■: In the last decades, demographic change coupled with new and expensive medical innovations have put most health care systems in developed countries under financial pressure. Therefore, ensuring efficient service provision is essential for a sustainable health care system. This paper investigates the performance of regional health care services in six West European countries between 2005 and 2014. We apply a stochastic metafrontier model to capture the different conditions in the health care systems in the countries within the European Union. By means of this approach, it is possible to detect performance differences in the European health care systems subject to different conditions and technologies relative to the potential technology available. The results indicate that regional deprivation plays a key role for the efficiency of health care provision. Furthermore, a pooled model which assumes a similar technology for all countries cannot sufficiently account for differences between countries. Surprisingly, the Scandinavian regions lag behind other regions with respect to the metafrontier.

JEL CLASSIFICATION

C23, D61, I12, I18, R10.

Pregnancy care in Germany, France and Japan: an international comparison of quality and efficiency using structural equation modelling and data envelopment analysis

OBJECTIVES

Healthcare systems in developed countries may differ in financing and organisation. Maternity services and delivery are particularly influenced by culture and habits. In this study, we compared the pregnancy care quality and efficiency of the German, French and Japanese healthcare systems.

STUDY DESIGN

Comparative healthcare data analysis.

METHODS

In an international comparison based mainly on Organisation for Economic Co-operation and Development (OECD) indicators, we analysed the health resources significantly affecting pregnancy care and quantified its quality using structural equation modelling. Pregnancy care efficiency was studied using data envelopment analysis. Pregnancy output was quantified overall or separately using indicators based on perinatal, neonatal or maternal mortality.

RESULTS

The density of obstetricians, midwives, paediatricians and the average annual doctor's consultations were positively and the caesarean delivery rate negatively associated with pregnancy outcome. In the international comparison at an aggregate level, Japan ranked first for pregnancy care quality, whereas Germany and France were positioned in the second part of the ranking. Similarly, at an aggregate level, the Japanese system showed pure technical efficiency, whereas Germany and France revealed mediocre efficiency results. Perinatal, neonatal and maternal care quality and efficiency taken separately were quite similar and mediocre in Germany and France. In Japan, there was a marked difference between a highly effective and efficient care of the unborn and newborn baby, and a rather mediocre quality and efficiency of maternal care.

CONCLUSION

Germany, France, and Japan have to struggle with quality and efficiency issues that are nevertheless different: in Germany and France, disappointing pregnancy care quality does not correspond to the high health care expenditures and lead to low technical efficiency. The Japanese system shows a high variability in outcomes and technical efficiency. Maternal care quality during delivery seems to be a particular issue that could possibly be addressed by legally implementing quality assurance systems with stricter rules for reimbursement in obstetrics.

[Multilevel analysis of the technical efficiency of hospitals in the Spanish National Health System by property and type of management]

OBJECTIVE

To analyze technical efficiency by type of property and management of general hospitals in the Spanish National Health System (2010-2012) and identify hospital and regional explanatory variables.

METHOD

230 hospitals were analyzed combining data envelopment analysis and fixed effects multilevel linear models. Data envelopment analysis measured overall, technical and scale efficiency, and the analysis of explanatory factors was performed using multilevel models.

RESULTS

The average rate of overall technical efficiency of hospitals without legal personality is lower than hospitals with legal personality (0.691 and 0.876 in 2012). There is a significant variability in efficiency under variable returns (TE) by direct, indirect and mixed forms of management. The 29% of the variability in TE es attributable to the Region. Legal personality increased the TE of the hospitals by 11.14 points. On the other hand, most of the forms of management (different to those of the traditional hospitals) increased TE in varying percentages. At regional level, according to the model considered, insularity and average annual income per household are explanatory variables of TE.

DISCUSSION

Having legal personality favours technical efficiency. The regulatory and management framework of hospitals, more than public or private ownership, seem to explain technical efficiency. Regional characteristics explain the variability in TE.

[Analysis of the technical efficiency of hospitals in the Spanish National Health Service]

OBJECTIVE

To analyse the technical efficiency and productivity of general hospitals in the Spanish National Health Service (NHS) (2010-2012) and identify explanatory hospital and regional variables.

METHODS

230 NHS hospitals were analysed by data envelopment analysis for overall, technical and scale efficiency, and Malmquist index. The robustness of the analysis is contrasted with alternative input-output models. A fixed effects multilevel cross-sectional linear model was used to analyse the explanatory efficiency variables.

RESULTS

The average rate of overall technical efficiency (OTE) was 0.736 in 2012; there was considerable variability by region. Malmquist index (2010-2012) is 1.013. A 23% variability in OTE is attributable to the region in question. Statistically significant exogenous variables (residents per 100 physicians, aging index, average annual income per household, essential public service expenditure and public health expenditure per capita) explain 42% of the OTE variability between hospitals and 64% between regions. The number of residents showed a statistically significant relationship. As regards regions, there is a statistically significant direct linear association between OTE and annual income per capita and essential public service expenditure, and an indirect association with the aging index and annual public health expenditure per capita.

DISCUSSION

The significant room for improvement in the efficiency of hospitals is conditioned by region-specific characteristics, specifically aging, wealth and the public expenditure policies of each one.

Evaluation of world's largest social welfare scheme: An assessment using non-parametric approach

Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is the world's largest social welfare scheme in India for the poverty alleviation through rural employment generation. This paper aims to evaluate and rank the performance of the states in India under MGNREGA scheme. A non-parametric approach, Data Envelopment Analysis (DEA) is used to calculate the overall technical, pure technical, and scale efficiencies of states in India. The sample data is drawn from the annual official reports published by the Ministry of Rural Development, Government of India. Based on three selected input parameters (expenditure indicators) and five output parameters (employment generation indicators), I apply both input and output oriented DEA models to estimate how well the states utilize their resources and generate outputs during the financial year 2013-14. The relative performance evaluation has been made under the assumption of constant returns and also under variable returns to scale to assess the impact of scale on performance. The results indicate that the main source of inefficiency is both technical and managerial practices adopted. 11 states are overall technically efficient and operate at the optimum scale whereas 18 states are pure technical or managerially efficient. It has been found that for some states it necessary to alter scheme size to perform at par with the best performing states. For inefficient states optimal input and output targets along with the resource savings and output gains are calculated. Analysis shows that if all inefficient states operate at optimal input and output levels, on an average 17.89% of total expenditure and a total amount of $780million could have been saved in a single year. Most of the inefficient states perform poorly when it comes to the participation of women and disadvantaged sections (SC&ST) in the scheme. In order to catch up with the performance of best performing states, inefficient states on an average need to enhance women participation by 133%. In addition, the states are also ranked using the cross efficiency approach and results are analyzed. State of Tamil Nadu occupies the top position followed by Puducherry, Punjab, and Rajasthan in the ranking list. To the best of my knowledge, this is the first pan-India level study to evaluate and rank the performance of MGNREGA scheme quantitatively and so comprehensively.

A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix : How to Evaluate When There is Not DRGs?

The public health system has restricted economic resources. Because of that, it is necessary to know how the resources are being used and if they are properly distributed. Several works have applied classical approaches based in Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for this purpose. However, if we have hospitals with different casemix, this is not the best approach. In order to avoid biases in the comparisons, other works have recommended the use of hospital production data corrected by the weights from Diagnosis Related Groups (DRGs), to adjust the casemix of hospitals. However, not all countries have this tool fully implemented, which limits the efficiency evaluation. This paper proposes a new approach for evaluating the efficiency of hospitals. It uses a graph-based clustering algorithm to find groups of hospitals that have similar production profiles. Then, DEA is used to evaluate the technical efficiency of each group. The proposed approach is tested using the production data from 2014 of 193 Chilean public hospitals. The results allowed to identify different performance profiles of each group, that differs from other studies that employs data from partially implemented DRGs. Our results are able to deliver a better description of the resource management of the different groups of hospitals. We have created a website with the results ( bioinformatic.diinf.usach.cl/publichealth ). Data can be requested to the authors.

Nonparametric Optimization of Preference in Technical Efficiency in China

Applying nonparametric path-converged approach, the research innovatively provides the measurement of preference in technical efficiency by the ratio of labor elasticity to capital elasticity and further attempts to realize the optimization of preference in technical efficiency by a strategy of 30% abolishment of initial Drug Addition and a strategy with combination of smoothed governmental fiscal expenditure, which sheds fresh light on promoting hospitals’ efficiency in China from perspective of management engineering. With sample data of provincial public hospitals in Zhejiang Province during period of 200901-201306, the research obtains following conclusions. First, benchmark preference in technical efficiency shows production has shifted from physical capital preference to labor skilled preference in technical efficiency. Second, the changing trend of preference in technical efficiency validates initial Drug Addition and governmental fiscal expenditure pushes and restrains the labor skilled preference in technical efficiency respectively. Third, the strategy of 30% abolishment of Drug Addition will strengthen labor skilled preference in technical efficiency with less promotion intensity of initial Drug Addition. The strategy with combination of governmental fiscal expenditure restrains labor skilled preference in technical efficiency. The facts validate great urgency of raising payments for doctors and nurses so as to promoting efficiency effectively.