Determinants of healthcare system's efficiency in OECD countries

Stroke rehabilitation pathways during the first year: A cost-effectiveness analysis from a cohort of 460 individuals

BACKGROUND

Stroke burden challenges global health, and social and economic policies. Although stroke recovery encompasses a wide range of care, including in-hospital, outpatient, and community-based rehabilitation, there are no published cost-effectiveness studies of integrated post-stroke pathways.

OBJECTIVE

To determine the most cost-effective rehabilitation pathway during the first 12 months after a first-ever stroke.

METHODS

A cohort of people in the acute phase of a first stroke was followed after hospital discharge; 51 % women, mean (SD) age 74.4 (12.9) years, mean National Institute of Health Stroke Scale score 11.7 (8.5) points, and mode modified Rankin Scale score 3 points. We developed a decision tree model of 9 sequences of rehabilitation care organised in 3 stages (3, 6 and 12 months) through a combination of public, semi-public and private entities, considering both the individual and healthcare service perspectives. Health outcomes were expressed as quality-adjusted life years (QALY) over a 1-year time horizon. Costs included healthcare, social care, and productivity losses. Sensitivity analyses were conducted on model input values.

RESULTS

From the individual perspective, pathway 3 (Short-term Inpatient Unit » Community Clinic) was the most cost-effective, followed by pathway 1 (Rehabilitation Centre » Community Clinic). From the healthcare service perspective, pathway 3 was the most cost-effective followed by pathway 7 (Outpatient Hospital » Private Clinic). All other pathways were considered strongly dominated and excluded from the analysis. The total 1-year mean cost ranged between €12104 and €23024 from the individual's perspective and between €10992 and €31319 from the healthcare service perspective.

CONCLUSION

Assuming a willingness-to-pay threshold of one times the national gross domestic product (€20633/QALY), pathway 3 (Short-term Inpatient Unit » Community Clinic) was the most cost-effective strategy from both the individual and healthcare service perspectives. Rehabilitation pathway data contribute to the development of a future integrated care system adapted to different stroke profiles.

The spatio-temporal pattern and its influencing factors of production efficiency of health resources in China

There is always a contradiction between the limited health resources and the unlimited demand of the population for health services, and only by improving the productivity of health resources can the health level of the population be improved as much as possible. Using prefecture-level administrative regions as spatial units, the paper analyzes the spatial pattern and changes of health productivity of health resources in China from 2000 to 2010, and uses a spatial panel Tobit model to examine the effects of factors such as technical level of health institutions, health service accessibility, public health policies and ecological environment quality on health productivity of health resources. The results show that with the Hu Huanyong line as the dividing line, the spatial heterogeneity of "high in the southeast and low in the northwest" in the health productivity of China's health resources is clear; as the regional differences narrow, the spatial correlation increases, and the spatial pattern of "overall dispersion and partial agglomeration" becomes more obvious. The fitting results of the spatial Durbin model reveal the direction and degree of influence of local and adjacent factors on the production efficiency of health resources. The positive influence of technical level of local health institutions and the accessibility of health services, the literacy level and the ability to pay for health services of residents in adjacent areas, the degree of urbanization of regional health resource allocation, climate suitability and the quality of the atmospheric environment are significant. And the negative influence of local residents' literacy and ability to pay for health services, the technical level of health institutions in adjacent areas and the degree of medicalization of health resource allocation are also significant. The influence of the degree of medicalization of local health resource allocation and the accessibility of health services in adjacent areas are significantly spatial-heterogeneous.

Factors influencing the technical efficiency of diabetes care at primary care level in Mexico

Diabetes prevalence is rising globally, especially in low- and middle-income countries like Mexico, posing challenges for healthcare systems that require efficient primary care to manage the disease. However, healthcare efficiency is influenced by factors beyond decision-makers, including socioeconomic and political conditions. This study aims to evaluate the technical efficiency of primary healthcare for diabetes patients in Mexico over a 12-year period and explore the impact of contextual variables on efficiency. A longitudinal analysis was conducted using administrative and socio-demographic data from 242 health jurisdictions between 2009 and 2020. Data envelopment analysis with bootstrapping and output orientation was used to measure the technical efficiency; health resources in infrastructure and human resources were used as inputs. As outcome, the number of patients receiving treatment for diabetes and the number of patients with controlled diabetes were considered. Machine learning algorithms were employed to analyse multiple factors affecting the provision of diabetes health services and assess heterogeneity and trends in efficiency across different health jurisdictions. The average technical efficiency in primary healthcare for diabetes patients was 0.44 (CI: 0.41-0.46) in 2009, reaching a peak of 0.71 (CI: 0.69-0.72) in 2016, and moderately declining to 0.60 (CI: 0.57-0.62) in 2020; these differences were statistically significant. The random forest analysis identified the marginalization index, primary healthcare coverage, proportion of indigenous population and demand for health services as the most influential variables in predicting efficiency levels. This research underscores the crucial need for the formulation of targeted public policies aimed at extending the scope of primary healthcare services, with a particular focus on addressing the unique challenges faced by marginalized and indigenous populations. According to our results, it is necessary that medical care management adjust to the specific demands and needs of these populations to guarantee equitable care in Mexico.

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis

BACKGROUND

Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance.

METHODS

We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics.

RESULTS

Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider.

CONCLUSIONS

Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking.

Inappropriate CT examinations: how much, who and where? Insights from a clinical decision support system (CDSS) analysis

OBJECTIVE

To assess the appropriateness of Computed Tomography (CT) examinations, using the ESR-iGuide.

MATERIAL AND METHODS

A retrospective study was conducted in 2022 in a medium-sized acute care teaching hospital. A total of 278 consecutive cases of CT referral were included. For each imaging referral, the ESR-iGuide provided an appropriateness score using a scale of 1-9 and the Relative Radiation Level using a scale of 0-5. These were then compared with the appropriateness score and the radiation level of the recommended ESR-iGuide exam.

DATA ANALYSIS

Pearson's chi-square test or Fisher exact test was used to explore the correlation between ESR-iGuide appropriateness level and physician, patients, and shift characteristics. A stepwise logistic regression model was used to capture the contribution of each of these factors.

RESULTS

Most of exams performed were CT head (63.67%) or CT abdominal pelvis (23.74%). Seventy percent of the actual imaging referrals resulted in an ESR-iGuide score corresponding to "usually appropriate." The mean radiation level for actual exam was 3.2 ± 0.45 compared with 2.16 ± 1.56 for the recommended exam. When using a stepwise logistic regression for modeling the probability of non-appropriate score, both physician specialty and status were significant (p = 0.0011, p = 0.0192 respectively). Non-surgical and specialist physicians were more likely to order inappropriate exams than surgical physicians.

CONCLUSIONS

ESR-iGuide software indicates a substantial rate of inappropriate exams of CT head and CT abdominal-pelvis and unnecessary radiation exposure mainly in the ED department. Inappropriate exams were found to be related to physicians' specialty and seniority.

CLINICAL RELEVANCE STATEMENT

These findings underscore the urgent need for improved imaging referral practices to ensure appropriate healthcare delivery and effective resource management. Additionally, they highlight the potential benefits and necessity of integrating CDSS as a standard medical practice. By implementing CDSS, healthcare providers can make more informed decisions, leading to enhanced patient care, optimized resource allocation, and improved overall healthcare outcomes.

KEY POINTS

• The overall mean of appropriateness for the actual exam according to the ESR-iGuide was 6.62 ± 2.69 on a scale of 0-9. • Seventy percent of the actual imaging referrals resulted in an ESR-iGuide score corresponding to "usually appropriate." • Inappropriate examination is related to both the specialty of the physician who requested the exam and the seniority status of the physician.

Effects of healthcare financing policy tools on health system efficiency: Evidence from sub-Saharan Africa

Background

Evidence shows high levels of catastrophic and impoverishing healthcare expenditure among households in sub-Saharan Africa (SSA). The way healthcare is financed has an impact on how well a health system performs its functions and achieves its objectives. This study aims to examine the effect of healthcare financing policy tools on health system efficiency.

Method

The study classifies 46 sub-Saharan African (SSA) countries into four groups of health systems sharing similar healthcare financing strategies. A two-stage and one-stage stochastic frontier analysis (SFA) and Tobit regression techniques were employed to assess the impact of healthcare financing policy variables on health system efficiency. Data from the selected 46 SSA countries from 2000 to 2019 was investigated.

Results

The results revealed that prepayment healthcare financing arrangements, social health insurance, mixed- and external-financing healthcare systems significantly enhance health system efficiency. Reliance on a single source for financing healthcare, particularly private out-of-pocket payment reduces health system efficiency.

Conclusion

For policy-making purposes, health care systems financed through a mix of financing arrangements comprising social health insurance, private, and public funding improve health system efficiency in delivering better health outcomes as opposed to depending on one major source of financing, particularly, private out-of-pocket payments.

Stochastic frontier approach to efficiency analysis of health facilities in providing services for non-communicable diseases in eight LMICs

BACKGROUND

The rising burden of non-communicable diseases presents an increasing public health challenge to many low- and middle-income countries. This problem may be compounded in health systems with lower levels of technical efficiency (TE).

METHODS

This study used recent Service Provision Assessments data to estimate the level of TEs of health facilities in eight countries. Initially, the general and disease-specific service readiness indexes are estimated. Finally, the production function is estimated using the exposures and the outcomes of the model.

RESULTS

Evidence shows that the general and disease-specific service readiness indexes are significantly associated with an increase in the number of outpatient visits. Outpatient visits may increase by 14% with an increase in health worker density. Similarly, outpatient visits may increase by 0.3% with a unit increase in the general and diabetes service readiness indexes. Furthermore, outpatient visits may increase by 0.4% and 0.8% with an increase in services readiness for cardiovascular and respiratory diseases. respectively. Overall, the level of TE score suggests the need for improvement.

CONCLUSIONS

Facility-level service readiness for chronic diseases is quite low. Therefore, improving health outcomes related to chronic diseases requires urgent investment in high-quality health systems in these countries.

Uncertain Malmquist productivity index: An application to evaluate healthcare systems during COVID-19 pandemic

Evaluation of healthcare systems, as a key organization providing different health services, is essential. This issue becomes more crucial when occurring crises such as a pandemic. They need to keep track of their success in the face of the crisis to assess the effects of policy changes and their capability to respond to new challenges. The Malmquist Productivity Index (MPI) is measured to analyze the causes of productivity change between two periods of time. The estimation of the traditional MPI requires reliable and detailed information on the inputs and outputs of decision-making units. However, there are a lot of situations where input and/or output may be imprecise. It is not manageable to reliably measure certain measurement indices, such as quality of treatment or system flexibility. For such cases, experts are invited to model their opinion. Uncertainty theory is a mathematical branch rationally dealing with belief degrees. The primary objective of this study is to apply MPI concept in the nonparametric approach of data envelopment analysis to calculate the efficiency of systems over different periods of time under uncertain conditions. Accordingly, we consider the MPI when inputs and outputs are belief degrees of experts. Furthermore, the sensitivity of the model is analyzed to determine the reliability of the results to the variation of variables. Finally, as an illustrative example, we explore longitudinal efficiency of healthcare systems during COVID-19 pandemic. According to the results of our model, the majority of the countries have improved in the second period which can be the result of efforts to improve pandemic preparedness. The decomposition of MPI into efficiency changes and technical changes indicates that the rise in productivity is entirely related to the progressive change of the production frontier related to policymaking. This application attempts to demonstrate how crucial it is to take uncertainties into account when comparing the performance of different systems over periods of time. The developed model enables us to consider the uncertainty existing in COVID-19 pandemic. The proposed model can handle more accurately the uncertainty during the pandemic. Thus, the result could be more reliable, which can benefit decision-makers in regard to performance improvement.

Assessing the efficiency of health systems in achieving the universal health coverage goal: evidence from Sub-Saharan Africa

OBJECTIVE

Universal health coverage (UHC) is a major pathway to save many people from catastrophic and impoverishing healthcare spending and address the inequality in health and healthcare. The objective of this paper is to assess the efficiency with which health systems in sub-Saharan Africa (SSA) are utilizing healthcare resources to progress towards achieving the UHC goal by 2030.

METHODS

The study followed the guidelines proposed by the World Health Organization (WHO) and World Bank joint UHC monitoring framework and the computational operationalization approach proposed by Wagstaff et al. (2015) to estimate the UHC index for each of the 30 selected SSA countries. The bootstrapping output-oriented data envelopment analysis (DEA) was used to estimate the bias-corrected technical efficiency scores and examine the environmental factors that influence health system efficiency.

RESULTS

The estimated UHC levels ranged from a minimum of 52% to a maximum of 81% [Formula: see text] with a median coverage of 66%. The average bias-corrected efficiency score was 0.81 [Formula: see text]. The study found that education, governance quality, public health spending, external health funding, and prepayment arrangements that pool funds for health had a positive significant effect on health system efficiency in improving UHC, while out-of-pocket payment had a negative impact.

CONCLUSION

The results show that health systems in SSA can potentially enhance UHC levels by at least 19% with existing healthcare resources if best practices are adopted. Policymakers should aim at improving education, good governance, and healthcare financing architecture to reduce out-of-pocket payments and over-reliance on donor funding for healthcare to achieve UHC.

Analysing the Efficiency of Health Systems: A Systematic Review of the Literature

BACKGROUND

Efficiency refers the use of resources in ways that optimise desired outcomes. Health system efficiency is a priority concern for policy makers globally as countries aim to achieve universal health coverage, and face the additional challenge of an aging population. Efficiency analysis in the health sector has typically focused on the efficiency of healthcare facilities (hospitals, primary healthcare facilities), with few studies focusing on system level (national or sub-national) efficiency. We carried out a thematic review of literature that assessed the efficiency of health systems at the national and sub-national level.

METHODS

We conducted a systematic search of PubMed and Google scholar between 2000 and 2021 and a manual search of relevant papers selected from their reference lists. A total of 131 papers were included. We analysed and synthesised evidence from the selected papers using a thematic approach (selecting, sorting, coding and charting collected data according to identified key issues and themes).

FINDINGS

There were more publications from high- and upper middle-income countries (53%) than from low-income and lower middle-income countries. There were also more publications focusing on national level (60%) compared to sub-national health systems' efficiency. Only 6% of studies used either qualitative methods or mixed methods while 94% used quantitative approaches. Data envelopment analysis, a non-parametric method, was the most common methodological approach used, followed by stochastic frontier analysis, a parametric method. A range of regression methods were used to identify the determinants of health system efficiency. While studies used a range of inputs, these generally considered the building blocks of health systems, health risk factors, and social determinants of health. Outputs used in efficiency analysis could be classified as either intermediate health service outputs (e.g., number of health facility visits), single health outcomes (e.g., infant mortality rate) or composite indices of either intermediate outputs of health outcomes (e.g., Health Adjusted Life Expectancy). Factors that were found to affect health system efficiency include demographic and socio-economic characteristics of the population, macro-economic characteristics of the national and sub-national regions, population health and wellbeing, the governance and political characteristics of these regions, and health system characteristics.

CONCLUSION

This review highlights the limited evidence on health system efficiency, especially in low- and middle-income countries. It also reveals the dearth of efficiency studies that use mixed methods approaches by incorporating qualitative inquiry. The review offers insights on the drivers of the efficiency of national and sub-national health systems, and highlights potential targets for reforms to improve health system efficiency.

Effect of Primary Health Care Expenditure on Universal Health Coverage: Evidence from Sub-Saharan Africa

Background

Investment in primary health care (PHC) to achieve universal health coverage (UHC) and better health outcomes remains a key global health agenda. This study aimed to assess the effects of PHC spending on UHC and health outcomes.

Methods

The study used the Grossman Health Production Model and conducted econometric analyses using panel data from 2016 to 2019 covering 34 countries in SSA. Fixed and random effects panel regression models were used for the analyses. All the analyses in this study were carried out using the statistical software package STATA Version 15.

Results

We found that PHC expenditure has a positive significant but inelastic effect on UHC and life expectancy at birth and a negative effect on infant mortality. Both the fixed and random effects models provided a robust relationship between PHC expenditure and UHC and health outcomes. Education, access to an improved water source, and the age structure of the population were found to be strongly associated with health outcomes.

Conclusion

The inelastic nature of the PHC expenditure means that the UHC goal might only be achieved at high levels of PHC expenditure. This implies that policymakers must make conscious effort to increase PHC expenditure to ensure the attainment of the UHC goal.

Identifying and understanding benefits associated with return-on-investment from large-scale healthcare Quality Improvement programmes: an integrative systematic literature review

BACKGROUND

We previously developed a Quality Improvement (QI) Return-on-Investment (ROI) conceptual framework for large-scale healthcare QI programmes. We defined ROI as any monetary or non-monetary value or benefit derived from QI. We called the framework the QI-ROI conceptual framework. The current study describes the different categories of benefits covered by this framework and explores the relationships between these benefits.

METHODS

We searched Medline, Embase, Global health, PsycInfo, EconLit, NHS EED, Web of Science, Google Scholar, organisational journals, and citations, using ROI or returns-on-investment concepts (e.g., cost-benefit, cost-effectiveness, value) combined with healthcare and QI. Our analysis was informed by Complexity Theory in view of the complexity of large QI programmes. We used Framework analysis to analyse the data using a preliminary ROI conceptual framework that was based on organisational obligations towards its stakeholders. Included articles discussed at least three organisational benefits towards these obligations, with at least one financial or patient benefit. We synthesized the different QI benefits discussed.

RESULTS

We retrieved 10 428 articles. One hundred and two (102) articles were selected for full text screening. Of these 34 were excluded and 68 included. Included articles were QI economic, effectiveness, process, and impact evaluations as well as conceptual literature. Based on these literatures, we reviewed and updated our QI-ROI conceptual framework from our first study. Our QI-ROI conceptual framework consists of four categories: 1) organisational performance, 2) organisational development, 3) external outcomes, and 4) unintended outcomes (positive and negative). We found that QI benefits are interlinked, and that ROI in large-scale QI is not merely an end-outcome; there are earlier benefits that matter to organisations that contribute to overall ROI. Organisations also found positive aspects of negative unintended consequences, such as learning from failed QI.

DISCUSSION AND CONCLUSION

Our analysis indicated that the QI-ROI conceptual framework is made-up of multi-faceted and interconnected benefits from large-scale QI programmes. One or more of these may be desirable depending on each organisation's goals and objectives, as well as stage of development. As such, it is possible for organisations to deduce incremental benefits or returns-on-investments throughout a programme lifecycle that are relevant and legitimate.

Spatio-Temporal Disparity and Driving Forces of the Supply Level of Healthcare Service in the Yangtze River Delta

The equalization of healthcare supply is not only related to the people's need for a better life, but can also provide a strong guarantee for the high-quality and sustainable development of the Yangtze River Delta integration. By using exploratory spatial analysis techniques, this study analyzed the spatio-temporal evolution characteristics and heterogeneous influence effects of the supply level of healthcare service in the Yangtze River Delta from 2007 to 2019. It was found that the supply level of healthcare service in the Yangtze River Delta had improved significantly. The differences in the supply level of healthcare service between cities had tended to narrow without polarization, and the supply level of healthcare service generally showed a high spatial pattern in the south delta and low spatial pattern in the north delta. The higher the supply level of healthcare service was, the weaker the interannual variability was. The supply level of healthcare service in the Yangtze River Delta region presented obvious spatial association and differentiated tendency of local high and low spatial clusters. The relative length and curvature of the supply level of healthcare service in the Yangtze River Delta generally presented a spatial pattern with low values in the northeast and high values in the southwest. Population density and urban-rural income gap generally exhibited negative spatio-temporal impact on the supply level of healthcare service across most cities. On the other hand, urbanization level and per capita disposable income generally had positive spatio-temporal impact on the supply level of healthcare service across most cities. Per capita gross domestic product (GDP) showed an increasingly positive spatio-temporal impact on the supply level of healthcare service across most cities. While per capita fiscal expenditure exhibited significantly negative impact on the supply level of healthcare service across most cities in space.

Nurturing Socioculturally and Medically Appropriate Palliative Care Delivery: Lessons Learned by Israeli Medical Faculty

Israel is one of the few countries worldwide with a national policy and defined standards of palliative care (PC); its culture is highly diverse and more traditionally oriented in comparison with Western countries. This study describes the current state of PC in Israel through examination of: (1) its current status, self-image and structural factors; (2) its relation to cultural and political characteristics; and (3) the chances, goals and obstacles of advancing PC in Israel. Face-to-face interviews were conducted at all five public medical faculties in Israel from November 2017 to February 2018. The following findings are reported: (1) definition of palliative care, (2) multidisciplinary approach, (3) special role of nurses, (4) personal perceptions of death, (5) understanding the role of medicine, (6) specialty palliative medicine, (7) religious, spiritual and cultural aspects, (8) political and economic aspects, (9) obstacles and weaknesses, and (10) prospects and goals of palliative care. Participants perceive PC as an integrative healthcare service that should be available to all patients, including children and their families, at any stage of illness. They internalize that PC principles apply regardless of ethnic, cultural, and religious background. Utilizing nurses' leadership, enhancing multidisciplinary teamwork, and person-centered approach, supports better PC to more people.

Similarities and differences between two well-performing healthcare systems: a comparison between the Israeli and the Danish healthcare systems

Background

Denmark and Israel both have highly rated and well-performing healthcare systems with marked differences in funding and organization of primary healthcare. Although better population health outcomes are seen in Israel, Denmark has a substantially higher healthcare expenditure. This has caused Danish policy makers to take an interest in Israeli community care organization. Consequently, we aim to provide a more detailed insight into differences between the two countries’ healthcare organization and cost, as well as health outcomes.

Methods

A comparative analysis combining data from OECD, WHO, and official sources. World Health Organization (WHO) and the Organisation for Economic Co-operation and Development (OECD) statistics were used, and national official sources were procured from the two healthcare systems. Literature searches were performed in areas relevant to expenditure and outcome. Data were compared on health care expenditure and selected outcome measures. Expenditure was presented as purchasing power parity and as percentage of gross domestic product, both with and without adjustment for population age, and both including and excluding long-term care expenditure.

Results

Denmark’s healthcare expenditure is higher than Israel’s. However, corrected for age and long-term care the difference diminishes. Life expectancy is lower in Denmark than in Israel, and Israel has a significantly better outcome regarding cancer as well as a lower number of Years of Potential Life Lost. Israelis have a healthier lifestyle, in particular a much lower alcohol consumption.

Conclusion

Attempting to correct for what we deemed to be the most important influencing factors, age and different inclusions of long-term care costs, the Israeli healthcare system still seems to be 25% less expensive, compared to the Danish one, and with better health outcomes. This is not necessarily a function of the Israeli healthcare system but may to a great extent be explained by cultural factors, mainly a much lower Israeli alcohol consumption.

COVID-19 and the efficiency of health systems in Europe

BACKGROUND

This study aims at analyzing the efficiency of the health systems of 31 European countries in treating COVID-19, for the period January 1, 2020 - January 1, 2021, by incorporating some factors from a multidimensional perspective.

METHODS

The methodology used in the research was Data Envelopment Analysis (DEA), through which efficiency scores for health systems have been calculated. The research was performed considering three stages: the first wave (January 1-June 15), the relaxation period (June 15-October 1) and the second wave (October 1-December 31). In evaluating the determinants of the efficiency of health systems, six major fields of influence were taken into account: health care, health status, population, economic, cultural/societal and governmental issues, all covering 15 indicators. After measuring the efficiency, we used the Tobit type regression to establish the influencing elements on it.

RESULTS

The results for the public health systems of European states were determined for each country and period. We evaluated the efficiency of health systems in Europe against COVID-19, starting from health inputs (COVID-19 cases, physicians, nurses, hospital beds, health expenditure) and output (COVID-19 deaths). The obtained outputs show that, especially in the first phase of the pandemic, the inefficiency of the health systems was quite high, mainly in Western countries (Italy, Belgium, Spain, UK). In the relaxation phase and in the second wave, the Western states, severely affected at the beginning of the pandemic, began to take adequate measures and improve the efficiency of their sanitary systems. Instead, Eastern European countries were hit hard by the inefficiency of health systems (Bulgaria, Greece, Hungary, Romania). After Tobit regression, results of the study show that the influencing elements are different for the three stages: concerning the first wave, comobirdities, population age, and population density are important; for relaxation period a great influence have government effectiveness and power distance; with respect to second wave, the relevant factors are education and population density.

CONCLUSIONS

The results obtained could serve as starting points for health policymakers to perform comparative analyzes in terms of good practices in the health system and to develop national plans to better deal with health crises. At the same time, they can be used internationally to achieve a coherent and effective community response to the pandemic.

Destructive Role of COVID-19 Fear on Nurses Performance: Mediating Role of Stress

Given its importance to psychological issues, the COVID-19 pandemic has created numerous challenges for all individuals, but healthcare professionals and particularly nursing staff are at front lines, and their performance is significantly affected. The current study relates COVID-19 fear with psychological strain, i.e., stress amongst the nursing staff. Moreover, the intervening role of COVID-19 stress between COVID-19 fear and the performance of the nursing staff has also been tested. An online survey was conducted to collect data from nurses. A total of 471 responses of nurses were received during the process of online data collection from 16 November 2020 to 30 April 2021. Results revealed the significant effect of COVID-19 fear on COVID-19 stress and the performance of nurses. Additionally, the results substantiate that COVID-19 stress mediates between COVID-19 fear and the health care performance of nurses. COVID-19 fear has become a psychological consequence that increases stress among nursing staffs. This study fills the research gap about the performance of the health care sectors, particularly with respect to COVID-19 fear and COVID-19 stress among nurses. Hence, COVID-19 fear plays a significant role in COVID-19 stress in terms of influencing the health care performance of nurses. Overall, the results give pragmatic insights for the consequences of the COVID-19 pandemic.

The efficiency of provincial government health care expenditure after China's new health care reform

OBJECTIVE

We aim to estimate the total factor productivity and analyze factors related to the Chinese government's health care expenditure in each of its provinces after its implementation of new health care reform in the period after 2009.

MATERIALS AND METHODS

We use the Malmquist DEA model to measure efficiency and apply the Tobit regression to explore factors that influence the efficiency of government health care expenditure. Data are taken from the China statistics yearbook (2004-2020).

RESULTS

We find that the average TFP of China's 31 provincial health care expenditure was lower than 1 in the period 2009-2019. We note that the average TFP was much higher after new health care reform was implemented, and note this in the eastern, central and western regions. But per capita GDP, population density and new health care reform implementation are found to have a statistically significant impact on the technical efficiency of the provincial government's health care expenditure (P<0.05); meanwhile, region, education, urbanization and per capita provincial government health care expenditure are not found to have a statistically significant impact.

CONCLUSION

Although the implementation of the new medical reform has improved the efficiency of the government's health expenditure, it is remains low in 31 provinces in China. In addition, the government should consider per capita GDP, population density and other factors when coordinating the allocation of health care input.

SIGNIFICANCE

This study systematically analyzes the efficiency and influencing factors of the Chinese government's health expenditure after it introduced new health care reforms. The results show that China's new medical reform will help to improve the government's health expenditure. The Chinese government can continue to adhere to the new medical reform policy, and should pay attention to demographic and economic factors when implementing the policy.

"The education is a mirror of where palliative care stands in Israel today": An exploration of palliative care undergraduate education at medical schools in Israel

OBJECTIVE

Israel serves as a case study for understanding the importance of undergraduate palliative care (PC) education in implementing, developing, and enabling access to palliative care services. This article presents the findings collected from the five medical schools.

METHOD

This qualitative study supported by a survey explores and describes the state of undergraduate PC education at medical schools in Israel. The survey included questions on voluntary and mandatory courses, allocation of different course models, teaching methods, time frame, content, institutions involved, and examinations. Semi-structured interviews with teaching faculty were conducted at the same locations.

RESULTS

Eleven expert interviews and five surveys demonstrate that PC is taught as a mandatory subject at only two out of the five Israeli universities. To enhance PC in Israel, it needs to become a mandatory subject for all undergraduate medical students. To teach communication, cultural safety, and other basic competencies, new interactive teaching forms need to be developed and adapted. In this regard, nationwide cooperation is proposed. An exchange between medical schools and university clinics is seen as beneficial. The new generation of students is open to PC philosophy and multidimensional care provision but resources to support their growth as professionals and people remain limited.

SIGNIFICANCE OF RESULTS

This study underlines the importance of teaching in PC at medical schools. Undergraduate education is a central measure of PC status and should be used as such worldwide. The improvement of the teaching situation would automatically lead to a better practical implementation for the benefit of people. Medical schools should cooperate, as the formation of expertise exchange across medical schools would automatically lead to better PC education.

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.

Assessing the efficiency of countries in making progress towards universal health coverage: a data envelopment analysis of 172 countries

Introduction

Maximising efficiency of resources is critical to progressing towards universal health coverage (UHC) and the sustainable development goal (SDG) for health. This study estimates the technical efficiency of national health spending in progressing towards UHC, and the environmental factors associated with efficient UHC service provision.

Methods

A two-stage efficiency analysis using Simar and Wilson’s double bootstrap data envelopment analysis investigates how efficiently countries convert health spending into UHC outputs (measured by service coverage and financial risk protection) for 172 countries. We use World Bank and WHO data from 2015. Thereafter, the environmental factors associated with efficient progress towards UHC goals are identified.

Results

The mean bias-corrected technical efficiency score across 172 countries is 85.7% (68.9% for low-income and 95.5% for high-income countries). High-achieving middle-income and low-income countries such as El Salvador, Colombia, Rwanda and Malawi demonstrate that peer-relative efficiency can be attained at all incomes. Governance capacity, income and education are significantly associated with efficiency. Sensitivity analysis suggests that results are robust to changes.

Conclusion

We provide a 2015 baseline for cross-country UHC technical efficiency scores. If countries wish to improve their UHC outputs within existing budgets, they should identify their current efficiency and try to emulate more efficient peers. Policy-makers should focus on strengthening institutions and implementing known best practices to replicate efficient systems. Using resources more efficiently is likely to positively impact UHC coverage goals and health outcomes, and without addressing gaps in efficiency progress towards achieving the SDGs will be impeded.

Global Healthcare Resource Efficiency in the Management of COVID-19 Death and Infection Prevalence Rates

The scale of impact of the COVID-19 pandemic on society and the economy globally provides a strong incentive to thoroughly analyze the efficiency of healthcare systems in dealing with the current pandemic and to obtain lessons to prepare healthcare systems to be better prepared for future pandemics. In the absence of a proven vaccine or cure, non-pharmaceutical interventions including social distancing, testing and contact tracing, isolation, and wearing of masks are essential in the fight against the worldwide COVID-19 pandemic. We use data envelopment analysis and data compiled from Worldometers and The World Bank to analyze how efficient the use of resources were to stabilize the rate of infections and minimize death rates in the top 36 countries that represented 90% of global infections and deaths out of 220 countries as of November 11, 2020. This is the first paper to model the technical efficiency of countries in managing the COVID-19 pandemic by modeling death rates and infection rates as undesirable outputs using the approach developed by You and Yan. We find that the average efficiency of global healthcare systems in managing the pandemic is very low, with only six efficient systems out of a total of 36 under the variable returns to scale assumption. This finding suggests that, holding constant the size of their healthcare systems (because countries cannot alter the size of a healthcare system in the short run), most of the sample countries showed low levels of efficiency during this time of managing the pandemic; instead it is suspected that most countries literally "threw" resources at fighting the pandemic, thereby probably raising inefficiency through wasted resource use.

Application of DEA-Based Malmquist Productivity Index on Health Care System Efficiency of ASEAN Countries

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.

Predictors of (in)efficiencies of Healthcare Expenditure Among the Leading Asian Economies - Comparison of OECD and Non-OECD Nations

Purpose

The goal of this study was to assess the effectiveness of healthcare spending among the leading Asian economies.

Methods

We have selected a total of nine Asian nations, based on the strength of their economic output and long-term real GDP growth rates. The OECD members included Japan and the Republic of Korea, while the seven non-OECD nations were China, India, Indonesia, Malaysia, Pakistan, the Philippines, and Thailand. Healthcare systems efficiency was analyzed over the period 1996–2017. To assess the effectiveness of healthcare expenditure of each group of countries, the two-way fixed effects model (country- and year effects) was used.

Results

Quality of governance and current health expenditure determine healthcare system performance. Population density and urbanization are positively associated with a healthy life expectancy in the non-OECD Asian countries. In this group, unsafe water drinking has a statistically negative effect on healthy life expectancy. Interestingly, only per capita consumption of carbohydrates is significantly linked with healthy life expectancy. In these non-OECD Asian countries, unsafe water drinking and per capita carbon dioxide emissions increase infant mortality. There is a strong negative association between GDP per capita and infant mortality in both sub-samples, although its impact is far larger in the OECD group. In Japan and South Korea, unemployment is negatively associated with infant mortality.

Conclusion

Japan outperforms other countries from the sample in major healthcare performance indicators, while South Korea is ranked second. The only exception is per capita carbon dioxide emissions, which have maximal values in the Republic of Korea and Japan. Non-OECD nations’ outcomes were led by China, as the largest economy. This group was characterized with substantial improvement in efficiency of health spending since the middle of the 1990s. Yet, progress was noted with remarkable heterogeneity within the group.

A healthcare evaluation system based on automated weighted indicators with cross-indicators based learning approach in terms of energy management and cybersecurity

OBJECTIVE

Hospital performance evaluation is vital in terms of managing hospitals and informing patients about hospital possibilities. Also, it plays a key role in planning essential issues such as electrical energy management and cybersecurity in hospitals. In addition to being able to make this measurement objectively with the help of various indicators, it can become very complicated with the participation of subjective expert thoughts in the process.

METHOD

As a result of budget cuts in health expenditures worldwide, the necessity of using hospital resources most efficiently emerges. The most effective way to do this is to determine the evaluation criteria effectively. Machine learning (ML) is the current method to determine these criteria, determined by consulting with experts in the past. ML methods, which can remain utterly objective concerning all indicators, offer fair and reliable results quickly and automatically. Based on this idea, this study provides an automated healthcare system evaluation framework by automatically assigning weights to specific indicators. First, the ability of hands to be used as input and output is measured.

RESULTS

As a result of this measurement, indicators are divided into only input group (group A) and both input and output group (group B). In the second step, the total effect of each input on the output is calculated by using the indicators in group B as output sequentially using the random forest of the regression tree model.

CONCLUSION

Finally, the total effect of each indicator on the healthcare system is determined. Thus, the whole system is evaluated objectively instead of a subjective evaluation based on a single output.

A DEA-Based Complexity of Needs Approach for Hospital Beds Evacuation during the COVID-19 Outbreak

Data envelopment analysis (DEA) is a powerful nonparametric engineering tool for estimating technical efficiency and production capacity of service units. Assuming an equally proportional change in the output/input ratio, we can estimate how many additional medical resource health service units would be required if the number of hospitalizations was expected to increase during an epidemic outbreak. This assessment proposes a two-step methodology for hospital beds vacancy and reallocation during the COVID-19 pandemic. The framework determines the production capacity of hospitals through data envelopment analysis and incorporates the complexity of needs in two categories for the reallocation of beds throughout the medical specialties. As a result, we have a set of inefficient healthcare units presenting less complex bed slacks to be reduced, that is, to be allocated for patients presenting with more severe conditions. The first results in this work, in collaboration with state and municipal administrations in Brazil, report 3772 beds feasible to be evacuated by 64% of the analyzed health units, of which more than 82% are moderate complexity evacuations. The proposed assessment and methodology can provide a direction for governments and policymakers to develop strategies based on a robust quantitative production capacity measure.

Health systems efficiency in Eastern Mediterranean Region: a data envelopment analysis

BACKGROUND

One of the most important issues in public policy and welfare state is health care. Poor management leads to the waste of resources, including money, human resources, facilities, and equipment.

AIMS

This paper seeks to answer the question of which eastern Mediterranean countries are more effective in allocating their health resources, and does Iran, in relation to those countries, have an effective health system.

METHODS

This study examined technical efficiency among eastern Mediterranean countries in 2018. Data were extracted from Global Health Observatory data World Health Organization. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. Inputs are Physicians density per 10,000 populations, Total hospital beds per 10,000 populations, Current expenditure on health, % of gross domestic product and outputs are infant survival rate and Life expectancy.

RESULTS

The most efficient health systems in the eastern Mediterranean were Bahrain, Egypt, Iran, Lebanon, Morocco, Oman, Pakistan, Qatar, Tunisia and the United Arab Emirates. The inefficient countries are Iraq, Jordan, Kuwait, Libya, Palestine and Saudi Arabia.

CONCLUSIONS

Among the efficient countries, one category of high-entry countries such as Bahrain and Qatar with high input especially in health expenditure had higher output. The second group of countries with lower inputs such as Iran and Morocco has been able to produce similar output with other countries. Also, inefficiency in countries such as Saudi Arabia can be attributed to this with higher input such as health expenditure has lower output such life expectancy and infant survival rate.

Healthcare and Welfare Policy Efficiency in 34 Developing Countries in Asia

The healthcare and welfare policies of nations, as well as the amount of investments put into these areas, vary across countries. Investments in healthcare and welfare have been increasing worldwide which brings the question of assessing the efficiency of these investments. There are, however, difficulties in evaluating the effectiveness of such investments due to differences in countries’ economic development levels and due to the differences in data definition issues. There are only a limited number of studies in the literature that employ consistent and comparable indicators across countries. This study evaluates the healthcare investment efficiency and health competitiveness efficiency of 34 developing countries in Asia using a two-stage dynamic data envelopment analysis approach. Furthermore, we employ a broader measure of indicators on national healthcare and welfare policies and outcomes, in addition to the investment data on healthcare and welfare expenditures. Our findings indicate that the establishment of an investment environment with a consolidated approach and management is an important factor that increases the efficiency of investments in healthcare and welfare sectors. A consistent delivery of the national policy strategy is also crucial for reaching the medium-and long-term targets for each country. For example, if a country establishes healthcare and welfare policies that focus on improving its indicators with low efficiencies, the output will be improved and a better return on investment will be ensured in a long-term perspective.

Gender Inequalities in Health and Their Effect on the Economic Prosperity Represented by the GDP of Selected Developed Countries-Empirical Study

The objective is to evaluate the relations between gender health inequalities and economic prosperity in the Organisation for Economic Co-operation and Development (OECD) countries. The groups included health indicators in the specification of men, women and gender inequalities: life expectancy, causes of mortality and avoidable mortality. The variable determining the economic prosperity was represented by the Gross Domestic Product (GDP). The analytical processing included descriptive analysis, analysis of differences and analysis of relationships. The regression analysis was presented as the main output of the research. Most of the significant gender differences in health showed a more positive outcome for women. It is possible to identify a certain relation between gender health inequalities and economic prosperity. If there is some reduction in gender inequalities in health, the economic prosperity will increase. The reduction seems to be more effective on the part of men than women. The output of the cluster analysis showed the relations of indicators evaluating the inequalities and the prosperity. The countries such as Luxembourg, Norway or Switzerland showed very positive outputs, on the other hand, the countries with a potential for the improvement are Lithuania, Latvia or Estonia. Overall, the policies should focus on reducing the inequalities in avoidable mortality as well as reducing the frequent diseases in younger people.

Provision of health care services and regional diversity in Germany: insights from a Bayesian health frontier analysis with spatial dependencies

The German health care system is among the most patient-oriented systems in Europe. Nevertheless, distinct utilisation patterns, access barriers due to socio-economic profiles, and potentials of misallocation of medical resources lead to disparities in the provision of health care services. We analyse how a possible over- and undersupply of services and the utilisation of and the access to the health care system relate to regional variations in the population's well-being. For this purpose, we employ a recent Bayesian stochastic frontier approach that allows for spatial dependence structures. Our results indicate that patient migration plays an important role in contributing to regional differences in the utilisation of the medical infrastructure. As a consequence, policy should take spatial patterns of health care utilisation into account to improve the allocation of medical resources.

Going beyond health efficiency: What really matters?

Both citizens and policymakers demand the best possible results from a country's healthcare system. It is of utmost importance to accurately and objectively assess the efficiency of a healthcare system and to note the key indicators, where resources are lost, and possibilities for improvement. This paper evaluates the efficiency of health systems in 38 countries, mainly members of the Organization for Economic Co-operation and Development, using data envelopment analysis (DEA). In the first stage, bootstrapped Ivanovic distance is used to generate weights for the indicators, thus taking into consideration different country's goals, but not to the extent of reducing the possibility of comparison. The analysis shows that human resources are the most important health system resource and countries should pay special attention to developing and employing competent medical workers. The reorganization of human resources and the funds allocated to them could also increase efficiency. The second stage examines environmental indicators to find the causes of inefficiency. No proof is found that any one basic health system funding model produces better health outcomes than the others. Obesity is identified as a major issue.

Technical and scale efficiency of provincial health systems in China: a bootstrapping data envelopment analysis

OBJECTIVE

With escalating health expenditures and increasing health needs, improving health system performance has become imperative in China and internationally. The objective of this study is to examine the efficiency of China's health system and to understand the underlying causes of the variation in efficiency across provinces.

SETTING

A system-wide perspective is adopted, focusing on performance in maternal health, child health and non-communicable diseases (NCDs) in the 31 provinces of mainland China during 2015.

METHODS

Analyses were performed using bootstrapping data envelopment technique. Health outcomes were measured by infant survival rates, maternal survival rates and healthy life years calculated only considering NCDs. Health inputs were measured using health expenditure, and density of medical personnel and hospital beds. The model also examined the impact of environmental factors on health system efficiency.

RESULTS

Due to wide-spread scale inefficiency in the country, the average bias-corrected overall technical efficiency (OTE) was 0.8022 (95% CI values ranging from 0.7251 to 0.8492). Socioeconomic status, hospitalisation rate and share of out-of-pocket expenditures were significant determinants of OTE. Nearly 60% of the provinces operated at a decreasing return to scale, meaning that a gain in efficiency could be achieved only through downsizing the scale of operation.

CONCLUSIONS

Given the pervasive nature of diminishing returns across provinces, health policy makers must explore the optimum operational scale which is people-centred and focused on prevention, rather than on treatment, of diseases. Moreover, due consideration should be afforded to social determinants of health and health financing arrangements to complement health-sector based reforms and meet the ambitious goals of the Healthy China 2030 Plan.

Potential determinants of health system efficiency: Evidence from Latin America and the Caribbean

This paper examines the levels of health system efficiency and their possible determinants across Latin American and Caribbean (LAC) countries using national-level data for those countries, as well as for other emerging and developed countries. The data are analyzed using data envelopment analyses and econometric advances that yield reliable estimations of the relationship between system efficiency and its potential determinants. We find that there is substantial room for efficiency improvements in the health system of most LAC countries. For example, LAC countries could improve life expectancy at birth by about five years on average at current public spending levels if they followed best practices. Furthermore, the paper assesses what factors amenable to policy act as the main possible levers for some countries to be able to translate a given level of health financing into better performance on access to care and health outcomes. Our econometric analyses suggest that efforts to increase health system efficiency could be focused in a few key policy areas associated with broader access to health services and better outcomes. These areas include general governance aspects, in addition to improvements in specific dimensions of the quality of health system institutions, notably stronger reliance on results-based management in the production of healthcare goods and services.

Research on the Efficiency of Local Government Health Expenditure in China and Its Spatial Spillover Effect

The efficiency of the local government health expenditure (GHE) in China determines the level of public health services. However, the local government does not pay much attention to that efficiency, though the scale of local GHE is increasing. In this paper, first, we use the data envelopment analysis (DEA) method to measure the static overall efficiency of the local government health expenditure (GHE) in each region of China from 2007 to 2016. Then, based on the spatial statistical theory, global and local spatial Moran’s I value is utilized to investigate its spatial correlation and spatial agglomeration phenomenon. Finally, the spatial spillover effect (SSE) of the static overall efficiency of local GHE in each region is measured by constructing a spatial Durbin model (SDM). It is demonstrated that there are significant differences in the efficiency of the local GHE between different regions of China. In addition, it is shown that Moran’s I value of the static overall efficiency of the local GHE from 2007 to 2016 is positive. It passed the test of the 5% significance level, indicating that there is a positive spatial correlation between the efficiency of the local GHE and a spatial spillover effect. On the other hand, the decomposition of the SDM reveals that the proportion of GHE to financial expenditure, gross domestic product (GDP) per capita, and population density have a positive effect on the efficiency of the local GHE. Hence, their growth will improve the GHE efficiency in the local region and neighboring regions. In contrast, the proportion of urban population, illiteracy, and fiscal decentralization have a negative effect. Thus, their growth will decrease the GHE efficiency in the local region and neighboring regions. The results are discussed and suggestions are given based on the analysis in this paper. The main contribution of this work is to consider the spatial spillover effect in terms with realistic meaning. The results obtained can be used as a reference for optimizing the structure and improving the efficiency of government health inputs. It breaks the government’s GDP-only theory-based assessment system and helps to improve it by assessing the GHE efficiency.

Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems

In recent years, most countries around the world have struggled with the consequences of budget cuts in health expenditure, obliging them to utilize their resources efficiently. In this context, performance evaluation facilitates the decision-making process in improving the efficiency of the healthcare system. However, the performance evaluation of many sectors, including the healthcare systems, is, on the one hand, a challenging issue and on the other hand a useful tool for decision- making with the aim of optimizing the use of resources. This study proposes a new methodology comprising two well-known analytical approaches: (i) data envelopment analysis (DEA) to measure the efficiencies and (ii) data science to complement the DEA model in providing insightful recommendations for strategic decision making on productivity enhancement. The suggested method is a first attempt to combine two DEA extensions: flexible measure and cross-efficiency. We develop a pair of benevolent and aggressive scenarios aiming at evaluating cross-efficiency in the presence of flexible measures. Next, we perform data mining cluster analysis to create groups of homogeneous countries. Organizing the data in similar groups facilitates identifying a set of benchmarks that perform similarly in terms of operating conditions. Comparing the benchmark set with poorly performing countries we can obtain attainable goals for performance enhancement which will assist policymakers to strategically act upon it. A case study of healthcare systems in 120 countries is taken as an example to illustrate the potential application of our new method.

Does happiness matter to health system efficiency? A performance analysis

BACKGROUND

The main objective of this study is to assess the performance of the global health system, emphasising the contribution of people's happiness to health system efficiency across countries. Technical efficiency (TE) scores are estimated using the output-oriented variable returns to scale (VRS) data envelopment analysis (DEA) model based on the input measures: health expenditure, labour, hospital beds and education, and the output measures: healthy life expectancy and inverse mortality index. The efficiency scores are regressed against three explanatory variables: happiness index, population density, and healthcare share of gross domestic product (GDP). The analysis involved 121 selected countries using double bootstrap DEA as proposed by Simar, L., Wilson, P.W J Econ 136:1‑34, 2007.

RESULTS

The bootstrap truncated regression indicates that happiness is one of the factors that contributes significantly to health system efficiency. The study also revealed that the selected health systems perform well, on average, in terms of population density and healthcare share of GDP.

CONCLUSIONS

In addition to improving the economic standard of living, policy-makers should also consider ways to increase the happiness and well-being of society. Policies focusing on well-being and happiness can lead to improved well-being and improved health outcomes, which may ultimately reduce the healthcare burden and enhance healthcare performance.

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.

A performance analysis of Brazilian public health: TOPSIS and neural networks application

Purpose

The purpose of this paper is to estimate the performance of Brazilian hospitals’ services and to examine contextual variables in the socioeconomic, demographic and institutional domains as predictors of the performance levels attained.

Design/methodology/approach

The paper applied a two-stage approach of the technique for order preference by similarity to the ideal solution (TOPSIS) in public hospitals in 92 Rio de Janeiro municipalities, covering the 2008–2013 period. First, TOPSIS is used to estimate the relative performance of hospitals in each municipality. Next, TOPSIS results are combined with neural networks in an effort to originate a performance model with predictive ability. Data refer to hospitals’ outpatient and inpatient services, based on frequent indicators adopted by the healthcare literature.

Findings

Despite a slight performance increase over the period, substantial room for improvement is observed. The most important performance predictors were related to the demographic and socioeconomic status (area in square feet and GDP per capita) and to the juridical nature and type of ownership of the healthcare facilities (number of federal and private hospitals).

Practical implications

The results provide managerial insights regarding the performance of public hospitals and opportunities for better resource allocation in the healthcare sector. The paper also considers the impact of external socioeconomic, demographic and institutional factors on hospitals’ performance, indicating the importance of integrative public health policies.

Originality/value

This study displays an innovative context for applying the two-stage TOPSIS technique, with similar efforts not having been identified in the healthcare literature.

Prediction and Decomposition of Efficiency Differences in Chinese Provincial Community Health Services

The objective of this paper is to analyze the provincial efficiency of the Chinese community health care service and its differences. This study allows us to predict the provincial differences in the efficiency of the Chinese community health care service from 2017 to 2026. This study analyzes the contributions of inter-regional and intra-regional differences in the total efficiency difference. We use the Super-SBM (Slacks-based Model) data envelopment analysis (DEA) model, Grey Model GM (1,1) for grey prediction, and the group-based Theil index decomposition method to study Chinese provincial panel data from 2008 to 2016. Results show that a fluctuating trend existed in the average provincial efficiency of community health services from 2008 to 2016. The community health services in a considerable number of provincial areas were inefficient. This study also reveals that there existed apparent inter-provincial differences in efficiency in Chinese community health services. The inter-provincial differences of the efficiency of Chinese community health services revealed by the Theil index declined at a relatively slow pace. With regard to the provincial efficiency difference of the Chinese community health service, the intra-regional efficiency difference is the most important structural reason for the overall efficiency difference, which explains the overall difference to a large extent. The inter-regional efficiency difference among the eastern, central, and western regions becomes the secondary structural reason, which should not be ignored. In conclusion, focus should be put on restructuring the investments into medical resources for community health service in each Chinese province. More attentions should be put into narrowing the inter-regional efficiency differences of the Chinese provincial community health service. The strategies targeted at reducing the inter-regional efficiency differences should not be ignored, so as to facilitate the improvement of overall efficiency of the Chinese community health service.

Costs and efficiency of gatekeeping under varying numbers of general practitioners

We study the relationship between gatekeeping on one hand and costs as well as efficiency on the other hand. We do this with special focus on the relative amount of general practitioners in the system when compared with all practitioners. Data collected between 2002 and 2011 by The Organization for Economic Co-operation and Development on 34 countries were analyzed. Of those, 18 countries have gatekeeping systems while 16 do not. The association between gatekeeping and health care costs was examined with regression analysis. Efficiency was assessed with data envelopment analysis. Finally, the efficiency assessments were analyzed with regression techniques to examine if gatekeeping and/or the ratio of GPs to all practitioners was associated with efficiency. Point estimates indicate that total costs tend to be lower in systems where GPs act as gatekeepers. However, efficiency is slightly lower where gatekeeping exists. Neither of these results is statistically significant at the 95% confidence level. There is also indication that the efficiency of a gatekeeping system increases with increased amount of GPs. When GPs are over 30% of practitioners, gatekeeping countries have more efficient health care systems than their counterparts. Consistent with other studies, we estimate income elasticity of health care demand to be 1.12, suggesting that those societies consider health care to be a luxury good.

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.

Improving health care service provision by adapting to regional diversity: An efficiency analysis for the case of Germany

The provision of health care in Germany exhibits sizeable geographic variation with a heterogeneous allocation of medical services in rural and urban areas. Furthermore, distinct utilisation patterns and access barriers due to the socio-economic environment might cause inefficiencies in the provision of health care services. Accordingly, an improved understanding of factors governing inefficiencies in health care provision is likely to benefit an efficient spatial allocation of health care infrastructure. We analyse how socio-economic factors influence the regional distribution of (in)efficiencies in the provision of health care services by means of a stochastic frontier analysis. Our results highlight that regional deprivation relates to inefficient provision of health care services. As a consequence, policies should also consider socio-economic conditions to improve the allocation of medical services and overall health.

The impact of healthcare reform on the efficiency of public county hospitals in China

BACKGROUND

The new round of Healthcare Reform in China has implemented over 3 years since 2009, and promoted greatly the development of public county hospitals. The purpose of this study is to evaluate county hospitals efficiency before and after the healthcare reform, and further assess the reform effectiveness through the comparative analysis of the efficiency.

METHODS

Data envelopment analysis (DEA) was employed to calculate the efficiency of 1105 sample hospitals which were selected from 31 provinces of China, also, Tobit regression was used to regress against those main external environmental factors.

RESULTS

Our results show that the scales and amounts of service of hospitals had increased sharply, however, the efficiency was relatively low and decreased slightly from 2008 to 2012. Thirteen (1.18%) in 2008 and six (0.54%) hospitals in 2012 were defined as technically efficient, and the average scores were 0.2916 and 0.2503. The technical efficiency average score of the post-reform was significantly less than that of the pre-reform (p < 0.001), and the score of eastern region was highest and the western was lowest among three regions of China.

CONCLUSIONS

It suggests the reform had not well improved county hospital efficiency although hospitals have reached a fair developing scale, and the corresponding policies and measures should be put into effect for improving efficiency, especially in the level and structure of health investment, operation and supervision mechanism of county hospitals.

Integrated Analysis of Healthcare Efficiency: A Systematic Review

Data Envelopment Analysis (DEA) has been used as a performance measurement tool in efficiency assessment of healthcare systems. However, over the years, researchers and health practitioners presented the theoretical and methodological limitations of DEA that limits the full view of healthcare efficiency. To address these limitations, a commonly used strategy is to integrate other statistical methods and techniques with DEA to provide better efficiency evaluation. This paper reviews 57 studies with DEA applications in the healthcare industry to illustrate the integrated analysis of healthcare efficiency. With DEA as the central method, regression models in conjunction with statistical tests are commonly used. Input-oriented radial DEA models using predominantly capacity-related inputs and activity-related outputs and following either constant return to scale or variable return to scale assumptions are mostly applied to measure healthcare efficiency.

Service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania

Objective

To evaluate the service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania.

Methods

Using existing data from service provision assessments of the health systems of the 10 study countries, we calculated a service readiness index for each of 8443 health facilities. This index represents the percentage availability of 50 items that the World Health Organization considers essential for providing health care. For our analysis we used 37–49 of the items on the list. We used linear regression to assess the independent explanatory power of four national and four facility-level characteristics on reported service readiness.

Findings

The mean values for the service readiness index were 77% for the 636 hospitals and 52% for the 7807 health centres/clinics. Deficiencies in medications and diagnostic capacity were particularly common. The readiness index varied more between hospitals and health centres/clinics in the same country than between them. There was weak correlation between national factors related to health financing and the readiness index.

Conclusion

Most health facilities in our study countries were insufficiently equipped to provide basic clinical care. If countries are to bolster health-system capacity towards achieving universal coverage, more attention needs to be given to within-country inequities.