The determinants of efficiency in the Canadian health care system

Identifying and prioritizing inefficiency causes in Iran's health system

BACKGROUND

Enhancing efficiency is crucial in addressing the escalating scarcity of healthcare resources. It plays a pivotal role in achieving Universal Health Coverage (UHC), with the ultimate goal of ensuring health equity for all. A fundamental strategy to bolster efficiency involves pinpointing the underlying causes of inefficiency within the healthcare system through empirical research. This study aimed to determine and prioritize the causes of inefficiency in Iran's health system.

METHODS

This mixed-method study comprised three phases. The initial phase involved identifying the causes of inefficiency through a comprehensive literature review of relevant studies published between January 1, 2010, to January 1, 2021. The causes were then aligned and prioritized using criteria derived from the literature and expert opinion. Finally, the identified causes were ranked based on their significance using Multiple-Criteria Decision Analysis (MCDA).

RESULTS

From an initial pool of 307 causes of inefficiency, they were reduced to 121 causes in the first round of screening which were categorized into 13 thematic topics. The second screening process further narrowed the list to 48 causes. Among these, the leading causes of inefficiency included the inadequate supply and unequal distribution of hospital beds, the overuse of health services, and the mismanagement of the health workforce. In contrast, the use of traditional treatment methods was determined to be the least significant factor contributing to inefficiency.

CONCLUSION

This study identified key inefficiencies in Iran's health system, such as resource misallocation, overuse of services, and workforce mismanagement. Addressing these issues is essential for optimizing resource utilization, enhancing service delivery, and achieving UHC. The findings suggest that policymakers should prioritize reforms in hospital bed distribution, implement strategies to reduce unnecessary health service use, and strengthen human resource management. Additionally, targeted policies that focus on decentralizing healthcare decision-making and enhancing primary care could significantly improve system-wide efficiency. Future research should evaluate the effectiveness of these interventions and explore the role of digital health solutions in mitigating identified inefficiencies.

Public healthcare efficiency in India: Estimates and determinants using two stage DEA approach

BACKGROUND

Nearly 400 million Indians (30 % of the total population) lack any financial protection for health which leads to very high out of pocket expenditure. In India more than 90 million people spend 10-25 % of household expenses on healthcare. This is a serious threat to Sustainable Development Goal 3, which aims at providing universal health coverage along with protection from catastrophic spending on health.

AIM

The aim of this paper is to estimate the efficiency and determinants of public health in India at subnational level.

METHODS

To estimate the efficiency of public healthcare, input oriented bias corrected DEA model has been used. In this model life expectancy at birth and infant survival rate have been treated as outputs. Public health spending and per capita income are treated as inputs. In the second stage Tobit regression is used to analyse the determinants of efficiency.

RESULTS

The mean bias corrected efficiency score across Indian states is 0.60, implying that on average there is a 40 % inefficiency in public healthcare in India. Maharashtra and Mizoram are the most and least efficient states with efficiency score of 0.921 and 0.218, respectively. Fourteen states have efficiency scores less than 0.60, two states have efficiency score of 0.60 and 15 states have the efficiency score greater than 0.60. Socio economic factors outweigh the medical factors in determining the public healthcare efficiency in India.

CONCLUSION

There are 40 % inefficiencies in public health in India implying significant wastages in public health. By improving public health efficiency, there would be savings of 48 % in terms of government expenditure on health per capita. It will also improve infant survival rate by 27.19 % and life expectancy by 20.65 %.

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.

A systematic review of reviews on the advantages of mHealth utilization in mental health services: A viable option for large populations in low-resource settings

Global mental health services face challenges such as stigma and a shortage of trained professionals, particularly in low- and middle-income countries, which hinder access to high-quality care. Mobile health interventions, commonly referred to as mHealth, have shown to have the capacity to confront and solve most of the challenges within mental health services. This paper conducted a comprehensive investigation in 2024 to identify all review studies published between 2000 and 2024 that investigate the advantages of mHealth in mental health services. The databases searched included PubMed, Scopus, Cochrane and ProQuest. The quality of the final papers was assessed and a thematic analysis was performed to categorize the obtained data. 11 papers were selected as final studies. The final studies were considered to be of good quality. The risk of bias within the final studies was shown to be in a convincing level. The main advantages of mHealth interventions were categorized into four major themes: 'accessibility, convenience and adaptability', 'patient-centeredness', 'data insights' and 'efficiency and effectiveness'. The findings of the study suggested that mHealth interventions can be a viable and promising option for delivering mental health services to large and diverse populations, particularly in vulnerable groups and low-resource settings.

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.

Analysis of Centralized Efficiency Improvement Practices in Australian Public Health Systems

Aim

Analysis of centralized efficiency improvement practices in Australian public health systems.

Introduction

Public health systems seek to maximize outcomes generated for resources used through efficiency improvement (EI) in response to funding and demand pressures. Despite this focus, evidence for EI approaches at the whole-of-system level is lacking in the literature. There is an urgent need for evidence-based approaches to centralized EI to address these pressures. This study aims to address this gap by answering the research question "How is EI conceptualized and managed by central public health system management entities in Australia?".

Material and Methods

Document analysis was selected due to its suitability for systematically searching and appraising health system documentation, with this study following Altheide's approach focusing on whole-of-system strategic plan and management framework documents originating from Australian public health organizations.

Results

Conceptualization of efficiency varied substantially with no consistent definition identified, however common attributes included resource use, management, service and delivery. Forty-two of 43 documents contained approaches associated with improving efficiency at the whole of system level.

Discussion

While no comprehensive framework for centralized EI was evident, we identified nine core approaches which together characterize centralized EI. Together these approaches represent a comprehensive evidence-based approach to EI at the whole of system level.

Conclusion

The approaches to whole-of-system EI identified in this study are likely to be highly transferable across health systems internationally with approaches including strategic priority setting, incentivization, performance support, use of EI evidence, digital enablement and workforce capability development.

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.

Efficiency Improvement Strategies for Public Health Systems: Developing and Evaluating a Taxonomy in the Australian Healthcare System

INTRODUCTION

As demand for healthcare continues to grow, public health systems are increasingly required to drive efficiency improvement (EI) to address public service funding challenges. Despite this requirement, evidence of EI strategies that have been successful applied at the whole-of-system level is limited. This study reports the development, implementation and evaluation of a novel taxonomy of EI strategies used in public health systems to inform systemwide EI models.

MATERIALS AND METHODS

The public health system in New South Wales, Australia, operates a centralised EI model statewide and was the setting for this study. An audit of EI strategies implemented in the NSW Health system between July 2016 and June 2019 was used to identify all available EI strategies within the study timeframe. A content management approach was applied to audit the strategies, with each strategy coded to an EI focus area. Codes were clustered according to similarity, and category names were assigned to each cluster to form a preliminary taxonomy. Each category was defined and examples were provided. The resulting taxonomy was distributed and evaluated by user feedback survey and pre-post study to assess the impact on EI strategy distribution.

RESULTS

A total of 1127 EI strategies were identified and coded into 263 unique strategies, which were clustered into nine categories to form the taxonomy of EI strategies. Categories included the following: non-clinical contracts and supplies; avoided and preventable activity; clinical service delivery and patient outcomes; finance and operations; recruitment, vacancies and FTE; staffing models; leave management; staff engagement and development; premium staffing; and clinical contracts and supplies. Evaluative findings revealed a perceived reduction in the duplication of EI work, improved access to EI knowledge and improved engagement with EI processes when using the taxonomy. The taxonomy was also associated with wider use of EI strategies.

CONCLUSIONS

Whole-of-system EI is an increasing requirement. Using a taxonomy to guide systemwide practice appears to be advanta-geous in reducing duplication and guiding practice, with implications for use in health systems internationally.

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.

Driving Efficiency Improvement (EI): Exploratory Analysis of a Centralised Model in New South Wales

Introduction

Public healthcare systems face rising demand coupled with reducing funding growth rates, necessitating ongoing approaches to efficiency improvement (EI). Centrally coordinated EI approaches l may support EI leaders, yet few such approaches exist internationally. This study provides evidence to inform system-wide EI by harnessing understanding of the perceptions, role demands and support requirements of key EI stakeholders in the centralised EI model implemented in New South Wales.

Methods

A purposive sample of key informants within NSW Health with responsibility for EI in their organisation were invited to participate. Semi-structured interviews were conducted, recorded and transcribed. A thematic analysis was undertaken using a theoretical deductive approach.

Results

Seventeen respondents participated who occupied EI leadership roles in metro (8) and rural (6) health services as well as non-clinical support (3) services. Four primary themes emerged on the perceptions and experiences of participants in 1. holding a unique skillset which enables them to undertake EI; 2. inheriting EI accountabilities as additional duties rather than holding dedicated EI roles; 3. the importance of senior support for EI success; and 4. feelings of isolation in undertaking EI. An additional underpinning theme that EI is not well conceptualized in public health systems also emerged, whereby EI planners felt that frontline staff generally do not consider efficiency as a component of their duties.

Conclusion

EI leaders provide points of authority, experience and influence across organisations within public health systems. This study finds that EI planners possess a unique skillset, can feel isolated both within their health organisation and within the broader public health system and believe that EI is poorly conceptualized amongst health staff. Centralised support for EI stakeholders across a public health system can promote knowledge sharing and capability development. Addressing the role and support requirements of key EI stakeholders is essential.

Supporting efficiency improvement in public health systems: a rapid evidence synthesis

BACKGROUND

Public health systems internationally are under pressure to meet increasing demand for healthcare in the context of increasing financial resource constraint. There is therefore a need to maximise health outcomes achieved with public healthcare expenditure. This paper aims to establish and synthesize the contemporary evidence base for approaches taken at a system management level to improve efficiency.

METHODS

Rapid Evidence Assessment (REA) methodology was employed. A search strategy was developed and applied (PUBMED, MEDLINE) returning 5,377 unique titles. 172 full-text articles were screened to determine relevance with 82 publications included in the final review. Data regarding country, study design, key findings and approaches to efficiency improvement were extracted and a narrative synthesis produced. Publications covering health systems from developed countries were included.

RESULTS

Identified study designs included policy reviews, qualitative reviews, mixed methods reviews, systematic reviews, literature reviews, retrospective analyses, scoping reviews, narrative papers, regression analyses and opinion papers. While findings revealed no comprehensive frameworks for system-wide efficiency improvement, a range of specific centrally led improvement approaches were identified. Elements associated with success in current approaches included dedicated central functions to drive system-wide efficiency improvement, managing efficiency in tandem with quality and value, and inclusive stakeholder engagement.

CONCLUSIONS

The requirement for public health systems to improve efficiency is likely to continue to increase. Reactive cost-cutting measures and short-term initiatives aimed only at reducing expenditure are unlikely to deliver sustainable efficiency improvement. By providing dedicated central system-wide efficiency improvement support, public health system management entities can deliver improved financial, health service and stakeholder outcomes.

Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis

BACKGROUND

Improving health system efficiency is a key strategy to increase health system performance and accelerate progress towards Universal Health Coverage. In 2013, Kenya transitioned into a devolved system of government granting county governments autonomy over budgets and priorities. We assessed the level and determinants of technical efficiency of the 47 county health systems in Kenya.

METHODS

We carried out a two-stage data envelopment analysis (DEA) using Simar and Wilson's double bootstrap method using data from all the 47 counties in Kenya. In the first stage, we derived the bootstrapped DEA scores using an output orientation. We used three input variables (Public county health expenditure, Private county health expenditure, number of healthcare facilities), and one outcome variable (Disability Adjusted Life Years) using 2018 data. In the second stage, the bias corrected technical inefficiency scores were regressed against 14 exogenous factors using a bootstrapped truncated regression.

RESULTS

The mean bias-corrected technical efficiency score of the 47 counties was 69.72% (95% CI 66.41-73.01%), indicating that on average, county health systems could increase their outputs by 30.28% at the same level of inputs. County technical efficiency scores ranged from 42.69% (95% CI 38.11-45.26%) to 91.99% (95% CI 83.78-98.95%). Higher HIV prevalence was associated with greater technical inefficiency of county health systems, while higher population density, county absorption of development budgets, and quality of care provided by healthcare facilities were associated with lower county health system inefficiency.

CONCLUSIONS

The findings from this analysis highlight the need for county health departments to consider ways to improve the efficiency of county health systems. Approaches could include prioritizing resources to interventions that will reduce high chronic disease burden, filling structural quality gaps, implementing interventions to improve process quality, identifying the challenges to absorption rates and reforming public finance management systems to enhance their efficiency.

An exploration of potential output measures to assess efficiency and productivity for labour and birth in Australia

Background

In maternity services, as in other areas of healthcare, increasing emphasis is placed on improving “efficiency” or “productivity”. The first step in any efficiency and productivity analysis is the selection of relevant input and output measures. Within healthcare quantifying what is produced (outputs) can be difficult.

The aim of this paper is to identify a potential output measure, that can be used in an assessment of the efficiency and productivity of labour and birth in-hospital care in Australia and to assess the extent to which it reflects the principles of woman-centred care.

Methods

This paper will survey available perinatal and maternal datasets in Australia to identify potential output measures; map identified output variables against the principles of woman-centred care outlined in Australia’s national maternity strategy; and based on this, create a preliminary composite outcome measure for use in assessing the efficiency and productivity of Australian maternity services.

Results

There are significant gaps in Australia’s maternity data collections with regard to measuring how well a maternity service is performing against the values of respect, choice and access; however safety is well measured. Our proposed composite measure identified that of the 63,215 births in Queensland in 2014, 67% met the criteria of quality outlined in our composite measure.

Conclusions

Adoption in Australia of the collection of woman-reported maternity outcomes would substantially strengthen Australia’s national maternity data collections and provide a more holistic view of pregnancy and childbirth in Australia beyond traditional measure of maternal and neonate morbidity and mortality. Such measures to capture respect, choice and access could complement existing safety measures to inform the assessment of productivity and efficiency in maternity care.

Empirical Analysis of Factors Influencing Healthcare Efficiency among Emerging Countries

Numerous factors, including inefficient utilization of healthcare resources have been attributed to the poor health outcome. The study aims to compare the efficiency of health expenses and its determining factors in the emerging economies based on their income levels. Data for the study is extracted from the World Bank’s World Development Indicators for 21 countries covering the period of 2000 to 2018. Analysis of the research involves two stages. Stage one computes the efficiency scores, whereas second stage examines factors affecting health efficiency by employing the Tobit regression and Simar-Wilson regression test to confirm the results. The Tobit result shows that research and development (R&D) and physicians enhanced health efficiency at the main panel, lower-middle-income, upper-middle-income, and high-income countries. Corruption remained negative with education showing mixed results. The interaction between research and development and physicians increases health efficiency in all the panels. Health research must be a policy focus if efficiency is to be achieved by the emerging economies.

Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis

BACKGROUND

General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17.

METHODS

We undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1.

RESULTS

The average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49% (95% CI, 44-54%), 69% (95% CI, 65-74%) and 70% (95% CI, 65-75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance.

CONCLUSION

The 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3439) less staff and 31% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

Assessment of health technical efficiency in the cities of the Rota dos Bandeirantes health region of the state of São Paulo, Brazil

Although administrators unanimously agree that the Brazilian Unified Health System (SUS) is underfunded, it is also unanimous that there are problems in the efficiency of expenditures management. From this perspective, this study assessed the health technical efficiency in the seven cities of the Rota dos Bandeirantes health region of the state of São Paulo, Brazil, from 2009 to 2012, through the Health Technical Efficiency Index. This index includes structure and results indicators, mainly from the goals and indicators agreement system, and it is collected from the database of the SUS Informatics Department. It was identified that only one city reached high health technical efficiency, while the other cities presented low efficiency. It was concluded that cities with higher income available and higher per capita expenditures achieved the best health indicator results and, therefore, better health technical efficiency indexes. However, some cities, even though small in structure, obtained better results than neighboring cities, which shows structure management efficiency. Thus, the resource represented an essential condition for efficiency, however not sufficient.

Measuring the efficiency of health systems in Asia: a data envelopment analysis

OBJECTIVE

This study aims to estimate the technical efficiency of health systems in Asia.

SETTINGS

The study was conducted in Asian countries.

METHODS

We applied an output-oriented data envelopment analysis (DEA) approach to estimate the technical efficiency of the health systems in Asian countries. The DEA model used per-capita health expenditure (all healthcare resources as a proxy) as input variable and cross-country comparable health outcome indicators (eg, healthy life expectancy at birth and infant mortality per 1000 live births) as output variables. Censored Tobit regression and smoothed bootstrap models were used to observe the associated factors with the efficiency scores. A sensitivity analysis was performed to assess the consistency of these efficiency scores.

RESULTS

The main findings of this paper demonstrate that about 91.3% (42 of 46 countries) of the studied Asian countries were inefficient with respect to using healthcare system resources. Most of the efficient countries belonged to the high-income group (Cyprus, Japan, and Singapore) and only one country belonged to the lower middle-income group (Bangladesh). Through improving health system efficiency, the studied high-income, upper middle-income, low-income and lower middle-income countries can improve health system outcomes by 6.6%, 8.6% and 8.7%, respectively, using the existing level of resources. Population density, bed density, and primary education completion rate significantly influenced the efficiency score.

CONCLUSION

The results of this analysis showed inefficiency of the health systems in most of the Asian countries and imply that many countries may improve their health system efficiency using the current level of resources. The identified inefficient countries could pay attention to benchmarking their health systems within their income group or other within similar types of health systems.

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.

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.