Efficiency and productivity of health systems in prevention and control of non-communicable diseases in China, 2008-2015

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 %.

Efficiency evaluation, regional technological heterogeneity and determinant of total factor productivity change in China's healthcare system

Enhancing efficiency and productivity in countries' healthcare systems is a global challenge. The Chinese government invested huge resources to improve the efficiency and productivity of the healthcare system across the country. To assess the success of the mission above, this research utilized DEA-SBM Meta frontier analysis alongside the Malmquist Productivity Index. These methodologies were employed to gauge Efficiency, production technology heterogeneity, and productivity of healthcare systems change across 31 mainland Chinese provinces and four distinct geographical regions throughout the study period spanning from 1997 to 2022. Results revealed that the mean efficiency score of China's healthcare system is 0.7672. It indicates a growth potential of 23.28 percent in the operational efficiency of healthcare systems. The eastern region's efficiency level (0.86917) is higher among all four regions. Zhejiang, Shandong, and Guangdong are the top three healthcare-efficiency performers. The technology gap ratio indicates that eastern regions witnessed a high TGR (0.9909), showing the country's attainment of superior healthcare technologies. Beijing, Guangdong, Shanghai, Tianjin, and Zhejiang witnessed higher TGR values among all 31 mainland Chinese provinces. The total factor productivity index of the healthcare system witnessed a slight growth of 0.33%, with an average MI score of 1.0033. Efficiency change (EC) was found to be the main determinant of TFPC as technology change TC is less than EC. Moreover, the MI score of the Western region (1.033) is higher than the corresponding Eastern, northeastern, and central regions. Guizhou, Anhui, and Yunnan were found to be the top three performers in TFPC growth. Finally, the Kruskal-Wallis test confirmed the statistically significant difference among 4 Chinese regions for the healthcare system's efficiency, TFPC, and TGR.

The allocation and utilization efficiency of hospital beds in Sichuan Province, China

OBJECTIVE

To analyze the allocation and utilization efficiency of hospital beds in Sichuan Province, China, and to provide a scientific basis for improving the rational allocation and efficient utilization.

METHODS

The supply and demand balance method, health resource agglomeration degree (HRAD), bed efficiency index and bed utilization model were used to evaluate the allocation and utilization efficiency of hospital beds in Sichuan Province from 2017 to 2021.

RESULTS

The number of hospital beds per 1000 population in Sichuan Province increased from 4.97 in 2017 to 5.94 in 2021. The overall supply and demand ratio of hospital beds in Sichuan Province is between 0.85 and 1.01, and the supply and demand situation is a basically balanced situation. The HRAD of hospital beds in Ya'an, Aba, Ganzi and Liangshan is <1, indicating that the equity of hospital beds by geography in these regions is low. The difference between HRAD and population agglomeration degree (PAD) in 9 regions, including Deyang, Aba, Ganzi and Liangshan, is <0, indicating that there are insufficient hospital beds in these areas relative to the agglomerated population. The bed efficiency index of hospital beds in 17 regions, including Chengdu, Zigong, Aba and Ganzi, are all <1, which means that hospital beds are operating with low efficiency. The bed utilization model of Panzhihua is efficiency type, that of Zigong, Deyang and Ziyang is pressure bed type, and that of Nanchong and Ya'an is idle type.

CONCLUSION

The hospital bed allocation in Sichuan Province is relatively good, and the supply and demand situation is in a basically balanced situation. The hospital bed allocation in Aba, Ganzi and Liangshan is insufficient by geography and population. The overall operational efficiency of hospital beds is low, and there are more idle and pressure bed utilization models.

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.

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

OBJECTIVE

To analyse regional differences in health resource allocation in the Chengdu-Chongqing economic circle.

DESIGN

A longitudinal analysis that collected data on health resource allocation from 2017 to 2021.

SETTING

The number of beds, health technicians, licensed (assistant) physicians, registered nurses and financial allocations per 1000 population in the 42 regions of Chengdu-Chongqing economic circle were used for the analysis.

METHODS

The entropy weight technique for order preference by similarity to an ideal solution (TOPSIS) method and the rank sum ratio (RSR) method were used to evaluate the health resource allocation.

RESULTS

The number of licensed (assistant) physicians per 1000 population in the Chengdu-Chongqing economic circle (3.01) was lower than the average in China (3.04) in 2021. According to the entropy weight-TOPSIS method, Yuzhong in Chongqing had the largest C-value and the highest ranking. Jiangbei in Chongqing and Chengdu and Ya'an in Sichuan Province had higher C-values and were ranked in the top 10. Jiangjin, Hechuan, Tongnan and Zhongxian in Chongqing and Guang'an in Sichuan Province had lower C-values and were all ranked after the 30th place. According to the RSR method, the 42 regions were divided into three grades of good, medium and poor. The health resource allocations of Yuzhong, Jiangbei, Nanchuan, Jiulongpo and Shapingba in Chongqing and Chengdu and Ya'an in Sichuan Province were of good grade, those of Tongnan, Jiangjin, Yubei and Dazu in Chongqing and Guang'an and Dazhou in Sichuan Province were of poor grade, and the rest of the regions were of medium grade.

CONCLUSION

The regional differences in health resource allocation in the Chengdu-Chongqing economic circle were more obvious, the health resource allocation in Chongqing was more polarised and the health resource allocation in Sichuan Province was more balanced, but the advantaged regions were not prominent enough.

Equity and efficiency of health resource allocation in township health centers in Sichuan Province, China

OBJECTIVE

To analyze the equity and efficiency of health resource allocation in township health centers in Sichuan Province, and to provide a scientific basis for promoting the development of township health centers in Sichuan Province, China.

METHODS

The Lorenz curve, Gini coefficient and health resource density index were used to analyze the equity of health resource allocation in township health centers in Sichuan Province from 2017 to 2021, and data envelopment analysis(DEA) was used to analyze the efficiency of health resource allocation in township health centers in Sichuan Province from 2017 to 2021.

RESULTS

The Gini coefficient of health resources of township health centers in Sichuan Province is below 0.2 by population in addition to the number of beds in 2020-2021 and practicing (assistant) physicians in 2021, and the Gini coefficient of health resources of township health centers in Sichuan Province is above 0.6 by geography. The Lorentz curve of health resources of township health centers in Sichuan Province is closer to the equity line by population allocation and further from the equity line by geographical allocation. The average level of township health centers in Sichuan Province is used as the standard to calculate the health resource density standard index(W) of each region, the Ws of Panzhihua, Ganzi, Aba and Liangshan are less than 1, and the Ws of Ziyang, Neijiang, Deyang and Meishan are greater than 1. The overall efficiency of township health centers in Sichuan Province in 2017 and 2021 is 1, and the DEA is relatively effective. The overall efficiency of township health centers in Sichuan Province in 2018 and 2019 is not 1, and the DEA is relatively ineffective. The overall efficiency of all health resources in Mianyang and Ziyang is 1, and the DEA is relatively effective. The overall efficiency of all health resources in Suining, Neijiang, Yibin, Aba and Ganzi is not 1, and the DEA is relatively ineffective.

CONCLUSION

The equity of health resource allocation by population is better than that by geography in township health centers in Sichuan Province. Combining population and geographical factors, the health resource allocation of Panzhihua, Ganzi, Aba and Liangshan is lower than the average level of Sichuan Province. The efficiency of health resource allocation in township health centers in Sichuan Province is low.

Trends and disparities in non-communicable diseases in the Western Pacific region

The WHO Western Pacific region bears disproportionate deaths from non-communicable diseases (NCDs), with increased overall NCD proportional mortality over the past two decades. The disease burden of mental health increased, resulting from rapid ageing, enhanced stress, and the COVID-19 pandemic, but it was largely neglected. The highly diverse cultures, religions, political systems, socioeconomic contexts, lifestyles, and environmental factors probably have led to massive disparities across countries in NCD mortality, risk factors, and NCD management. Geographically, East Asia had the lowest NCD mortality whilst Pacific islands had the highest. Economic booms, ageing, nutrition transition, social stress, prevalent tobacco use, and fast-increasing obesity and hyperglycaemia are important drivers of NCDs. Men tended to have more adverse behavioural and metabolic risk factors. Rural residents are catching up with their urban counterparts in metabolic risk factors and conditions. Sustainable strategies tailored to NCD patterns are needed to fight the NCD epidemic and related disparities.

The trade-off between health system resiliency and efficiency: evidence from COVID-19 in European regions

The objective of this paper was to investigate the existence of a trade-off between health system resilience and the economic efficiency of the health system, using data for 173 regions in the European Union and the European Free Trade Association countries. Data Envelopment Analysis was used to measure the efficiency of regional health systems before the COVID-19 pandemic. Then, a spatial econometrics model was used to estimate whether this measure of efficiency, adjusted for several covariates, has a significant impact on regional health system resilience during the COVID-19 pandemic, measured by the number of COVID-19 deaths per hundred thousand inhabitants. The results show that COVID-19 death rates were significantly higher in regions with higher population density, higher share of employment in industry, and higher share of women in the population. Results also show that regions with higher values of the health system efficiency index in 2017 had significantly higher rates of COVID-19 deaths in 2020 and 2021, suggesting the existence of a trade-off between health system efficiency and health system resilience during the COVID-19 pandemic.

Performance evaluation of national healthcare systems in the prevention and treatment of non-communicable diseases in sub-Saharan Africa

BACKGROUND

Non-communicable diseases (NCDs) remain a major public health concern globally, threatening the achievement of sustainable development goal 3.4 (SDG 3.4), which seeks to reduce premature NCD-related deaths by one-third by 2030. According to the World Health Organization (WHO), improving the efficiency of NCD spending (i.e., maximizing the impact of every dollar spent on NCDs) is one of the strategic approaches for achieving SDG target 3.4. This study aims to assess the efficiency and productivity of NCDs spending in 34 sub-Saharan African (SSA) countries from 2015 to 2019.

METHODS

The study employed the data envelopment analysis (DEA) double-bootstrap truncated and Tobit regressions, one-stage stochastic frontier analysis (SFA) model, the Malmquist productivity index (MPI), and spatial autocorrelation analysis to estimate NCDs spending efficiency, identify the context-specific environmental factors that influence NCDs spending efficiency, evaluate total productivity change and identify its components, and assess the spatial interdependence of the efficiency scores.

RESULTS

The estimated average DEA bias-corrected NCD spending efficiency score was 87.3% (95% CI: 86.2-88.5). Additionally, smoking per capita, solid fuel pollution, alcohol use, governance quality, urbanization, GDP per capita, external funding for NCDs, and private domestic funding for NCDs healthcare services were found to be significantly associated with NCDs spending efficiency. The study also revealed a decline of 3.2% in the MPI, driven by a 10.6% technical regress. Although all countries registered growth in efficiency, except for the Central Africa Republic and DR Congo, the growth in efficiency was overshadowed by the decline in technical change. Global Moran's I test indicated the existence of significant positive spatial autocorrelation in the efficiency of NCDs spending across SSA countries.

CONCLUSION

The study underscores the importance of efficient use of resources in NCDs treatment and prevention and increased investment in NCDs research and development in achieving the SDG target 3.4.

Efficiency trends of essential public health services and possible influencing factors since the new round health reform in China: a case study from Hainan Province

Objective

This article aimed to evaluate the efficiency trends and influencing factors of essential public health services in Hainan Province after the healthcare reform launched in 2009 in China.

Methods

The efficiency of essential public health services (EPHS) at primary health institutions was assessed using data envelopment analysis (DEA), and the efficiency change was analyzed by employing the Malmquist productivity index (MPI). We used Tobit regression to identify the influence of environmental factors on the efficiency of public health services. The bootstrap method was adopted to reduce the impact of random errors on the result.

Results

The bootstrapping bias-corrected efficiency revealed that the average values of technical efficiency, pure technical efficiency, and scale efficiency were 0.7582, 0.8439, and 0.8997, respectively, which meant that the EPHS in Hainan Province were not at the most effective state. The average bias-corrected MPI was 1.0407 between 2010 and 2011 and 1.7404 between 2011 and 2012. MPIs were less than 1.0000 during other periods investigated, ranging from 0.8948 to 0.9714, indicating that the efficiency of EPHS has been decreasing since 2013. The Tobit regression showed that the regression coefficients of per capita GDP, population density, the proportion of older people aged over 65, and the proportion of ethnic minority population were 0.0286, -0.0003, -0.0316, and - 0.0041 respectively, which were statistically significant (p < 0.05).

Conclusion

There was a short-term improvement in the efficiency of EPHS in Hainan after the launch of the new round of health reform. However, this trend has not been sustained after 2013. In particular, equalized financial investment in essential public health could not fulfill the needs of poor counties. This has resulted in the inability to improve scale efficiency in some counties, which in turn has affected the improvement of overall EPHS efficiency. Therefore, to promote EPHS efficiency sustainably, it is suggested that under this model of provincial control of counties, the equity of resource allocation should be effectively improved while further advancing the technology of service delivery.

Comprehensive assessment of resources for prevention and control of chronic and non-communicable diseases in China: a cross-sectional study

OBJECTIVE

This study aims to comprehensively evaluate the resources for prevention and control of chronic and non-communicable diseases (NCDs) in China to provide a reference basis for optimising the resource allocation for prevention and control of NCDs.

METHODS

China Chronic Disease and Risk Factor Surveillance sites and National Demonstration Areas for Integrated Chronic and Non-communicable Disease Prevention and Control (NCDDA) were selected as investigation objects. In December 2021, the district (or county) resource allocation for NCD prevention and control was investigated through the NCDDA management information system. According to the index system of NCD prevention and control, 31 indicators of 6 dimensions were collected, and the weighted technique for order preference by similarity to an ideal solution, weighted rank-sum ratio and fuzzy comprehensive evaluation methods were used for comprehensive evaluation of resources for prevention and control of NCDs.

RESULTS

The 653 districts (or counties) in this study cover 22.96% of China's districts (or counties). The top three weights were full-time staff for NCD prevention and control (0.1066), the amount of funds for NCD prevention and control (0.0967), and the coverage rate of districts (or counties) establishing chronic obstructive pulmonary disease surveillance information system (0.0886). The comprehensive evaluation results for the resources for prevention and control of NCDs by the three methods were basically the same. The results of fuzzy comprehensive evaluation showed that the resource allocation in urban areas (0.9268) was better than that in rural areas (0.3257), the one in eastern region (0.9016) was better than that in central (0.3844) and western regions (0.3868), and the one in NCDDA (0.9625) was better than that in non-NCDDA (0.2901).

CONCLUSION

The resources in China for NCD prevention and control differ among different regions, which should be taken into account in future policymaking and resource allocation.

Evaluation of the allocation efficiency of medical and health resources in China's rural three-tier healthcare system

OBJECTIVES

Evaluating the efficiency of health resource allocations is critical to improving China's rural three-level health service network.

STUDY DESIGN

This was a prospective panel data study.

METHODS

Based on panel data of the medical and health resources of 31 provinces within rural China, collected from 2003 to 2020, this study uses a three-stage Data Envelopment Analysis-Malmquist index to analyze the evolution of efficiency and productivity.

RESULTS

The efficiency and productivity of county and county-level medical and health institutions rank highest, followed by township hospitals, whereas village clinics are shown to be in great need of improvement. A decline in technical advancement appears as a crucial factor exacerbating loss of factor productivity.

CONCLUSIONS

Policy makers should further optimize the efficiency of medical resource allocation and promote the coordinated development of rural health in China.

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.

Impact of the development of information society on healthcare efficiency: Empirical evidence from 31 Chinese provinces

The development of information society has deeply changed the style of the healthcare service delivery and medical information access. This study aims to investigate how the information society development affects the efficiency of healthcare system in China, and explore provincial disparities in the impact. Based on the two-stage Data Envelopment Analysis (DEA) framework, this paper uses a panel data from 31 Chinese provinces from 2014 to 2017 to estimate efficiency of healthcare service and analyze the influence of the development of information society on efficiency. With the information society index (ISI) increased from 0.423 to 0.488 during the sample period, the healthcare efficiency experienced a slight decrease from 0.892 to 0.869. Moreover, the pure technical efficiency (PTE) is much lower than the scale efficiency (SE), and thus is the key to enhance the overall technical efficiency (TE). The time-fixed Tobit regression analysis suggests that information society development leads to a significant increase in PTE, but results in a decrease in SE, and therefore has little effect on TE. Further analysis reveals that the impact differs sharply between low-efficiency and high-efficiency provinces. For the low-efficiency provinces, the TE increases significantly with the development of the information society, mainly due to a considerable increase in PTE. In contrast, the TE decreases for the high-efficiency provinces, mainly caused by a decrease in SE. This paper highlights the importance of information infrastructure investment in healthcare system and the application of emerging information technologies to breakout the time and space boundaries of healthcare services in improving overall efficiency. In inefficient provinces, it is also necessary to properly control the growth of healthcare inputs.

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

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

The Core of Healthcare Efficiency: A Comprehensive Bibliometric Review on Frontier Analysis of Hospitals

Parametric and non-parametric frontier applications are typical for measuring the efficiency and productivity of many healthcare units. Due to the current COVID-19 pandemic, hospital efficiency is the center of academic discussions and the most desired target for many public authorities under limited resources. Investigating the state of the art of such applications and methodologies in the healthcare sector, besides uncovering strategical managerial prospects, can expand the scientific knowledge on the fundamental differences among efficiency models, variables and applications, drag research attention to the most attractive and recurrent concepts, and broaden a discussion on the specific theoretical and empirical gaps still to be addressed in future research agendas. This work offers a systematic bibliometric review to explore this complex panorama. Hospital efficiency applications from 1996 to 2022 were investigated from the Web of Science base. We selected 65 from the 203 most prominent works based on the Core Publication methodology. We provide core and general classifications according to the clinical outcome, bibliographic coupling of concepts and keywords highlighting the most relevant perspectives and literature gaps, and a comprehensive discussion of the most attractive literature and insights for building a research agenda in the field.

An External Patient Healthcare Index (EPHI) for Simulating Spatial Tendencies in Healthcare Seeking Behavior

Background

Healthcare resources are always more limited compared with demand, but better matching supply with demand can improve overall resource efficiency. In countries like China where patients are free to choose healthcare facilities, over-utilization and under-utilization of healthcare resources co-exist because of unreasonable healthcare seeking behavior. However, scholarship regarding the spatial distribution of utilization for healthcare resources, resulting from unreasonable spatial tendencies in healthcare seeking, is rare.

Methods

In this article, we propose a new External Patient Healthcare Index (EPHI) to simulate the spatial distribution of utilization for healthcare resources, based on the Two-Step Floating Catchment Area (2SFCA) method, which is widely used to assess potential spatial accessibility. Instead of using individual-level healthcare utilization data which is difficult to obtain, the EPHI uses institution-level aggregated data, including numbers of inpatient/outpatient visits. By comparing the estimated utilization (based on local healthcare institution services provision) with the expected utilization (based on local population morbidity), guest patients (e.g., patients flowing in for treatment) and bypass patients (patients flowing out) can be identified. To test the applicability of this index, a case study was carried out on China's Hainan Island. The spatial tendencies of patients for inpatient and outpatient services were simulated, then incorporated with spatial access to healthcare resources to evaluate overall resource allocation efficiency, thus guiding future resource allocations and investment for policy makers and healthcare providers.

Results

The EPHI revealed that bypass activities widely exist on Hainan Island in both inpatient and outpatient care, with patients tending to travel from less developed regions with fewer healthcare resources to more highly developed regions with more healthcare resources to receive healthcare. Comparison with spatial accessibility demonstrated how bypass activities on Hainan produced an under-utilization of doctors in less developed regions and over-utilization of doctors in more developed coastal regions.

Conclusions

This case study on Hainan Island demonstrates that this new index can very clearly identify both the sources and sinks of patient spatial tendencies. Combining these results with spatial accessibility of healthcare resources, how efficiently the available supply matches the utilization can be revealed, indicating wide-ranging applicability for local governments and policymakers.

An Empirical Analysis of Income Elasticity of Out-of-Pocket Healthcare Expenditure in Mauritius

A free universal healthcare provision exists in Mauritius. Yet the share of out-of-pocket healthcare expenditure out of total household expenditure has been growing over time. This study estimates income elasticity of out-of-pocket healthcare expenditure using Mauritian household data within an Engel curve framework. In the absence of longitudinal data on out-of-pocket healthcare expenditure patterns, the study proposes the application of the pseudo-panel approach using cross-sectional Household Budget Survey waves from 1996/97 to 2017. Income elasticity of out-of-pocket healthcare expenditure is estimated to be 0.938, which is just below unity. This implies that out-of-pocket healthcare demand is not considered to be a luxury, but a necessity in Mauritius. In order to see the differences in income elasticities by income groups, separate regressions are estimated for each income quartile over different years. The results indicate that income elasticities of out-of-pocket healthcare expenditure vary non-monotonically.