Health Expenditure Research Articles

Gatekeeping in primary care: Analysing GP referral patterns and specialist consultations in the NHS

This study investigates the impact of increasing the number of gatekeeper General Practitioners (GPs) on referral rates and specialist treatments. Gatekeeping is a supply-side strategy implemented to control health expenditure and improve efficiency by limiting patient access to services below marginal cost. It aims to address specialist moral hazard by reducing the overuse of expensive diagnostics and replacing them with more cost-effective GP diagnostic information. Using administrative data from 2004 to 2011, we examine whether the availability of gatekeeper GPs in local areas is associated with changes in outpatient referrals and elective admissions. Our findings reveal that increasing GP supply in socioeconomically disadvantaged areas leads to a decrease in both outpatient referrals and elective admissions. However, these effects are less pronounced in prosperous areas or regions with high GP referral rates. Interestingly, we observe that having more GP practices in a specific area implies higher referral rates and elective admissions. These findings offer valuable insights that can assist policymakers in crafting targeted policies to effectively reduce healthcare costs and enhance the overall efficiency of the health system.

Economic assessment of animal disease burden in Senegalese small ruminants

Small ruminant production in sub-Saharan Africa is limited by a range of constraints, including animal health issues. This study aimed at estimating the impact of these issues on the small ruminant production in Senegal in a holistic manner, using an approach developed by the Global Burden of Animal Diseases (GBADs) programme. The estimation focused on the mixed crop-livestock system, representing a large proportion (>60%) of the small ruminant population in the country. It was based on existing data collected via a systematic literature review, acquisition of secondary datasets from local stakeholders, and expert elicitation. A dynamic population model was used to calculate the gross margin of the sector under both the current health constraints and an ideal health state, where animals are not exposed to causes of morbidity and mortality. The difference between the current and ideal health scenarios, termed the Animal Health Loss Envelope (AHLE), provides a quantitative measure of the farm-level cost of disease in the system. The all-cause AHLE was estimated at 292 billion FCFA (468 million USD, with 95% prediction interval 216 – 366 billion FCFA) per year for 2022, for a population of 8.8 million animals. The contribution of Peste des Petits Ruminants (PPR) was modelled separately, as an example of attributing part of the AHLE to a specific disease cause. PPR was estimated to contribute 5% of the total AHLE. The animal disease burden experienced by Senegalese livestock keepers was largely due to loss in animals and production, with relatively small amounts of animal health expenditure. Implementation of this study contributed to the further development of the GBADs approach. Such estimates can support decision making at all levels, from investment decisions at the international level to local disease awareness campaigns targeting livestock keepers.

Exploring the Impact of Environmental Degradation, Income Inequality, Technological Development and Food Availability on Quality of Life: Recent Evidence From South Asia

ABSTRACTThis study investigates the determinants of quality of life in South Asian countries, focusing on Bangladesh, India, Sri Lanka, Nepal, and Pakistan from 2000 to 2018. Life expectancy is used as the dependent variable, representing life quality. The independent variables include carbon emissions, remittances, information and communication technology, income inequality, government health expenditure, economic development, and food security. Cross‐sectional time series FGLS is the main analytical method, supplemented by Pedroni and Kao cointegration tests and the Drisc/Kraay method. The findings indicate that information and communication technology, remittances, economic progress, and food security positively impact life expectancy, while CO2 emissions, income inequality, and government health expenditures negatively affect it. The study proposes several policy recommendations to improve the quality of life in the South Asian region.

Changes in Health Spending During the COVID-19 Pandemic by Expenditure Type and Household Profiles in Mexican Households

ObjectiveThis study aimed to analyze the changes in the health expenditure of households in Mexico during the COVID-19 pandemic to approximate changes in healthcare that can lead to difficulties in detecting noncommunicable diseases, among others. MethodsWe compare health spending before and after the pandemic through various estimators using multivariate linear regression models at the household level. We also explore heterogeneous effects by zone, sex, and household composition by age. We explore potential mechanisms of change estimating probit models of healthcare. We use microdata from the National Health and Nutrition Survey 2018 and COVID-19. ResultsThe results suggest a significant reduction in health spending, mainly referring to oral health, clinical analysis, and medical studies. Moreover, differences arise by type of area and household age profile. Changes are more significant among families with children younger than 12 years and households situated in urban areas. Regarding the mechanisms, the results suggest that the lower spending is not due to fewer health needs but rather due to less healthcare attention. ConclusionThe COVID-19 pandemic had a significant and heterogeneous impact on household health spending. This lower spending could lead to less detection of noncommunicable diseases, translating into more pressure on the health system in the medium and long term.

Impact of greenhouse gas emission, renewable energy, and economic growth on health expenditure in Southeast Asia: A comparative analysis of econometric models

Purpose — The study explores the effects of greenhouse gas emissions, renewable energy, and economic growth on health expenditures across Southeast Asia while comparing the performance of different econometric models for accuracy in analysis.Method — To analyze the relationships among variables, the study employs three econometric models, the Autoregressive Distributed Lag Model, the co-integration Model, and the Quantile Regression Model, using annual data from 2000 to 2020.Findings — The results reveal that greenhouse gas emissions and GDP significantly influence health expenditure in all three models. However, the significance of renewable energy consumption varies, with only the quantile regression model indicating a significant relationship with health expenditure. Model comparison based on Mean Squared Error (MSE) suggests that the autoregressive distributed lag (ARDL) model provides the most accurate predictions. Also, it found that there is a short-run and long-run causal effect of GHG and GDP on health expenditure, as well as health spending on GDP.Implication — This study helps to understand how economic growth, environmental factors, and healthcare spending interact to develop sustainable policies to address health and environmental problems in Southeast Asia.Originality — This research contributes to the body of knowledge examining the impact of economic and environmental factors on health expenditures in Southeast Asia through a comparative analysis of different econometric models.

ASARA-A technology-driven maternal and child healthcare model of Araku

Tribal populations form 8.6% of total India’s population. The health indicators of tribal populations lag behind their non-tribal counterparts. Limited access to healthcare services, poor transportation facilities, increased out-of-pocket expenditures for health, distinct cultural practices and remote settlement among many others contribute to the poor health status of the tribal populations. However, to achieve sustainable development goals by 2030, it is extremely important to address the healthcare needs of the tribal population. The current paper is the first part of the model of care working paper series that discusses the components of the ASARA project to highlight the impacts of the decade long efforts towards improving maternal and child care in the region.

Pengaruh Pendapatan Asli Daerah (PAD), Dana Perimbangan, dan Pengeluaran Bidang kesehatan terhadap Indeks Pembangunan Manusia (IPM) Kabupaten Jombang Tahun 2007-2021

The aim of the research is to analyze the influence of a region's original income, balancing funds and health expenditure on the human development index (HDI) in Jombang Regency during the period 2007 - 2021. Using the multiple linear regression method by carrying out the Best Linear Unbiased Estimation (BLUE) test, and analysis hypothesis testing. The results of this research concluded that simultaneously the human development index (HDI) in Jombang Regency during the 2007-2021 period was influenced by local original income (PAD), balancing funds and expenditure in the health sector. However, only partial balancing funds can influence the human development index in Jombang Regency during the 2007-2021 period.

Factors Affecting Household Health Expenditures: Evidence from Iran

Abstract Background Productivity plays a crucial role in driving economic growth, and its primary determinant is human capital. Human capital, in turn, is influenced by health and education investments, leading both households and governments to allocate substantial resources toward these sectors. Understanding the factors influencing health expenses is vital for designing effective policies. Methods This study investigates the factors affecting health costs by analyzing data from various provinces in the Islamic Republic of Iran, spanning from 2006 to 2019. The data, sourced from the Statistics Center of Iran, was analyzed using the panel data approach to uncover the relationships between health expenditure and several key variables. Results The analysis revealed significant disparities in health expenditure among provinces. Sistan & Baluchestan had the lowest health expenditure per household, while Tehran reported the highest. Inflation emerged as a significant factor, having a negative impact on health expenses due to its influence on purchasing power. Conversely, the education and salary of household heads had a positive impact on health expenditure. Notably, economic growth did not exhibit a significant relationship with health expenses. Conclusions The study highlights the importance of education and income levels in shaping health expenditures, while inflation can curtail spending on health due to reduced purchasing power. Policymakers should consider these factors to ensure equitable and effective allocation of health resources. Key messages • Improving health and well-being, essential for comprehensive progress and human development, relies significantly on household health expenditure. • The efforts to enhance human capital should focus on reducing inflation.

Social Inequalities in mental health service use and perceived helpfulness: A global analysis across 111 countries

Abstract Social inequalities in mental health are evident in the prevalence of mental health problems, but also the utilisation and patents’ perceived benefits of treatment. However, the extent of these disparities on a global scale and whether there are country-level differences in the predictors of mental health service use remain unknown. This study uses data from the Wellcome Global Monitor 2020, a nationally representative survey encompassing 111 countries and 117,088 individuals. We examine the association of socio-economic factors (such as household income and education), psycho-social factors (including stigma perception and trust in health professionals), and country-level variables (such as GDP, Gini coefficient, and health expenditure) with mental health service use and perceived effectiveness of treatment. Multi-level logistic regression models were employed for analysis. The utilisation of mental health professions of people with depression or anxiety symptomology is higher in HICs (predicted probability of 62% CI[0.60 - 0.65]) compared to LIMCs (predicted probability of 33% CI[0.31 - 0.34]). Higher country GDP (OR = 1.26 CI[1.08-1.47]) and health expenditure (OR = 1.11 CI[1.04-1.19] per percentage of health expenditure) are associated with higher treatment utilisation. On the individual level, those in the wealthiest quintile are more likely to engage with mental health professionals (OR = 1.25[1.14-1.36]) and perceive this treatment as highly beneficial (OR = 1.23[1.07-1.40]). Trust in healthcare practitioners and perceived stigma are also associated with mental healthcare use. This analysis shows strong patterns of mental healthcare use and perceived benefits depending on the wealth of the country, health expenditure and individual socio-economic status. Moreover, disparities in treatment utilization and effectiveness are also influenced by trust in healthcare professionals and perceived mental health stigma.

How Avoidable Mortality is influenced by health expenditure: an Italian 14-year panel data analysis

Abstract Background Avoidable Mortality is a widely used public health indicator to assess the quality of healthcare systems. The aim of this study was to investigate how the allocation of private and public health expenditure (PHE) could influence avoidable mortality (AM), treatable mortality (TM) and preventable mortality (PM) of Italian citizens. Methods A pooled cross-sectional time series study was conducted. Italian healthcare data from 2009 to 2019 was extracted from ‘Health for All’, a WHO-related database released periodically by the Italian National Institute of Statistics. PHE was divided by providers area (directly provided services (DPS), general and specialist medicine, pharmaceutical, rehabilitation). Data about private health expenditure, gross domestic product per capita (GDPPC), level of education, medical drug consumption per capita (MDCPC), general practitioners per capita (GPPC), physical exercise, tobacco use, and obesity were collected. AM was divided into TM and PM using OECD/Eurostat lists of causes of death (2022). A fixed-effects regression was used to assess the effects of economic and social variables on AM, TM and PM. Results Higher spending on DPS (-0.027), higher MDCPC (-0.859) and higher GDPPC (-0.001) were associated with lower rates of AM. Higher sport activity (c -0.673) was associated with lower rates of TM. Higher levels of private health expenditure (0.022) and higher number of GPPC (0.023) were associated with higher rates of PM; these counterintuitive results could be caused by the inappropriateness of medical treatment directly requested by patients. Other variables were not significantly associated with AM, TM or PM. Conclusions The results highlight the importance of medical DPS by NHS (emergency departments, hospital care, specialized care, primary care, etc.). Analyzing health data divided by areas of NHS we could help policy makers to allocate human and economic resources more efficiently. Key messages • The allocation of public health resources could influence the health status of the polulazion. • Italian National Health System could reduce avoidable mortality through the use of directly provided services.

Detecting Unrecognized Dementia Using Deep Learning Methods with Korean National Claims Data

Abstract Background Dementia is one of the leading causes of death in elderly people. In Korea, the government supports dementia screening for people aged 60 and older, but it is not a population-based organized screening program. It is difficult to achieve early diagnosis and early treatment. The objective of this study is to detect unrecognized dementia using Korean National Claims Data for early diagnosis. Methods This study used the National Health Insurance Claims data in Korea. The case group is the new dementia visit as an unrecognized group, while the control group was randomly selected from the general population without dementia. The predictors included health utilization, socioeconomic and demographic, procedure codes, diagnostic codes and health screenings data. The health utilization variables included length of stay, the number of outpatient visits, health expenditures and other encounter information. All medical utilization data was aggregated monthly. In the case group, 12 months of data from 6-month or 2-years before the onset of dementia were used. In the control group, 12 months of data from randomly selected time point were included. Transformer, embedding methods, and Time2Vec were used as the deep learning methods. This study included 453,306 incidents of dementia, representing almost all cases reported from 2010 to 2019 in Korea. The control group consisted of 669,873. Results After training the deep learning prediction model, the AUC for 6-month dementia prediction on the test dataset was 0.87, and for 2-year dementia prediction, it was 0.76. The most important variables were health utilization variables, especially health expenditures. The health utilization trajectories of the case group were significantly different from those of the control group. Conclusions Based on the claims data, we could detect unrecognized dementia case. We can extend the model to other chronic disease such as cancer and stroke, which are significant burden of disease. Key messages • Screening in healthcare facilities or using lab test results would be more accurate, but it would be difficult to apply to a large population due to the cost-effectiveness and timeliness constraints. • On the other hand, the detection model using the existing claims data would be helpful to to develop cost-effective mass screening program. It can cover the weakness of current screening program.

Population ageing and health financing: A method for forecasting two sides of the same coin

Abstract There is a perception that population ageing will have deleterious effects on future health financing sustainability. Given the positive association between health care utilization and increasing calendar age, many analysts assume population ageing will result in considerable growth in health spending. Since this expenditure tends to be sourced primarily from public funds, there is great policy interest to quantify how population ageing is likely to affect health expenditure trends. We propose a new method-the Population Ageing financial Sustainability gap for Health systems (or alternatively, the PASH)-to explore how changes in the population age mix will affect health expenditures and revenues. Using a set of six countries in Europe and the Western Pacific representing a diverse range of health financing systems (Australia, Bulgaria, Japan, Slovenia, United Kingdom, Vietnam), we forecast the size of the ageing-attributable gap between health revenues and expenditures from 2020 to 2100 under current health financing arrangements. The largest gap by 2100 is expected to be in Vietnam, where the gap between revenues and expenditure is expected to increase by around $170 per person in 2018 PPPs or 2.3% of GDP; 87.1% of this increase is due to expected growth in expenditures. In Slovenia, where the gap is forecast in line with the forecast for Japan (the oldest country in the world), nearly half of the gap (44.2%) is due to reductions in revenue generation. All countries face some health financing gap due to ageing under current financing arrangements. The PASH analysis highlights the wide range of policy options available to manage health financing as the population ages, such as changing sources for health revenues and reducing expenditure by promoting healthy ageing.

Consumption and expenditure of antidepressants and anxiolitycs in 14 European countries

Abstract Background Since the burden of depressive and anxiety disorders, assessing the use and spending of drugs commonly prescribed for treating such conditions is a valuable barometer of mental health assistance and healthcare services. The current research aims to evaluate the consumption of antidepressants and anxiolytics and the relative expenditure among 14 European countries (Austria, Czech Republic, Finland, Germany, Hungary, Italy, Latvia, Luxembourg, Norway, Portugal, Slovak Republic, Slovenia, Spain and Sweden). Methods A retrospective longitudinal study was assessed based on pooled time series analysis of secondary data over ten years (2012-2021). Defined Daily Doses (DDD) per 1,000 inhabitants and health expenditure per capita (current US$, computed on purchasing power parity) were considered. Linear and quadratic trends were calculated for defining relationships between the variables of interest. Results Prevailing patterns of consumption and spending show an increase in antidepressants and a decrease in anxiolytics. Noteworthy is the growth slope of antidepressant consumption in three selected countries, Portugal, Spain, and Sweden, by over two and a half times from 2012 to 2021. In addition, for a few countries, there is a pattern contrary to most countries for anxiolytics (Latvia, Spain) and discordant between consumption and expenditure for antidepressants (Austria, Hungary). Conclusions The widespread growth of antidepressant use deserves attention. As a public health issue, the prescription and use of antidepressants should be addressed by targeted policies for integrating multifaceted strategies. Key messages • Monitoring consumption and expenditure of antidepressant and anxiolytic drugs represents a valid tool for assessing the efficacy and availability of mental healthcare services among the population. • The growth in the consumption of antidepressants represents a relevant public health issue and deserves attention for the evaluation of an integrated approach of assistance.

Health Impacts of Disasters and Social Indicators: An Ecological Study

Abstract The objective of this study is to investigate the correlation between certain social indicators and the mortality and morbidity in disasters recorded in the EM-DAT database within countries in the last decade. The correlation between the mortality and morbidity in disasters recorded in the EM-DAT database between March 1, 2014-2024 and the most recent data on Human Development Index (HDI), Gender Inequality Index (GII), Gini Coefficient (GC), Government Health Expenditure as a share of GDP (GHE/GDP) and Corruption Perception Index (CPI) were analyzed. During the period of the study, disasters from a total of 207 countries/regions were recorded in the database. The median (IQR) values of countries in disasters were found to be 35.1 (67.5) for death per million and 76.3 (783.0) for injury per million. The most frequent types of disasters, the most frequent cause of mortality and the most frequent cause of injury in each country were found to be floods, extreme temperatures, and epidemics, respectively. While there was no significant difference between the social indicators analyzed and the total number of deaths, there was a negative correlation between the number of injuries and the HDI, CPI, GHE/GDP values of the countries, and a positive correlation between the GC and GII values (for all tests, Spearman correlation test, p < 0.001). The correlation coefficient was interpreted as ‘weak’ in all other pairwise analyses except for the GHE/GDP value (moderate). Countries with social indicators closer to the positive threshold have been found to have less injuries in disasters. The possible reason for the insignificant correlation with the mortality is thought to be the difficulties in detecting mortality, especially in ‘extreme temperatures’, and the fact that it is mostly recorded in countries where social indicators are relatively more advanced. More research is needed to investigate the relationality between social indicators and disaster harms. Key messages • Disasters are critical mediators between social determinants and health. Addressing and reducing inequalities should remain on the public health agenda to prevent disasters and protect health. • Analysis of disasters shows that ‘extreme temperatures’, which cause the most deaths in some countries, are barely detected in developing countries. Disaster recording systems need to be strengthened.

Solutions for reducing the severe economic burden of musculoskeletal diseases

Abstract Issue In Slovenia the big group of over 150 musculoskeletal and connective tissue diseases (MSCTD) constitute a serious public health problem, a major burden on health systems and society as a whole. Patients with these diseases have a poorer quality of life and often retire early. Any early retirement that could have been prevented represents a loss of human capital, which is a major social and economic cost to society. The aim of this study was to analyze the economic burden of the six most common MSCTD in Slovenia for the period from 2020 to 2022, to contribute to a better understanding of this problem and suggest solutions. Methods At the Slovenian National Institute of Public Health, in collaboration with the Faculty of Economics at the University of Ljubljana, we calculated the burden of six most common MSCTD for the period 2020-2022. We used the National Transfer Accounts (NTA) methodology to calculate the indirect costs; direct costs were calculated based on the national routine health data. Results The calculated economic burden of the six most common diagnoses of MSCTD represents 5% of total health expenditure or 0.4% of Slovenian gross domestic product on average. Direct costs amounted to 2% of total health expenditure (hospitalizations 22.5%, costs for medicines 9.3%, first curative visits at the primary level and visits to the outpatient clinic at the secondary level 2.7%). Indirect costs amounted to 3% of total health expenditure. Conclusions Despite the reduced access to the health system due to COVID-19 the economic burden of MSCTD is high in Slovenia and would be significantly higher considering all diagnoses from this group of diseases. The research requires interdisciplinary cooperation between medicine and economics regarding demanding NTA methodology which is innovative in our country. Key messages • One of the main public health priorities in Slovenia should be to raise awareness of MSCTD. • In the light of the aging population prevention activities with focus on MSCTD should be intensified as soon as possible.

Impact of public health expenditure on malnutrition among Peruvians during the period 2010-2020: A panel data analysis

Background The study analyzes the impact of public health spending on malnutrition among Peruvians, using data from the National Household Survey, the Central Reserve Bank of Peru, the National Institute of Statistics and Informatics and the Ministry of Economy and Finance from 2010. -2020. Previous studies have revealed the existing relationship of health spending with the reduction of malnutrition. Methods A quantitative approach is considered, with an explanatory type of research using panel data methodology considering the bidimensionality of the data, which allows quantifying this effect for the Peruvian case using the National Household Survey, data from the Central Reserve Bank of Peru, as well as information from the National Institute of Statistics and Informatics and the Transparency Portal of the Ministry of Economy and Finance in the period 2010-2020. Results The results show that public expenditure on health has a negative relationship with malnutrition; the rural sector has a positive relationship with malnutrition given the limitations present for access to adequate food. Similarly, the unemployment rate shows a positive relationship with malnutrition, given that being unemployed leads to a higher cause of malnutrition in the population, and the gross domestic product has a negative relationship with malnutrition, given that greater economic growth produces an impact on reducing malnutrition, with the greatest impact being on the rural population and the gross domestic product. Conclusions In the analysis period 2010-2020 in Peru, based on the panel data analysis, the impact of public health expenditure on reducing malnutrition is observed in 10 departments, achieving a reduction in malnutrition; while in 14 departments, this indicator has not been reduced.

Implications for household health expenditure in China’s ageing population: based on Red Herring hypothesis

Implications for household health expenditure in China’s ageing population: based on Red Herring hypothesis

Global variations in coronary revascularisation and acute myocardial infarction mortality between 2006-2020: a longitudinal, population-level analysis of 16 high-income nations from the OECD database

Abstract Background Revascularisation options for ischaemic heart disease (IHD) includes either, percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). Whilst PCI remains the preferred choice in ST-elevation myocardial infarction (STEMI)(1), several landmark trials have questioned its universal superiority (2,3), thus prompting re-evaluation of guidelines. A wide-scale contemporary overview of revascularisation trends is lacking. Purpose To examine the evolving pattern in PCI and CABG rates, alongside mortality from acute myocardial infarction (AMI) across a group of 16 high-income countries between 2006 and 2020. Methods Standardized PCI and CABG procedure rates alongside AMI age-standardised mortality rate (ASMR) were obtained from the Organisation for Economic Co-operation and Development (OECD) database. Data from 2006-2020 was extracted for; Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom (UK). Together, these countries are commonly known as the European Union (EU) 15+ and represent a cluster of high-income nations with comparable levels of health expenditure. Procedural trends including the estimated annual percentage change (EAPC) were evaluated using Joinpoint analysis whilst Locally Weighted Scatterplot Smoothing (LOESS) models was used to analysis trends in AMI mortality. Results Over 15 years, 14.0 million PCI and 2.8 million CABG procedures were recorded in total. PCI rates varied amongst nations (Figure 1), however showed an overall increase in 11 countries, led by Finland (+36.0%). The steepest increase was observed in France between 2012-2018 (EAPC 5.4, 95% CI: 4.8 – 6.1). The greatest overall decrease in PCI was observed in Luxemburg (-33.5%). The fastest decrease was seen during 2018-2020 in the UK (EAPC -7.2, 95% CI: -9.7 – -4.6). CABG rates declined overall in 15 countries (Figure 1), with Luxembourg (-71.3%), experiencing the largest fall and showing the steepest decline between 2014-2018 (EAPC -20.7, 95% CI: -28.3 – -12.3). Ireland was the only country to show an increase in CABG rate (+16.3%). Throughout the study period, the PCI-to-CABG ratio increased (Figure 2A), whilst AMI mortality decreased consistently across all countries (Figure 2B). Conclusion Despite evidence supporting CABG over PCI in specific scenarios, CABG rates have declined, and PCI rates have increased. This trend may be influenced by several factors including patient preference for less invasive procedures and advancements in interventional techniques. The varied use of PCI among these nations, alongside a sustained decline in AMI mortality rates, may be expected given the importance of optimal medical therapy in the management of IHD. The results further highlight the significance of factors beyond revascularisation in driving improved outcomes.PCI and CABG rates between 2006 and 2020PCI to CABG ratio and AMI mortality rate

Exploring the Relationship Between Health and Out-of-Pocket Health Expenditures: Evidence for Middle-Aged and Older Adults in China.

With population aging, disability and chronic conditions are increasingly prevalent among middle-aged and older adults in China. Using panel data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018, this paper explores the effects of Activities of Daily Living limitations, Instrumental Activities of Daily Living limitations, and chronic conditions on Out-of-Pocket Expenditures (OOPEs) among middle-aged and older adults in China. A first-difference model and a system-generalized method of moment model (GMM) are used. The system-GMM model for the first time addresses unobserved heterogeneity and produces unbiased estimates of the effects of health and OOPEs. Additionally, this paper assesses the heterogeneity of the results across the demographic and socioeconomic groups. These findings can be used to inform policymakers on improving medical resource allocation and ensure better financial protection for those living with a disability and chronic diseases.

The Role of Government Health Expenditure in Driving Economic Growth: Evidence from OECD Countries

This study examines the influence of government health expenditure and life expectancy on economic growth. The study makes use of panel data analysis and utilizes data from the OECD nations between 2000 and 2021. The study applies panel data analysis using POLS, FEM and REM models and dynamic GMM models. The study also gauges the moderating role of life expectancy on the relationship between government health expenditure and economic growth. The results indicate that government expenditure on health hurts economic growth. A detrimental relationship between life expectancy and economic growth indicates that higher life expectancy could result in elevated healthcare and financial expenses. Nevertheless, the interactive regression model suggests that there is no significant moderation of the association between government expenditure on health and economic growth by life expectancy, implying that the influence of government health expenditure on economic growth is generally unaffected by demographic changes. These findings emphasize the significance of differentiating between the short-term and long-term economic consequences of healthcare expenditure. This study offers insights into the optimization of public spending in OECD nations to promote sustainable economic growth and enhance public health outcomes.