Government health expenditures and health outcome nexus: a study on OECD countries

Anwar, Asim; Hyder, Shabir; Nor, Norashidah Mohamed; Younis, Mustafa Z

doi:10.3389/fpubh.2023.1123759

Cited by 19 publications

(6 citation statements)

References 40 publications

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“…Several factors come into play, including how the investment is allocated, including infrastructure, pharmaceuticals, and primary care, among other aspects. Additionally, non-medical determinants, such as population habits and lifestyles, exert a substantial influence on health outcomes [29].…”

Section: Healthcare Expenditure Coverage Status and Non-medical Deter...mentioning

confidence: 99%

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A cross-national performance comparison universal healthcare systems of Chile, Costa Rica, Italy, and Spain using OECD data

Zavaleta-Monestel,

Zovi,

Morales-Vallespín

et al. 2024

Discov Health Systems

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Objectives To analyze Organization for Economic Cooperation and Development (OECD) indicators for the Health Systems of Costa Rica, Spain, and Italy, focusing on year-to-year changes. Study design and methods Examining each country’s healthcare systems utilizes a value-for-money approach, aiming to outline their healthcare expenditures relative to the OECD average, while also assessing the value obtained from these investments. This involves contrasting reported indicator values for each country and the OECD average during a year close to the last decade’s outset (year 1) with data around 2020 (year 2). Results Results obtained are based on different indicators and the countries being examined. Costa Rica stood out with lowest healthcare investment, while Chile had the less population coverage for a set core of services. Italy and Spain achieved 100% healthcare coverage. All four regions reported decreased tobacco consumption in terms of non-medical determinants of health. Costa Rica showcased the highest vaccination coverage and experienced the most significant increase in this aspect within healthcare utilization. In the context of resource accessibility, waiting times from specialist assessment to treatment increased the most for hip replacement procedures in Chile, Costa Rica, Italy, and Spain. The Pharmaceutical Consumption analysis highlighted agents acting on the Renin-Angiotensin system as the most widely consumed category. Conclusion This analysis helps reveal the workings of diverse health systems, allowing us to pinpoint areas for potential improvement within each region. By examining the achievements and obstacles faced by other nations, policymakers and healthcare stakeholders acquire a valuable foundation on which to enact reforms.

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Section: Healthcare Expenditure Coverage Status and Non-medical Deter...mentioning

confidence: 99%

“…These measures should go hand in hand with environmental reforms and quality-of-life improvements, aiming to achieve enduring health outcomes. Therefore, it is not solely about increasing healthcare investments but also ensuring their appropriate and strategic allocation [29,30].…”

Section: Healthcare Expenditure Coverage Status and Non-medical Deter...mentioning

confidence: 99%

A cross-national performance comparison universal healthcare systems of Chile, Costa Rica, Italy, and Spain using OECD data

Zavaleta-Monestel,

Zovi,

Morales-Vallespín

et al. 2024

Discov Health Systems

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“…These variables reflect the domains of financing (health expenditures), resources generation (health professionals and beds), and service delivery (inpatient related indicators) motivated by the building blocks of a health system proposed by WHO (11,12). We use the control variable GDP per capita in PPP which has the label "GDPpc" (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26). The source of all the independent variables is Eurostat database and the online code is displayed in Table 1.…”

Section: Independent Variablesmentioning

confidence: 99%

“…This aggregate analysis allows for international comparisons relatively to best results or practices, policies and interventions among countries, and it enables the identification of disparities and differences across countries. Among the common factors associated with treatable mortality across European countries, we have identified GDP per capita and health expenditures, which are important determinants for health outcomes (15)(16)(17)(18)(19)(20)(21)(22)(23)(24).…”

Section: Introductionmentioning

confidence: 99%

Treatable mortality and health care related factors across European countries

Tavares

2024

Front. Public Health

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IntroductionDespite the improvements in European health systems, a large number of premature deaths are attributable to treatable mortality. Men make up the majority of these deaths, with a significant gap existing between women and men’s treatable mortality rate in the EU.AimThis study aims to identify the healthcare-related factors, including health expenditures, human and physical resources, and hospital services use associated with treatable mortality in women and men across European countries during the period 2011–2019.MethodsWe use Eurostat data for 28 EU countries in the period 2011–2019. We estimate a panel data linear regression with country fixed effects and quantile linear regression for men and women.ResultsThe results found (i) differences in drivers for male and female treatable mortality, but common drivers hold the same direction for both sexes; (ii) favorable drivers are GDP per capita, health expenditures, number of physicians per capita, and (only for men) the average length of a hospital stay, (iii) unfavorable drivers are nurses and beds per capita, although nurses are not significant for explaining female mortality.ConclusionPolicy recommendations may arise that involve an improvement in hospital bed management and the design of more specific policies aimed at healthcare professionals.

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“…The study used a system generalised method of moments (GMM) for estimation. This is because, in assessing the panel model estimation, potential endogeneity issues arise because of unobserved heterogeneity and cross-sectional dependence [55,56]. Endogeneity can be loosely defined as a correlation between independent variables and error terms in a regression model [57].…”

Section: Estimation Techniquesmentioning

confidence: 99%

Factors Influencing Women’s Health in Conflict Zones in Africa

Mlambo,

Mvuyana,

Sithole

2024

Women

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This study sought to examine the factors that influence women’s health in conflict zones for the period spanning 1975–2018. The investigation was motivated by the fact that war and violent conflict strain already underdeveloped healthcare systems and frequently put disadvantaged groups—particularly women and children—at risk of being denied access to essential services like healthcare. Living in or close to conflict zones puts women at a higher risk for sexual assault, poor reproductive health, unwanted pregnancy, and poor maternal health outcomes. By destroying infrastructure, food, water, and sanitation systems, armed conflict reduces access to healthcare. The results showed that the remittances and life expectancy have a negative relationship with maternal mortality. Development assistance, the number of refuges, and military expenditure were seen as having a positive relationship with maternal mortality, but no significant relationship was found with either economic growth or internet usage. This calls for new policy and self-care interventions. There is also a need to explore how to maximise the benefits of technology in delivering health interventions to hard-to-reach populations. There is also a need for policymakers to explore how to maximise the benefits of technology in delivering health interventions to hard-to-reach populations.

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Government health expenditures and health outcome nexus: a study on OECD countries

Cited by 19 publications

References 40 publications

A cross-national performance comparison universal healthcare systems of Chile, Costa Rica, Italy, and Spain using OECD data

A cross-national performance comparison universal healthcare systems of Chile, Costa Rica, Italy, and Spain using OECD data

Treatable mortality and health care related factors across European countries

Factors Influencing Women’s Health in Conflict Zones in Africa

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