Total healthcare spending as a share of GDP Total healthcare expenditure as the share of national gross domestic product (GDP). Citation: World Health Organization - Global Health Observatory (2026)

significantly. For example, total U.S. health expenditures steadily increased as a share of gross domestic product (GDP), demonstrating the increased Health economics is a branch of economics concerned with issues related to efficiency, effectiveness, value and behavior in the production and consumption of health and healthcare. Health economics is important in determining how to improve health outcomes and lifestyle patterns through interactions between individuals, healthcare providers and clinical settings. Health economists study the functi Health spending as percent of gross domestic product (GDP) by country List of countries by total health expenditure per capita The average estimated cost-effectiveness threshold (CET) per Quality-adjusted life year for health care rationing varied between countries in 2019 from 0.14 of GDP per capita for Ethiopia to 1.47 GDP per capita for USA according to a study.

Background As middle-income countries become more affluent, economically sophisticated and productive, health expenditure patterns are likely to change. Other socio-demographic and political changes that accompany rapid economic growth are also likely to influence health spending and financial protection. Methods This study investigates the relationship between growth on per-capita healthcare expenditure and gross domestic product (GDP) in a group of 27 large middle-income economies and compares findings with those of 24 high-income economies from the Organization for Economic Cooperation and Development (OECD) group. This comparison uses national accounts data from 1995-2014. We hypothesize that the aggregated income elasticity of health expenditure in middle-income countries would be less than one (meaning healthcare is a normal good). An initial exploratory analysis tests between fixed-effects and random-effects model specifications. A fixed-effects model with time-fixed effects is implemented to assess the relationship between the two measures. Unit root, Hausman and serial correlation tests are conducted to determine model fit. Additional explanatory variables are introduced in different model specifications to test the robustness of our regression results. We include the out-of-pocket (OOP) share of health spending in each model to study the potential role of financial protection in our sample of high- and middle-income countries. The first-difference of study variables

The efficiency and efficacy of the U.S. healthcare system has been in question for decades. We spend more per capita than any other industrialized nation while consistently realizing inferior health outcomes for our population as a whole when compared with many industrialized nations. In 1965, the proportion of U.S. gross domestic product (GDP) attributed to healthcare was approximately 6%. Today, the share of GDP spent on healthcare by the United States is almost 18%. This number is 5% higher than the next two countries, the Netherlands and France (spending 12.0% and 11.8% of their GDP on hea

<h4>Introduction</h4>Life expectancy is determined by several structural interplays. This study examines the impact of economic growth, AI (as measured by digitalization), and carbon emissions on life expectancy in GCC countries from 2000 to 2024.<h4>Methods</h4>This research relies on a standard model derived from the health economics function, which combines panel fixed effects and dynamic models (System GMM) to measure the impact of economic growth, digital transformation, and environmental sustainability on public health. Estimates were obtained using static fixed effects and a dynamic specification corresponding to the generalized multiple methods approach. These estimates are useful for controlling for unobserved heterogeneity, health persistence, and possible internal relationships among income, technology, and health. Life expectancy indicates a high level of persistence.<h4>Results</h4>The dynamic estimates indicate that the lag values of the current health outcome can explain the outcome over 70 years. After controlling for static and dynamic specifications and internalities, the economic growth role is positive but reduced. All specifications indicate that digital transformation has a positive and robust effect on life expectancy, with an economically significant magnitude. In contrast, a strong correlation exists between per capita carbon dioxide emissions and low life expectancy. The proportion of health expenditure to GDP is not significantly associated with life expectancy in the GCC countries.<h4>Discussion</h4>Overall, these findings imply that population health improvements in GCC countries are probably driven less by health expenditure volumes and more by structural changes in the digital and environmental efficiency of population health production. Economic development will expand fiscal space for health-sector expenditures. The development of the digital economy clearly increases the productivity of health sector expenditures. Conversely, carbon-intensive growth imposes significant health costs. The findings elucidate that digital and environmental health organizations within the public health sector are essential for achieving health gains and long-term sustainability in GCC countries.