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Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Bill & Melinda Gates Foundation.

Background The leading emerging markets of Brazil, Russia, India, China and South Africa (BRICS) are increasingly shaping the landscape of the global health sector demand and supply for medical goods and services. BRICS’ share of global health spending and future projections will play a prominent role during the 2020s. The purpose of the current research was to examine the decades-long underlying historical trends in BRICS countries’ health spending and explore these data as the grounds for reliable forecasting of their health expenditures up to 2030. Methods BRICS’ health spending data spanning 1995–2017 were extracted from the Institute for Health Metrics and Evaluation (IHME) Financing Global Health 2019 database. Total health expenditure, government, prepaid private and out-of-pocket spending per capita and gross domestic product (GDP) share of total health spending were forecasted for 2018–2030. Autoregressive integrated moving average (ARIMA) models were used to obtain future projections based on time series analysis. Results Per capita health spending in 2030 is projected to be as follows: Brazil, $1767 (95% prediction interval [PI] 1615, 1977); Russia, $1933 (95% PI 1549, 2317); India, $468 (95% PI 400.4, 535); China, $1707 (95% PI 1079, 2334); South Africa, $1379 (95% PI 755, 2004). Health spending as a percentage of GDP in 2030 is projected as follows: Brazil, 8.4% (95% PI 7.5, 9.4); Russia, 5.2% (95% PI 4.5, 5.9); India, 3.5% (95% PI 2.9%, 4.1%); China, 5.9% (95% PI 4.9, 7.0); South Africa, 10.4% (95% PI 5.5, 15.3). Conclusions All BRICS countries show a long-term trend towards increasing their per capita spending in terms of purchasing power parity (PPP). India and Russia are highly likely to maintain stable total health spending as a percentage of GDP until 2030. China, as a major driver of global economic growth, will be able to significantly expand its investment in the health sector across an array of indicators. Brazil is the only large nation whose health expenditure as a percentage of GDP is about to contract substantially during the third decade of the twenty-first century. The steepest curve of increased per capita spending until 2030 seems to be attributable to India, while Russia should achieve the highest values in absolute terms. Health policy implications of long-term trends in health spending indicate the need for health technology assessment dissemination among the BRICS ministries of health and national health insurance funds. Matters of cost-effective allocation of limited resources will remain a core challenge in 2030 as well.

Abstract The inclusion of mental health in the Sustainable Development Goals represents a global commitment to include mental health among the highest health and development priorities for investment. Low- and middle-income countries (LMICs), such as South Africa, contemplating mental health system scale-up embedded into wider universal health coverage-related health system transformations, require detailed and locally derived estimates on existing mental health system resources and constraints. The absence of these data has limited scale-up efforts to address the burden of mental disorders in most LMICs. We conducted a national survey to quantify public expenditure on mental health and evaluate the constraints of the South African mental health system. The study found that South Africa’s public mental health expenditure in the 2016/17 financial year was USD615.3 million, representing 5.0% of the total public health budget (provincial range: 2.1–7.7% of provincial health budgets) and USD13.3 per capita uninsured. Inpatient care represented 86% of mental healthcare expenditure, with nearly half of total mental health spending occurring at the psychiatric hospital-level. Almost one-quarter of mental health inpatients are readmitted to hospital within 3 months of a previous discharge, costing the public health system an estimated USD112 million. Crude estimates indicate that only 0.89% and 7.35% of the uninsured population requiring care received some form of public inpatient and outpatient mental healthcare, during the study period. Further, mental health human resource availability, infrastructure and medication supply are significant constraints to the realization of the country’s progressive mental health legislation. For the first time, this study offers a nationally representative reflection of the state of mental health spending and elucidates inefficiencies and constraints emanating from existing mental health investments in South Africa. With this information at hand, the government now has a baseline for which a rational process to planning for system reforms can be initiated.

This study examined the differences in health spending within the World Health Organization (WHO) Europe region by comparing the EU15, the EU post-2004, CIS, EU Candidate and CARINFONET countries. The WHO European Region (53 countries) has been divided into the following sub-groups: EU15, EU post-2004, CIS, EU Candidate countries and CARINFONET countries. The study period, based on the availability of WHO Global Health expenditure data, was 1995 to 2014. EU15 countries have exhibited the strongest growth in total health spending both in nominal and purchasing power parity terms. The dynamics of CIS members’ private sector expenditure growth as a percentage of GDP change has exceeded that of other groups. Private sector expenditure on health as a percentage of total government expenditure, has steadily the highest percentage point share among CARINFONET countries. Furthermore, private households’ out-of-pocket payments on health as a percentage of total health expenditure, has been dominated by Central Asian republics for most of the period, although, for the period 2010 to 2014, the latter have tended to converge with those of CIS countries. Western EU15 nations have shown a serious growth of health expenditure far exceeding their pace of real economic growth in the long run. There is concerning growth of private health spending among the CIS and CARINFONET nations. It reflects growing citizen vulnerability in terms of questionable affordability of healthcare. Health care investment capability has grown most substantially in the Russian Federation, Turkey and Poland being the classical examples of emerging markets.

Asthma is a chronic disease that affects quality of life, productivity at work and school, and healthcare use; and it can result in death. Measuring the current economic burden of asthma provides important information on the impact of asthma on society. This information can be used to make informed decisions about allocation of limited public health resources. In this paper, we provide a comprehensive approach to estimating the current prevalence, medical costs, cost of absenteeism (missed work and school days), and mortality attributable to asthma from a national perspective. In addition, we estimate the association of the incremental medical cost of asthma with several important factors, including race/ethnicity, education, poverty, and insurance status. The primary source of data was the 2008-2013 household component of the Medical Expenditure Panel Survey. We defined treated asthma as the presence of at least one medical or pharmaceutical encounter or claim associated with asthma. For the main analysis, we applied two-part regression models to estimate asthma-related annual per-person incremental medical costs and negative binomial models to estimate absenteeism associated with asthma. Of 213,994 people in the pooled sample, 10,237 persons had treated asthma (prevalence, 4.8%). The annual per-person incremental medical cost of asthma was $3,266 (in 2015 U.S. dollars), of which $1,830 was attributable to prescription medication, $640 to office visits, $529 to hospitalizations, $176 to hospital-based outpatient visits, and $105 to emergency room visits. For certain groups, the per-person incremental medical cost of asthma differed from that of the population average, namely $2,145 for uninsured persons and $3,581 for those living below the poverty line. During 2008-2013, asthma was responsible for $3 billion in losses due to missed work and school days, $29 billion due to asthma-related mortality, and $50.3 billion in medical costs. All combined, the total cost of asthma in the United States based on the pooled sample amounted to $81.9 billion in 2013. Asthma places a significant economic burden on the United States, with a total cost of asthma, including costs incurred by absenteeism and mortality, of $81.9 billion in 2013.

Over the past four decades, the share of income devoted to health care nearly tripled. If policy is unchanged, this trend is likely to continue. Should Americans decide to rein in the growth of health care spending, they will be forced to consider whether to ration care for the well-insured, a prospect that is odious and unthinkable to many. This book argues that sensible health care rationing can not only save money but improve general welfare and public health. It reviews the experience with health care rationing in Great Britain. The choices the British have made point up the nature of the options Americans will face if they wish to keep public health care budgets from driving taxes ever higher and private health care spending from crowding out increases in other forms of worker compensation and consumption. This book explains why serious consideration of health care rationing is inescapable. It also provides the information policymakers and concerned citizens need to think clearly about these difficult issues and engage in an informed debate.

To investigate trends in out-of-pocket health-care payments and catastrophic health expenditure in India by household age composition. We obtained data from four national consumer expenditure surveys and three health-care utilization surveys conducted between 1993 and 2014. Households were divided into five groups by age composition. We defined catastrophic health expenditure as out-of-pocket payments equalling or exceeding 10% of household expenditure. Factors associated with catastrophic expenditure were identified by multivariable analysis. Overall, the proportion of catastrophic health expenditure increased 1.47-fold between the 1993-1994 expenditure survey (12.4%) and the 2011-2012 expenditure survey (18.2%) and 2.24-fold between the 1995-1996 utilization survey (11.1%) and the 2014 utilization survey (24.9%). The proportion increased more in the poorest than the richest quintile: 3.00-fold versus 1.74-fold, respectively, across the utilization surveys. Catastrophic expenditure was commonest among households comprising only people aged 60 years or older: the adjusted odds ratio (aOR) was 3.26 (95% confidence interval, CI: 2.76-3.84) compared with households with no older people or children younger than 5 years. The risk was also increased among households with both older people and children (aOR: 2.58; 95% CI: 2.31-2.89), with a female head (aOR: 1.32; 95% CI: 1.19-1.47) and with a rural location (aOR: 1.27; 95% CI: 1.20-1.35). The proportion of households experiencing catastrophic health expenditure in India increased over the past two decades. Such expenditure was highest among households with older people. Financial protection mechanisms are needed for population groups at risk for catastrophic health expenditure.

Continuous economic growth and the rise in energy consumption are linked with environmental pollution. Demand for health care expenditure increased after the COVID-19 pandemic. This study is interesting in modeling the nexus between public and private health expenditure, carbon dioxide emissions, and economic growth. To this end, the present study analyzed the nexus between public and private health care expenditure, economic growth, and environmental pollution for 36 Asian countries for the period 1991–2017. FMOLS, GMM, and quantile regression analysis confirm the EKC hypothesis in Asia. Besides, FMOLS and quantile regressions reached the reducing effects of government and private health expenditures on CO 2 emissions. While quantile regression results show that public and private health expenditures can mitigate CO 2 emissions; however, these results differ for various levels of CO 2 . Findings of quantile regression show a significant impact of both public and private health expenditures in reducing CO 2 at the 50 th and 75 th quantiles but results are insignificant for the 25 th quantile. Overall, the paper concludes that both government and private health sectors’ expenditures caused CO 2 emissions to decrease in Asia and that the negative impact of the private health sector on CO 2 emissions is greater than that of the government health sector. The concluding remark is that the higher the health spending, the higher the environmental quality will be in Asia. Hence, the health administrators need to increase public and private health expenditures with an effective cost-service and energy-efficient management approach to reach sustainable health services and a sustainable environment in Asia.

Total nominal US health care spending increased 4.3 percent and reached $3.3 trillion in 2016. Per capita spending on health care increased by $354, reaching $10,348. The share of gross domestic product devoted to health care spending was 17.9 percent in 2016, up from 17.7 percent in 2015. Health spending growth decelerated in 2016 following faster growth in 2014 and 2015 associated with coverage expansions under the Affordable Care Act (ACA) and strong retail prescription drug spending growth. In 2016 the slowdown was broadly based, as spending for the largest categories by payer and by service decelerated. Enrollment trends drove the slowdown in Medicaid and private health insurance spending growth in 2016, while slower per enrollee spending growth influenced Medicare spending. Furthermore, spending for retail prescription drugs slowed, partly as a result of lower spending for drugs used to treat hepatitis C, while slower use and intensity of services drove the slowdown in hospital care and physician and clinical services.

Background Financial risk protection (FRP), defined as households’ access to needed healthcare services without experiencing undue financial hardship, is a critical health systems target, particularly in low- and middle-income countries (LMICs). Given the remarkable growth in FRP literature in recent times, we conducted a scoping review of the literature on FRP from out-of-pocket (OOP) health spending in LMICs. The objective was to review current knowledge, identify evidence gaps and propose future research directions. Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to conduct this scoping review. We systematically searched PubMed, Scopus, ProQuest and Web of Science in July 2021 for literature published since 1 January 2015. We included empirical studies that used nationally representative data from household surveys to measure the incidence of at least one of the following indicators: catastrophic health expenditure (CHE), impoverishment, adoption of strategies to cope with OOP expenses, and forgone care for financial reasons. Our review covered 155 studies and analysed the geographical focus, data sources, methods and analytical rigour of the studies. We also examined the level of FRP by disease categories (all diseases, chronic illnesses, communicable diseases) and the effect of health insurance on FRP. Results The extant literature primarily focused on India and China as research settings. Notably, no FRP study was available on chronic illness in any low-income country (LIC) or on communicable diseases in an upper-middle-income country (UMIC). Only one study comprehensively measured FRP by examining all four indicators. Most studies assessed (lack of) FRP as CHE incidence alone (37.4%) or as CHE and impoverishment incidence (39.4%). However, the LMIC literature did not incorporate the recent methodological advances to measure CHE and impoverishment that address the limitations of conventional methods. There were also gaps in utilizing available panel data to determine the length of the lack of FRP (e.g. duration of poverty caused by OOP expenses). The current estimates of FRP varied substantially among the LMICs, with some of the poorest countries in the world experiencing similar or even lower rates of CHE and impoverishment compared with the UMICs. Also, health insurance in LMICs did not consistently offer a higher degree of FRP. Conclusion The literature to date is unable to provide a reliable representation of the actual level of protection enjoyed by the LMIC population because of the lack of comprehensive measurement of FRP indicators coupled with the use of dated methodologies. Future research in LMICs should address the shortcomings identified in this review.