One of the most important gatherings of the world's economic leaders, the G20 Summit and ministerial meetings, takes place in June, 2019. The Summit presents a valuable opportunity to reflect on the provision and receipt of development assistance for health (DAH) and the role the G20 can have in shaping the future of health financing. The participants at the G20 Summit (ie, the world's largest providers of DAH, emerging donors, and DAH recipients) and this Summit's particular focus on global health and the Sustainable Development Goals offers a unique forum to consider the changing DAH context and its pressing questions. In this Health Policy perspective, we examined trends in DAH and its evolution over time, with a particular focus on G20 countries; pointed to persistent and emerging challenges for discussion at the G20 Summit; and highlighted key questions for G20 leaders to address to put the future of DAH on course to meet the expansive Sustainable Development Goals. Key questions include how to best focus DAH for equitable health gains, how to deliver DAH to strengthen health systems, and how to support domestic resource mobilisation and transformative partnerships for sustainable impact. These issues are discussed in the context of the growing effects of climate change, demographic and epidemiological transitions, and a global political shift towards increasing prioritisation of national interests. Although not all these questions are new, novel approaches to allocating DAH that prioritise equity, efficiency, and sustainability, particularly through domestic resource use and mobilisation are needed. Wrestling with difficult questions in a changing landscape is essential to develop a DAH financing system capable of supporting and sustaining crucial global health goals.
BACKGROUND: Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries.
METHODS: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health.
FINDINGS: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89-4·12) annually, although it grew slower in per capita terms (2·72% [2·61-2·84]) and increased by less than $1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55% [5·18-5·95]), mainly due to growth in government health spending, and in lower-middle-income countries (3·71% [3·10-4·34]), mainly from DAH. Health spending globally reached $8·0 trillion (7·8-8·1) in 2016 (comprising 8·6% [8·4-8·7] of the global economy and $10·3 trillion [10·1-10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$5252 (5184-5319) in high-income countries, $491 (461-524) in upper-middle-income countries, $81 (74-89) in lower-middle-income countries, and $40 (38-43) in low-income countries. In 2016, 0·4% (0·3-0·4) of health spending globally was in low-income countries, despite these countries comprising 10·0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ($9·5 billion, 24·3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ($644·7 million in 2018). Globally, health spending is projected to increase to $15·0 trillion (14·0-16·0) by 2050 (reaching 9·4% [7·6-11·3] of the global economy and $21·3 trillion [19·8-23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1·84% (1·68-2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0·6% (0·6-0·7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130·2 (122·9-136·9) in 2016 and is projected to remain at similar levels in 2050 (125·9 [113·7-138·1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending.
INTERPRETATION: Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.
FUNDING: Bill & Melinda Gates Foundation.
BACKGROUND: Between 2012 and 2016, development assistance for HIV/AIDS decreased by 20·0%; domestic financing is therefore critical to sustaining the response to HIV/AIDS. To understand whether domestic resources could fill the financing gaps created by declines in development assistance, we aimed to track spending on HIV/AIDS and estimated the potential for governments to devote additional domestic funds to HIV/AIDS.
METHODS: We extracted 8589 datapoints reporting spending on HIV/AIDS. We used spatiotemporal Gaussian process regression to estimate a complete time series of spending by domestic sources (government, prepaid private, and out-of-pocket) and spending category (prevention, and care and treatment) from 2000 to 2016 for 137 low-income and middle-income countries (LMICs). Development assistance data for HIV/AIDS were from Financing Global Health 2018, and HIV/AIDS prevalence, incidence, and mortality were from the Global Burden of Disease study 2017. We used stochastic frontier analysis to estimate potential additional government spending on HIV/AIDS, which was conditional on the current government health budget and other finance, economic, and contextual factors associated with HIV/AIDS spending. All spending estimates were reported in 2018 US$.
FINDINGS: Between 2000 and 2016, total spending on HIV/AIDS in LMICs increased from $4·0 billion (95% uncertainty interval 2·9-6·0) to $19·9 billion (15·8-26·3), spending on HIV/AIDS prevention increased from $596 million (258 million to 1·3 billion) to $3·0 billion (1·5-5·8), and spending on HIV/AIDS care and treatment increased from $1·1 billion (458·1 million to 2·2 billion) to $7·2 billion (4·3-11·8). Over this time period, the share of resources sourced from development assistance increased from 33·2% (21·3-45·0) to 46·0% (34·2-57·0). Care and treatment spending per year on antiretroviral therapy varied across countries, with an IQR of $284-2915. An additional $12·1 billion (8·4-17·5) globally could be mobilised by governments of LMICs to finance the response to HIV/AIDS. Most of these potential resources are concentrated in ten middle-income countries (Argentina, China, Colombia, India, Indonesia, Mexico, Nigeria, Russia, South Africa, and Vietnam).
INTERPRETATION: Some governments could mobilise more domestic resources to fight HIV/AIDS, which could free up additional development assistance for many countries without this ability, including many low-income, high-prevalence countries. However, a large gap exists between available financing and the funding needed to achieve global HIV/AIDS goals, and sustained and coordinated effort across international and domestic development partners is required to end AIDS by 2030.
FUNDING: The Bill & Melinda Gates Foundation.
BACKGROUND: Sustaining achievements in malaria control and making progress toward malaria elimination requires coordinated funding. We estimated domestic malaria spending by source in 106 countries that were malaria-endemic in 2000-16 or became malaria-free after 2000.
METHODS: We collected 36 038 datapoints reporting government, out-of-pocket (OOP), and prepaid private malaria spending, as well as malaria treatment-seeking, costs of patient care, and drug prices. We estimated government spending on patient care for malaria, which was added to government spending by national malaria control programmes. For OOP malaria spending, we used data reported in National Health Accounts and estimated OOP spending on treatment. Spatiotemporal Gaussian process regression was used to ensure estimates were complete and comparable across time and to generate uncertainty.
FINDINGS: In 2016, US$4·3 billion (95% uncertainty interval [UI] 4·2-4·4) was spent on malaria worldwide, an 8·5% (95% UI 8·1-8·9) per year increase over spending in 2000. Since 2000, OOP spending increased 3·8% (3·3-4·2) per year, amounting to $556 million (487-634) or 13·0% (11·6-14·5) of all malaria spending in 2016. Governments spent $1·2 billion (1·1-1·3) or 28·2% (27·1-29·3) of all malaria spending in 2016, increasing 4·0% annually since 2000. The source of malaria spending varied depending on whether countries were in the malaria control or elimination stage.
INTERPRETATION: Tracking global malaria spending provides insight into how far the world is from reaching the malaria funding target of $6·6 billion annually by 2020. Because most countries with a high burden of malaria are low income or lower-middle income, mobilising additional government resources for malaria might be challenging.
FUNDING: The Bill & Melinda Gates Foundation.
BACKGROUND: Financial risk protection (FRP) is a key objective of national health systems and a core pillar of universal health coverage (UHC). Yet, little is known about the disease-specific distribution of catastrophic health expenditure (CHE) at the national level.
METHODS: Using the World Health Surveys (WHS) from 39 countries, we quantified CHE, or household health spending that surpasses 40% of capacity-to-pay by key disease areas. We restricted our analysis to households in which the respondent used health care in the last 30 days and categorized CHE into disease areas included as WHS response options: maternal and child health (MCH); high fever, severe diarrhea, or cough; heart disease; asthma; injury; surgery; and other. We compared disease-specific CHE estimates by income, pooled funding as a share of total health expenditure, share of the population affected by the different diseases, and poverty status.
RESULTS: Across countries, an average of 45.1% of CHE cases could not be tied to a specific cause; 37.6% (95% UI 35.4-39.9%) of CHE cases were associated with high fever, severe cough, or diarrhea; 3.9% (3.0-4.9%) with MCH; and 4.1% (3.3-4.9%) with heart disease. Injuries constituted 5.2% (4.2-6.4%) of CHE cases. The distribution of CHE varied substantially by national income. A 10% increase in heart disease prevalence was associated with a 1.9% (1.3-2.4%) increase in heart disease CHE, an association stronger than any other disease area.
CONCLUSIONS: Our approach is comparable, comprehensive, and empirically based and highlights how financial risk protection may not be aligned with disease burden. Disease-specific CHE estimates can illuminate how health systems can target reform to best protect households from financial risk.
Building upon the successes of Countdown to 2015, Countdown to 2030 aims to support the monitoring and measurement of women's, children's, and adolescents' health in the 81 countries that account for 95% of maternal and 90% of all child deaths worldwide. To achieve the Sustainable Development Goals by 2030, the rate of decline in prevalence of maternal and child mortality, stillbirths, and stunting among children younger than 5 years of age needs to accelerate considerably compared with progress since 2000. Such accelerations are only possible with a rapid scale-up of effective interventions to all population groups within countries (particularly in countries with the highest mortality and in those affected by conflict), supported by improvements in underlying socioeconomic conditions, including women's empowerment. Three main conclusions emerge from our analysis of intervention coverage, equity, and drivers of reproductive, maternal, newborn, and child health (RMNCH) in the 81 Countdown countries. First, even though strong progress was made in the coverage of many essential RMNCH interventions during the past decade, many countries are still a long way from universal coverage for most essential interventions. Furthermore, a growing body of evidence suggests that available services in many countries are of poor quality, limiting the potential effect on RMNCH outcomes. Second, within-country inequalities in intervention coverage are reducing in most countries (and are now almost non-existent in a few countries), but the pace is too slow. Third, health-sector (eg, weak country health systems) and non-health-sector drivers (eg, conflict settings) are major impediments to delivering high-quality services to all populations. Although more data for RMNCH interventions are available now, major data gaps still preclude the use of evidence to drive decision making and accountability. Countdown to 2030 is investing in improvements in measurement in several areas, such as quality of care and effective coverage, nutrition programmes, adolescent health, early childhood development, and evidence for conflict settings, and is prioritising its regional networks to enhance local analytic capacity and evidence for RMNCH.
As growth in development assistance for health levels off, development assistance partners must make allocation decisions within tighter budget constraints. Furthermore, with the advent of comprehensive and comparable burden of disease and health financing estimates, empirical evidence can increasingly be used to direct funding to those most in need. In our 'financing gaps framework', we propose a new approach for harnessing information to make decisions about health aid. The framework was designed to be forward-looking, goal-oriented, versatile and customizable to a range of organizational contexts and health aims. Our framework brings together expected health spending, potential health spending and spending need, to orient financing decisions around international health targets. As an example of how the framework could be applied, we develop a case study, focused on global goals for child health. The case study harnesses data from the Global Burden of Disease 2013 Study, Financing Global Health 2015, the WHO Global Health Observatory and National Health Accounts. Funding flows are tied to progress toward the Sustainable Development Goal's target for reductions in under-five mortality. The flexibility and comprehensiveness of our framework makes it adaptable for use by a diverse set of governments, donors, policymakers and other stakeholders. The framework can be adapted to short- or long-run time frames, cross-country or subnational scales, and to a number of specific health focus areas. Depending on donor preferences, the framework can be deployed to incentivize local investments in health, ensuring the long-term sustainability of health systems in low- and middle-income countries, while also furnishing international support for progress toward global health goals.
BACKGROUND: To propose health system strategies to meeting the World Health Organization (WHO) recommendations on HIV screening through antenatal care (ANC) services, we assessed predictors of HIV screening, and simulated the impact of changes in these predictors on the probability of HIV screening in Guatemala, Honduras, Mexico (State of Chiapas), Nicaragua, Panama, and El Salvador.
METHODS: We interviewed a representative sample of women of reproductive age from the poorest Mesoamerican areas on ANC services, including HIV screening. We used a multivariate logistic regression model to examine correlates of HIV screening. First differences in expected probabilities of HIV screening were simulated for health system correlates that were associated with HIV screening.
RESULTS: Overall, 40.7% of women were screened for HIV during their last pregnancy through ANC. This rate was highest in El Salvador and lowest in Guatemala. The probability of HIV screening increased with education, household expenditure, the number of ANC visits, and the type of health care attendant of ANC visits. If all women were to be attended by a nurse, or a physician, and were to receive at least four ANC visits, the probability of HIV screening would increase by 12.5% to reach 45.8%.
CONCLUSIONS: To meet WHO's recommendations for HIV screening, special attention should be given to the poorest and least educated women to ensure health equity and progress toward an HIV-free generation. In parallel, health systems should be strengthened in terms of testing and human resources to ensure that every pregnant woman gets screened for HIV. A 12.5% increase in HIV screening would require a minimum of four ANC visits and an appropriate professional attendance of these visits.
Background: While there is increasing recognition that the non-technical aspects of health care quality - particularly the inter-personal dimensions of care - are important components of health system performance, evidence from population-based studies on these outcomes in low- and middle-income countries is sparse. This study assesses these non-technical aspects of care using two measures: health system responsiveness (HSR), which quantifies the degree to which the health system meets the expectations of the population, and non-technical health care quality (QoC), for which we 'filtered out' these expectations. Pooling data from six large middle-income countries, this study therefore aimed to determine how HSR and QoC vary between countries and by individuals' sociodemographic characteristics within countries.
Methods: We pooled individual-level data, collected between 2007 and 2010, from nationally representative household surveys of (primarily) adults aged 50 years and older in China, Ghana, India, Mexico, Russia, and South Africa. The outcome measure was a binary indicator for a 'bad' rating (HSR: "very bad" or "bad" on a five-point Likert scale; QoC: a worse rating of one's own visit than that of the character in an anchoring vignette) on at least one of seven dimensions for the most recent primary care visit.
Results: 23 749 adults who reported to have sought primary care during the preceding 12 months were includedin the analysis. The proportion of participants who gave a bad rating for their last primary care visit on at least one of seven dimensions varied from 4.3% (95% confidence interval (CI) = 2.8-6.7) in China to 33.1% (95% CI = 23.6-44.2) in South Africa for HSR, and from 17.0% (95% CI = 11.4-24.5) in Russia to 50.8% (95% CI = 46.0-55.6) in Ghana for QoC. There was a strong negative association between increasing household wealth and both bad HSR and QoC in India and South Africa.
Conclusions: Achieving universal health coverage (UHC) with good-quality health services ("effective UHC") will require efforts to improve HSR and QoC across the population in Ghana and South Africa. Additionally, a particular focus on raising HSR and QoC for the poorest population groups is needed in India and South Africa.
BACKGROUND: Comparable estimates of health spending are crucial for the assessment of health systems and to optimally deploy health resources. The methods used to track health spending continue to evolve, but little is known about the distribution of spending across diseases. We developed improved estimates of health spending by source, including development assistance for health, and, for the first time, estimated HIV/AIDS spending on prevention and treatment and by source of funding, for 188 countries.
METHODS: We collected published data on domestic health spending, from 1995 to 2015, from a diverse set of international agencies. We tracked development assistance for health from 1990 to 2017. We also extracted 5385 datapoints about HIV/AIDS spending, between 2000 and 2015, from online databases, country reports, and proposals submitted to multilateral organisations. We used spatiotemporal Gaussian process regression to generate complete and comparable estimates for health and HIV/AIDS spending. We report most estimates in 2017 purchasing-power parity-adjusted dollars and adjust all estimates for the effect of inflation.
FINDINGS: Between 1995 and 2015, global health spending per capita grew at an annualised rate of 3·1% (95% uncertainty interval [UI] 3·1 to 3·2), with growth being largest in upper-middle-income countries (5·4% per capita [UI 5·3-5·5]) and lower-middle-income countries (4·2% per capita [4·2-4·3]). In 2015, $9·7 trillion (9·7 trillion to 9·8 trillion) was spent on health worldwide. High-income countries spent $6·5 trillion (6·4 trillion to 6·5 trillion) or 66·3% (66·0 to 66·5) of the total in 2015, whereas low-income countries spent $70·3 billion (69·3 billion to 71·3 billion) or 0·7% (0·7 to 0·7). Between 1990 and 2017, development assistance for health increased by 394·7% ($29·9 billion), with an estimated $37·4 billion of development assistance being disbursed for health in 2017, of which $9·1 billion (24·2%) targeted HIV/AIDS. Between 2000 and 2015, $562·6 billion (531·1 billion to 621·9 billion) was spent on HIV/AIDS worldwide. Governments financed 57·6% (52·0 to 60·8) of that total. Global HIV/AIDS spending peaked at 49·7 billion (46·2-54·7) in 2013, decreasing to $48·9 billion (45·2 billion to 54·2 billion) in 2015. That year, low-income and lower-middle-income countries represented 74·6% of all HIV/AIDS disability-adjusted life-years, but just 36·6% (34·4 to 38·7) of total HIV/AIDS spending. In 2015, $9·3 billion (8·5 billion to 10·4 billion) or 19·0% (17·6 to 20·6) of HIV/AIDS financing was spent on prevention, and $27·3 billion (24·5 billion to 31·1 billion) or 55·8% (53·3 to 57·9) was dedicated to care and treatment.
INTERPRETATION: From 1995 to 2015, total health spending increased worldwide, with the fastest per capita growth in middle-income countries. While these national disparities are relatively well known, low-income countries spent less per person on health and HIV/AIDS than did high-income and middle-income countries. Furthermore, declines in development assistance for health continue, including for HIV/AIDS. Additional cuts to development assistance could hasten this decline, and risk slowing progress towards global and national goals.
FUNDING: The Bill & Melinda Gates Foundation.
BACKGROUND: Results-based aid (RBA) is increasingly used to incentivize action in health. In Mesoamerica, the region consisting of southern Mexico and Central America, the RBA project known as the Salud Mesoamérica Initiative (SMI) was designed to target disparities in maternal and child health, focusing on the poorest 20% of the population across the region.
METHODS AND FINDINGS: Data were first collected in 365 intervention health facilities to establish a baseline of indicators. For the first follow-up measure, 18 to 24 months later, 368 facilities were evaluated in these same areas. At both stages, we measured a near-identical set of supply-side performance indicators in line with country-specific priorities in maternal and child health. All countries showed progress in performance indicators, although with different levels. El Salvador, Honduras, Nicaragua, and Panama reached their 18-month targets, while the State of Chiapas in Mexico, Guatemala, and Belize did not. A second follow-up measurement in Chiapas and Guatemala showed continued progress, as they achieved previously missed targets nine to 12 months later, after implementing a performance improvement plan.
CONCLUSIONS: Our findings show an initial success in the supply-side indicators of SMI. Our data suggest that the RBA approach can be a motivator to improve availability of drugs and services in poor areas. Moreover, our innovative monitoring and evaluation framework will allow health officials with limited resources to identify and target areas of greatest need.
BACKGROUND: Considerable debate exists concerning the effects of antiretroviral therapy (ART) service scale-up on non-HIV services and overall health system performance in sub-Saharan Africa. In this study, we examined whether ART services affected trends in non-ART outpatient department (OPD) visits in Kenya and Uganda.
METHODS: Using a nationally representative sample of health facilities in Kenya and Uganda, we estimated the effect of ART programs on OPD visits from 2007 to 2012. We modeled the annual percent change in non-ART OPD visits using hierarchical mixed-effects linear regressions, controlling for a range of facility characteristics. We used four different constructs of ART services to capture the different ways in which the presence, growth, overall, and relative size of ART programs may affect non-ART OPD services.
RESULTS: Our final sample included 321 health facilities (140 in Kenya and 181 in Uganda). On average, OPD and ART visits increased steadily in Kenya and Uganda between 2007 and 2012. For facilities where ART services were not offered, the average annual increase in OPD visits was 4·2% in Kenya and 13·5% in Uganda. Among facilities that provided ART services, we found average annual OPD volume increases of 7·2% in Kenya and 5·6% in Uganda, with simultaneous annual increases of 13·7% and 12·5% in ART volumes. We did not find a statistically significant relationship between annual changes in OPD services and the presence, growth, overall, or relative size of ART services. However, in a subgroup analysis, we found that Ugandan hospitals that offered ART services had statistically significantly less growth in OPD visits than Ugandan hospitals that did not provide ART services.
CONCLUSIONS: Our findings suggest that ART services in Kenya and Uganda did not have a statistically significant deleterious effects on OPD services between 2007 and 2012, although subgroup analyses indicate variation by facility type. Our findings are encouraging, particularly given recent recommendations for universal access to ART, demonstrating that expanding ART services is not inherently linked to declines in other health services in sub-Saharan Africa.
BACKGROUND: Donor financing for malaria has declined since 2010 and this trend is projected to continue for the foreseeable future. These reductions have a significant impact on lower burden countries actively pursuing elimination, which are usually a lesser priority for donors. While domestic spending on malaria has been growing, it varies substantially in speed and magnitude across countries. A clear understanding of spending patterns and trends in donor and domestic financing is needed to uncover critical investment gaps and opportunities.
METHODS: Building on the Institute for Health Metrics and Evaluation's annual Financing Global Health research, data were collected from organizations that channel development assistance for health to the 35 countries actively pursuing malaria elimination. Where possible, development assistance for health (DAH) was categorized by spend on malaria intervention. A diverse set of data points were used to estimate government health budgets expenditure on malaria, including World Malaria Reports and government reports when available. Projections were done using regression analyses taking recipient country averages and earmarked funding into account.
RESULTS: Since 2010, DAH for malaria has been declining for the 35 countries actively pursuing malaria elimination (from $176 million in 2010 to $62 million in 2013). The Global Fund is the largest external financier for malaria, providing 96% of the total external funding for malaria in 2013, with vector control interventions being the highest cost driver in all regions. Government expenditure on malaria, while increasing, has not kept pace with diminishing DAH or rising national GDP rates, leading to a potential gap in service delivery needed to attain elimination.
CONCLUSION: Despite past gains, total financing available for malaria in elimination settings is declining. Health financing trends suggest that substantive policy interventions will be needed to ensure that malaria elimination is adequately financed and that available financing is effectively targeted to interventions that provide the best value for money.
Professional skilled care has shown to be one of the most promising strategies to reduce maternal mortality, and in-facility deliveries are a cost-effective way to ensure safe births. Countries in Mesoamerica have emphasized in-facility delivery care by professionally skilled attendants, but access to good-quality delivery care is still lacking for many women. We examined the characteristics of women who had a delivery in a health facility and determinants of the decision to bypass a closer facility and travel to a distant one. We used baseline information from the Salud Mesoamerica Initiative (SMI). Data were collected from a large household and facilities sample in the poorest quintile of the population in Guatemala, Honduras and Nicaragua. The analysis included 1592 deliveries. After controlling for characteristics of women and health facilities, being primiparous (RR = 1.15, 95% CI 1.10, 1.21), being literate (RR = 1.24, 95% CI 1.04, 1.48), having antenatal care (RR = 1.68, 95% CI 1.24, 2.27), being informed of the need for having a C-section (RR = 1.07, 95% CI 1.02, 1.11) and travel time to the closest facility totaling 1-2 h vs under 30 min (RR = 0.88, 95% CI 0.77, 0.99) were associated with in-health facility deliveries. In Guatemala, increased availability of medications and equipment at a distant facility was strongly associated with bypassing the closest facility in favor of a distant one for delivery (RR = 2.10, 95% CI 1.08, 4.07). Our study showed a strong correlation between well-equipped facilities and delivery attendance in poor areas of Mesoamerica. Indeed, women were more likely to travel to more distant facilities if the facilities were of higher level, which scored higher on our capacity score. Our findings call for improving the capacity of health facilities, quality of care and addressing cultural and accessibility barriers to increase institutional delivery among the poor population in Mesoamerica.
BACKGROUND: An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends.
METHODS: We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development.
FINDINGS: Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3·0%. The largest health spending growth rates were in upper-middle-income (5·9) and lower-middle-income groups (5·0), which both increased spending at more than 5% per year, and spent $914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4·6%, and health spending increased from $51 to $120 per capita. In 2014, 59·2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29·1% and 58·0% of spending was OOP spending and 35·7% and 3·0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1·8%, and reached US$37·6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount.
INTERPRETATION: Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.
FUNDING: The Bill & Melinda Gates Foundation.
BACKGROUND: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending.
METHODS: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted.
FINDINGS: We estimated that global spending on health will increase from US$9·21 trillion in 2014 to $24·24 trillion (uncertainty interval [UI] 20·47-29·72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5·3% (UI 4·1-6·8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4·2% (3·8-4·9). High-income countries are expected to grow at 2·1% (UI 1·8-2·4) and low-income countries are expected to grow at 1·8% (1·0-2·8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and $195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries.
INTERPRETATION: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.
FUNDING: Bill & Melinda Gates Foundation.
BACKGROUND: In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015).
METHODS: We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices.
FINDINGS: In 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8-61·8) and varied widely by country, ranging from 85·5 (84·2-86·5) in Iceland to 20·4 (15·4-24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r=0·88) and the MDG index (r=0·92), whereas the non-MDG index had a weaker relation with SDI (r=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0-10·4), and gains on the MDG index (a median change of 10·0 [6·7-13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1-8·9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened.
INTERPRETATION: GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.
FUNDING: Bill & Melinda Gates Foundation.