More Data and Appropriate Statistical Methods Needed to Fully Measure the Displacement Effects of Development Assistance for Health

Christopher Murray and colleagues provide a perspective on displacement due to development assistance for health, and argue for more data and better statistical methods to measure aid displacement

Estimating health spending associated with chronic multimorbidity in 2018:An observational study among adults in the United States

BACKGROUND: The rise in health spending in the United States and the prevalence of multimorbidity-having more than one chronic condition-are interlinked but not well understood. Multimorbidity is believed to have an impact on an individual's health spending, but how having one specific additional condition impacts spending is not well established. Moreover, most studies estimating spending for single diseases rarely adjust for multimorbidity. Having more accurate estimates of spending associated with each disease and different combinations could aid policymakers in designing prevention policies to more effectively reduce national health spending. This study explores the relationship between multimorbidity and spending from two distinct perspectives: (1) quantifying spending on different disease combinations; and (2) assessing how spending on a single diseases changes when we consider the contribution of multimorbidity (i.e., additional/reduced spending that could be attributed in the presence of other chronic conditions). METHODS AND FINDINGS: We used data on private claims from Truven Health MarketScan Research Database, with 16,288,894 unique enrollees ages 18 to 64 from the US, and their annual inpatient and outpatient diagnoses and spending from 2018. We selected conditions that have an average duration of greater than one year among all Global Burden of Disease causes. We used penalized linear regression with stochastic gradient descent approach to assess relationship between spending and multimorbidity, including all possible disease combinations with two or three different conditions (dyads and triads) and for each condition after multimorbidity adjustment. We decomposed the change in multimorbidity-adjusted spending by the type of combination (single, dyads, and triads) and multimorbidity disease category. We defined 63 chronic conditions and observed that 56.2% of the study population had at least two chronic conditions. Approximately 60.1% of disease combinations had super-additive spending (e.g., spending for the combination was significantly greater than the sum of the individual diseases), 15.7% had additive spending, and 23.6% had sub-additive spending (e.g., spending for the combination was significantly less than the sum of the individual diseases). Relatively frequent disease combinations (higher observed prevalence) with high estimated spending were combinations that included endocrine, metabolic, blood, and immune disorders (EMBI disorders), chronic kidney disease, anemias, and blood cancers. When looking at multimorbidity-adjusted spending for single diseases, the following had the highest spending per treated patient and were among those with high observed prevalence: chronic kidney disease ($14,376 [12,291,16,670]), cirrhosis ($6,465 [6,090,6,930]), ischemic heart disease (IHD)-related heart conditions ($6,029 [5,529,6,529]), and inflammatory bowel disease ($4,697 [4,594,4,813]). Relative to unadjusted single-disease spending estimates, 50 conditions had higher spending after adjusting for multimorbidity, 7 had less than 5% difference, and 6 had lower spending after adjustment. CONCLUSIONS: We consistently found chronic kidney disease and IHD to be associated with high spending per treated case, high observed prevalence, and contributing the most to spending when in combination with other chronic conditions. In the midst of a surging health spending globally, and especially in the US, pinpointing high-prevalence, high-spending conditions and disease combinations, as especially conditions that are associated with larger super-additive spending, could help policymakers, insurers, and providers prioritize and design interventions to improve treatment effectiveness and reduce spending.</p

Tracking development assistance for health to fragile states: 2005–2011

BACKGROUND: Development assistance for health (DAH) has grown substantially, totaling more than $31.3 billion in 2013. However, the degree that countries with high concentrations of armed conflict, ethnic violence, inequality, debt, and corruption have received this health aid and how that assistance might be different from the funding provided to other countries has not been assessed. METHODS: We combine DAH estimates and a multidimensional fragile states index for 2005 through 2011. We disaggregate and compare total DAH disbursed for fragile states versus stable states. RESULTS: Between 2005 and 2011, DAH per person in fragile countries increased at an annualized rate of 5.4$6.2 billion, which is $5.05 per person. This is 43$7.22 per person while stable countries received $11.15 per person. Relative to stable countries, donors preferred to provide more funding to low-income fragile countries that have refugees or ongoing external intervention but tended to avoid providing funding to countries with political gridlock, flawed elections, or economic decline. In 2011, Ethiopia received the most health aid of all fragile countries, while the United States provided the most funds to fragile countries. CONCLUSIONS: In 2011, 1.2 billion people lived in fragile countries. DAH can bolster health systems and might be especially valuable in providing long-term stability in fragile environments. While external health funding to these countries has increased since 2005, it is, in per person terms, almost half as much as the DAH provided to stable countries of comparable income levels. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12992-015-0097-9) contains supplementary material, which is available to authorized users

Development assistance for human resources for health, 1990–2020

Background: Investing in the health workforce is key to achieving the health-related Sustainable Development Goals. However, achieving these Goals requires addressing a projected global shortage of 18 million health workers (mostly in low- and middle-income countries). Within that context, in 2016, the World Health Assembly adopted the WHO Global Strategy on Human Resources for Health: Workforce 2030. In the Strategy, the role of official development assistance to support the health workforce is an area of interest. The objective of this study is to examine progress on implementing the Global Strategy by updating previous analyses that estimated and examined official development assistance targeted towards human resources for health. Methods: We leveraged data from IHME’s Development Assistance for Health database, COVID development assistance database and the OECD’s Creditor Reporting System online database. We utilized an updated keyword list to identify the relevant human resources for health-related activities from the project databases. When possible, we also estimated the fraction of human resources for health projects that considered and/or focused on gender as a key factor. We described trends, examined changes in the availability of human resources for health-related development assistance since the adoption of the Global Strategy and compared disease burden and availability of donor resources. Results: Since 2016, development assistance for human resources for health has increased with a slight dip in 2019. In 2020, fueled by the onset of the COVID-19 pandemic, it reached an all-time high of USD 4.1 billion, more than double its value in 2016 and a 116.5% increase over 2019. The highest share (42.4%) of support for human resources for health-related activities has been directed towards training. Since the adoption of the Global Strategy, donor resources for health workforce-related activities have on average increased by 13.3% compared to 16.0% from 2000 through 2015. For 47 countries identified by the WHO as having severe workforce shortages, the availability of donor resources remains modest. Conclusions: Since 2016, donor support for health workforce-related activities has increased. However, there are lingering concerns related to the short-term nature of activities that donor funding supports and its viability for creating sustainable health systems

The health-adjusted dependency ratio as a new global measure of the burden of ageing: a population-based study.

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Estimating the development assistance for health provided to faith-based organizations, 1990-2013

BACKGROUND: Faith-based organizations (FBOs) have been active in the health sector for decades. Recently, the role of FBOs in global health has been of increased interest. However, little is known about the magnitude and trends in development assistance for health (DAH) channeled through these organizations. Material and METHODS: Data were collected from the 21 most recent editions of the Report of Voluntary Agencies. These reports provide information on the revenue and expenditure of organizations. Project-level data were also collected and reviewed from the Bill & Melinda Gates Foundation and the Global Fund to Fight AIDS, Tuberculosis and Malaria. More than 1,900 non-governmental organizations received funds from at least one of these three organizations. Background information on these organizations was examined by two independent reviewers to identify the amount of funding channeled through FBOs. RESULTS: In 2013, total spending by the FBOs identified in the VolAg amounted to US$1.53 billion. In 1990, FB0s spent 34.1$80.9 million in 2011, or 16.7% of the Global Fund's contributions to NGOs. In 2011, the Gates Foundation's contributions to FBOs amounted to $7.1 million, or 1.1% of the total provided to NGOs. CONCLUSION: Development assistance partners exhibit a range of preferences with respect to the amount of funds provided to FBOs. Overall, estimates show that FBOS have maintained a substantial and consistent share over time, in line with overall spending in global health on NGOs. These estimates provide the foundation for further research on the spending trends and effectiveness of FBOs in global health

Financing health in sub-Saharan Africa 1990–2050: Donor dependence and expected domestic health spending

In 2021, global life expectancy at birth was 74 years whereas in sub-Saharan Africa it was 66 years. Yet in that same year, $92 per person was spent on health in sub- Saharan Africa, which is roughly one fifth of what the next lowest geographic region—North Africa and Middle East—spent ($379). The challenges to healthy lives in sub-Saharan Africa are many while health spending remains low. This study uses gross domestic product, government, and health spending data to give a more complete picture of the patterns of future health spending in sub-Saharan Africa. We analyzed trends in growth in gross domestic product, government health spending, development assistance for health and the prioritization of health in national spending to compare countries within sub-Saharan Africa and globally.We found that while gross domestic product was projected to increase through 2050 in sub-Saharan Africa, the share of gross domestic product that goes to health spending is only expected to increase moderately. Our exploration shows that this tepid growth is expected because the percent of overall government spending that is dedicated to health 7·2% (6·3–8·3) compared to average of 12·4% (11·7–13·2) in other regions) is expected to stay low. Even if the amount, of resources provided from donors climbs some, it is not expected to keep pace with growing economies in sub-Saharan Africa and may transition towards other global public health goods. Critically, development assistance for health provided to sub-Saharan Africa is expected to decrease in some countries, and the expected growth in government health spending might not be enough to cover this expected decline. Increases in spending with a concordant prioritization of health and the appropriate health system governance and structural reforms are critical to ensure that people who live in sub-Saharan Africa are not left behind

Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

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.Peer reviewe

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

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

Health expenditures by services and providers for 195 countries, 2000-2017

Introduction National Health Accounts are a significant source of health expenditure data, designed to be comprehensive and comparable across countries. However, there is currently no single repository of this data and even when compiled major gaps persist. This research aims to provide policymakers and researchers with a single repository of available national health expenditures by healthcare functions (ie, services) and providers of such services. Leveraging these data within statistical methods, a complete set of detailed health expenditures is estimated. Methods A methodical compilation and synthesis of all available national health expenditure reports including disaggregation by healthcare functions and providers was conducted. Using these data, a Bayesian multivariate regression analysis was implemented to estimate national-level health expenditures by the cross-classification of functions and providers for 195 countries, from 2000 to 2017. Results This research used 1662 country-years and 110 070 data points of health expenditures from existing National Health Accounts. The most detailed country-year had 52% of the categories of interest reported. Of all health functions, curative care and medical goods were estimated to make up 51.4% (uncertainty interval (UI) 33.2% to 59.4%) and 17.5% (UI 13.0% to 26.9%) of total global health expenditures in 2017, respectively. Three-quarters of the global health expenditures are allocated to three categories of providers: hospital providers (35.4%, UI 30.3% to 38.9%), providers of ambulatory care (25.5%, UI 21.1% to 28.8%) and retailers of medical goods (14.4%, UI 12.4% to 16.3%). As gross domestic product increases, countries spend more on long-term care and less on preventive care. Conclusion Disaggregated estimates of health expenditures are often unavailable and unable to provide policymakers and researchers a holistic understanding of how expenditures are used. This research aggregates reported data and provides a complete time-series of estimates, with uncertainty, of health expenditures by health functions and providers between 2000 and 2017 for 195 countries.</p