Factors Associated With Increases in US Health Care Spending, 1996-2013

IMPORTANCE

Health care spending in the United States increased substantially from 1995 to 2015 and comprised 17.8% of the economy in 2015. Understanding the relationship between known factors and spending increases over time could inform policy efforts to contain future spending growth.

OBJECTIVE

To quantify changes in spending associated with 5 fundamental factors related to health care spending in the United States: population size, population age structure, disease prevalence or incidence, service utilization, and service price and intensity.

DESIGN AND SETTING

Data on the 5 factors from 1996 through 2013 were extracted for 155 health conditions, 36 age and sex groups, and 6 types of care from the Global Burden of Disease 2015 study and the Institute for Health Metrics and Evaluation's US Disease Expenditure 2013 project. Decomposition analysis was performed to estimate the association between changes in these factors and changes in health care spending and to estimate the variability across health conditions and types of care.

EXPOSURES

Change in population size, population aging, disease prevalence or incidence, service utilization, or service price and intensity.

MAIN OUTCOMES AND MEASURES

Change in health care spending from 1996 through 2013.

RESULTS

After adjustments for price inflation, annual health care spending on inpatient, ambulatory, retail pharmaceutical, nursing facility, emergency department, and dental care increased by $933.5 billion between 1996 and 2013, from $1.2 trillion to $2.1 trillion. Increases in US population size were associated with a 23.1% (uncertainty interval [UI], 23.1%-23.1%), or $269.5 (UI, $269.0-$270.0) billion, spending increase; aging of the population was associated with an 11.6% (UI, 11.4%-11.8%), or $135.7 (UI, $133.3-$137.7) billion, spending increase. Changes in disease prevalence or incidence were associated with spending reductions of 2.4% (UI, 0.9%-3.8%), or $28.2 (UI, $10.5-$44.4) billion, whereas changes in service utilization were not associated with a statistically significant change in spending. Changes in service price and intensity were associated with a 50.0% (UI, 45.0%-55.0%), or $583.5 (UI, $525.2-$641.4) billion, spending increase. The influence of these 5 factors varied by health condition and type of care. For example, the increase in annual diabetes spending between 1996 and 2013 was $64.4 (UI, $57.9-$70.6) billion; $44.4 (UI, $38.7-$49.6) billion of this increase was pharmaceutical spending.

CONCLUSIONS AND RELEVANCE

Increases in US health care spending from 1996 through 2013 were largely related to increases in health care service price and intensity but were also positively associated with population growth and aging and negatively associated with disease prevalence or incidence. Understanding these factors and their variability across health conditions and types of care may inform policy efforts to contain health care spending.

The burden of cancer in Mexico, 1990-2013

OBJECTIVE

To analyze mortality and incidence for 28 cancers by deprivation status, age and sex from 1990 to 2013.

MATERIALS AND METHODS

The data and methodological approaches provided by the Global Burden of Disease (GBD 2013) were used.

RESULTS

Trends from 1990 to 2013 show important changes in cancer epidemiology in Mexico. While some cancers show a decreasing trend in incidence and mortality (lung, cervical) others emerge as relevant health priorities (prostate, breast, stomach, colorectal and liver cancer). Age standardized incidence and mortality rates for all cancers are higher in the northern states while the central states show a decreasing trend in the mortality rate. The analysis show that infection related cancers like cervical or liver cancer play a bigger role in more deprived states and that cancers with risk factors related to lifestyle like colorectal cancer are more common in less marginalized states.

CONCLUSIONS

The burden of cancer in Mexico shows complex regional patterns by age, sex, types of cancer and deprivation status. Creation of a national cancer registry is crucial.

Adjusting health spending for the presence of comorbidities: an application to United States national inpatient data

BACKGROUND

One of the major challenges in estimating health care spending spent on each cause of illness is allocating spending for a health care event to a single cause of illness in the presence of comorbidities. Comorbidities, the secondary diagnoses, are common across many causes of illness and often correlate with worse health outcomes and more expensive health care. In this study, we propose a method for measuring the average spending for each cause of illness with and without comorbidities.

METHODS

Our strategy for measuring cause of illness-specific spending and adjusting for the presence of comorbidities uses a regression-based framework to estimate excess spending due to comorbidities. We consider multiple causes simultaneously, allowing causes of illness to appear as either a primary diagnosis or a comorbidity. Our adjustment method distributes excess spending away from primary diagnoses (outflows), exaggerated due to the presence of comorbidities, and allocates that spending towards causes of illness that appear as comorbidities (inflows). We apply this framework for spending adjustment to the National Inpatient Survey data in the United States for years 1996-2012 to generate comorbidity-adjusted health care spending estimates for 154 causes of illness by age and sex.

RESULTS

The primary diagnoses with the greatest number of comorbidities in the NIS dataset were acute renal failure, septicemia, and endocarditis. Hypertension, diabetes, and ischemic heart disease were the most common comorbidities across all age groups. After adjusting for comorbidities, chronic kidney diseases, atrial fibrillation and flutter, and chronic obstructive pulmonary disease increased by 74.1%, 40.9%, and 21.0%, respectively, while pancreatitis, lower respiratory infections, and septicemia decreased by 21.3%, 17.2%, and 16.0%. For many diseases, comorbidity adjustments had varying effects on spending for different age groups.

CONCLUSIONS

Our methodology takes a unified approach to account for excess spending caused by the presence of comorbidities. Adjusting for comorbidities provides a substantially altered, more accurate estimate of the spending attributed to specific cause of illness. Making these adjustments supports improved resource tracking, accountability, and planning for future resource allocation.

Spending on Children's Personal Health Care in the United States, 1996-2013

IMPORTANCE

Health care spending on children in the United States continues to rise, yet little is known about how this spending varies by condition, age and sex group, and type of care, nor how these patterns have changed over time.

OBJECTIVE

To provide health care spending estimates for children and adolescents 19 years and younger in the United States from 1996 through 2013, disaggregated by condition, age and sex group, and type of care.

EVIDENCE REVIEW

Health care spending estimates were extracted from the Institute for Health Metrics and Evaluation Disease Expenditure 2013 project database. This project, based on 183 sources of data and 2.9 billion patient records, disaggregated health care spending in the United States by condition, age and sex group, and type of care. Annual estimates were produced for each year from 1996 through 2013. Estimates were adjusted for the presence of comorbidities and are reported using inflation-adjusted 2015 US dollars.

FINDINGS

From 1996 to 2013, health care spending on children increased from $149.6 (uncertainty interval [UI], 144.1-155.5) billion to $233.5 (UI, 226.9-239.8) billion. In 2013, the largest health condition leading to health care spending for children was well-newborn care in the inpatient setting. Attention-deficit/hyperactivity disorder and well-dental care (including dental check-ups and orthodontia) were the second and third largest conditions, respectively. Spending per child was greatest for infants younger than 1 year, at $11 741 (UI, 10 799-12 765) in 2013. Across time, health care spending per child increased from $1915 (UI, 1845-1991) in 1996 to $2777 (UI, 2698-2851) in 2013. The greatest areas of growth in spending in absolute terms were ambulatory care among all types of care and inpatient well-newborn care, attention-deficit/hyperactivity disorder, and asthma among all conditions.

CONCLUSIONS AND RELEVANCE

These findings provide health policy makers and health care professionals with evidence to help guide future spending. Some conditions, such as attention-deficit/hyperactivity disorder and inpatient well-newborn care, had larger health care spending growth rates than other conditions.

US Spending on Personal Health Care and Public Health, 1996-2013

IMPORTANCE

US health care spending has continued to increase, and now accounts for more than 17% of the US economy. Despite the size and growth of this spending, little is known about how spending on each condition varies by age and across time.

OBJECTIVE

To systematically and comprehensively estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care.

DESIGN AND SETTING

Government budgets, insurance claims, facility surveys, household surveys, and official US records from 1996 through 2013 were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions). For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Spending was adjusted to reflect the health condition treated, rather than the primary diagnosis.

EXPOSURES

Encounter with US health care system.

MAIN OUTCOMES AND MEASURES

National spending estimates stratified by condition, age and sex group, and type of care.

RESULTS

From 1996 through 2013, $30.1 trillion of personal health care spending was disaggregated by 155 conditions, age and sex group, and type of care. Among these 155 conditions, diabetes had the highest health care spending in 2013, with an estimated $101.4 billion (uncertainty interval [UI], $96.7 billion-$106.5 billion) in spending, including 57.6% (UI, 53.8%-62.1%) spent on pharmaceuticals and 23.5% (UI, 21.7%-25.7%) spent on ambulatory care. Ischemic heart disease accounted for the second-highest amount of health care spending in 2013, with estimated spending of $88.1 billion (UI, $82.7 billion-$92.9 billion), and low back and neck pain accounted for the third-highest amount, with estimated health care spending of $87.6 billion (UI, $67.5 billion-$94.1 billion). The conditions with the highest spending levels varied by age, sex, type of care, and year. Personal health care spending increased for 143 of the 155 conditions from 1996 through 2013. Spending on low back and neck pain and on diabetes increased the most over the 18 years, by an estimated $57.2 billion (UI, $47.4 billion-$64.4 billion) and $64.4 billion (UI, $57.8 billion-$70.7 billion), respectively. From 1996 through 2013, spending on emergency care and retail pharmaceuticals increased at the fastest rates (6.4% [UI, 6.4%-6.4%] and 5.6% [UI, 5.6%-5.6%] annual growth rate, respectively), which were higher than annual rates for spending on inpatient care (2.8% [UI, 2.8%-2.8%] and nursing facility care (2.5% [UI, 2.5%-2.5%]).

CONCLUSIONS AND RELEVANCE

Modeled estimates of US spending on personal health care and public health showed substantial increases from 1996 through 2013; with spending on diabetes, ischemic heart disease, and low back and neck pain accounting for the highest amounts of spending by disease category. The rate of change in annual spending varied considerably among different conditions and types of care. This information may have implications for efforts to control US health care spending.

Assessing the Complex and Evolving Relationship between Charges and Payments in US Hospitals: 1996 - 2012

BACKGROUND

In 2013 the United States spent $2.9 trillion on health care, more than in any previous year. Much of the debate around slowing health care spending growth focuses on the complicated pricing system for services. Our investigation contributes to knowledge of health care spending by assessing the relationship between charges and payments in the inpatient hospital setting. In the US, charges and payments differ because of a complex set of incentives that connect health care providers and funders. Our methodology can also be applied to adjust charge data to reflect actual spending.

METHODS

We extracted cause of health care encounter (cause), primary payer (payer), charge, and payment information for 50,172 inpatient hospital stays from 1996 through 2012. We used linear regression to assess the relationship between charges and payments, stratified by payer, year, and cause. We applied our estimates to a large, nationally representative hospital charge sample to estimate payments.

RESULTS

The average amount paid per $1 charged varies significantly across three dimensions: payer, year, and cause. Among the 10 largest causes of health care spending, average payments range from 23 to 55 cents per dollar charged. Over time, the amount paid per dollar charged is decreasing for those with private or public insurance, signifying that inpatient charges are increasing faster than the amount insurers pay. Conversely, the amount paid by out-of-pocket payers per dollar charged is increasing over time for several causes. Applying our estimates to a nationally representative hospital charge sample generates payment estimates which align with the official US estimates of inpatient spending.

CONCLUSIONS

The amount paid per $1 charged fluctuates significantly depending on the cause of a health care encounter and the primary payer. In addition, the amount paid per charge is changing over time. Transparent accounting of hospital spending requires a detailed assessment of the substantial and growing gap between charges and payments. Understanding what is driving this divergence and generating accurate spending estimates can inform efforts to contain health care spending.

Development assistance for health: past trends, associations, and the future of international financial flows for health

BACKGROUND

Disbursements of development assistance for health (DAH) have risen substantially during the past several decades. More recently, the international community's attention has turned to other international challenges, introducing uncertainty about the future of disbursements for DAH.

METHODS

We collected audited budget statements, annual reports, and project-level records from the main international agencies that disbursed DAH from 1990 to the end of 2015. We standardised and combined records to provide a comprehensive set of annual disbursements. We tracked each dollar of DAH back to the source and forward to the recipient. We removed transfers between agencies to avoid double-counting and adjusted for inflation. We classified assistance into nine primary health focus areas: HIV/AIDS, tuberculosis, malaria, maternal health, newborn and child health, other infectious diseases, non-communicable diseases, Ebola, and sector-wide approaches and health system strengthening. For our statistical analysis, we grouped these health focus areas into two categories: MDG-related focus areas (HIV/AIDS, tuberculosis, malaria, child and newborn health, and maternal health) and non-MDG-related focus areas (other infectious diseases, non-communicable diseases, sector-wide approaches, and other). We used linear regression to test for structural shifts in disbursement patterns at the onset of the Millennium Development Goals (MDGs; ie, from 2000) and the global financial crisis (impact estimated to occur in 2010). We built on past trends and associations with an ensemble model to estimate DAH through the end of 2040.

FINDINGS

In 2015, US$36·4 billion of DAH was disbursed, marking the fifth consecutive year of little change in the amount of resources provided by global health development partners. Between 2000 and 2009, DAH increased at 11·3% per year, whereas between 2010 and 2015, annual growth was just 1·2%. In 2015, 29·7% of DAH was for HIV/AIDS, 17·9% was for child and newborn health, and 9·8% was for maternal health. Linear regression identifies three distinct periods of growth in DAH. Between 2000 and 2009, MDG-related DAH increased by $290·4 million (95% uncertainty interval [UI] 174·3 million to 406·5 million) per year. These increases were significantly greater than were increases in non-MDG DAH during the same period (p=0·009), and were also significantly greater than increases in the previous period (p<0·0001). Between 2000 and 2009, growth in DAH was highest for HIV/AIDS, malaria, and tuberculosis. Since 2010, DAH for maternal health and newborn and child health has continued to climb, although DAH for HIV/AIDS and most other health focus areas has remained flat or decreased. Our estimates of future DAH based on past trends and associations present a wide range of potential futures, although our mean estimate of $64·1 billion (95% UI $30·4 billion to $161·8 billion) shows an increase between now and 2040, although with a large uncertainty interval.

INTERPRETATION

Our results provide evidence of two substantial shifts in DAH growth during the past 26 years. DAH disbursements increased faster in the first decade of the 2000s than in the 1990s, but DAH associated with the MDGs increased the most out of all focus areas. Since 2010, limited growth has characterised DAH and we expect this pattern to persist. Despite the fact that DAH is still growing, albeit minimally, DAH is shifting among the major health focus areas, with relatively little growth for HIV/AIDS, malaria, and tuberculosis. These changes in the growth and focus of DAH will have critical effects on health services in some low-income countries. Coordination and collaboration between donors and domestic governments is more important than ever because they have a great opportunity and responsibility to ensure robust health systems and service provision for those most in need.

FUNDING

Bill & Melinda Gates Foundation.

Tracking development assistance for HIV/AIDS: the international response to a global epidemic

OBJECTIVE

To better understand the global response to HIV/AIDS, this study tracked development assistance for HIV/AIDS at a granular, program level.

METHODS

We extracted data from the Institute for Health Metrics and Evaluation's Financing Global Health 2015 report that captured development assistance for HIV/AIDS from 1990 to 2015 for all major bilateral and multilateral aid agencies. To build on these data, we extracted additional budget data, and disaggregated development assistance for HIV/AIDS into nine program areas, including prevention, treatment, and health system support.

RESULTS

Since 2000, $109.8 billion of development assistance has been provided for HIV/AIDS. Between 2000 and 2010, development assistance for HIV/AIDS increased at an annualized rate of 22.8%. Since 2010, the annualized rate of growth has dropped to 1.3%. Had development assistance for HIV/AIDS continued to climb after 2010 as it had in the previous decade, $44.8 billion more in development assistance would have been available for HIV/AIDS. Since 1990, treatment and prevention were the most funded HIV/AIDS program areas receiving $24.6 billion and $22.7 billion, respectively. Since 2010, these two program areas and HIV/AIDS health system strengthening have continued to grow, marginally, with majority support from the US government and the Global Fund. An average of $252.9 of HIV/AIDS development assistance per HIV/AIDS prevalent case was disbursed between 2011 and 2013.

CONCLUSION

The scale-up of development assistance for HIV/AIDS from 2000 to 2010 was unprecedented. During this period, international donors prioritized HIV/AIDS treatment, prevention, and health system support. Since 2010, funding for HIV/AIDS has plateaued.

The Global Burden of Cancer 2013

IMPORTANCE

Cancer is among the leading causes of death worldwide. Current estimates of cancer burden in individual countries and regions are necessary to inform local cancer control strategies.

OBJECTIVE

To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 28 cancers in 188 countries by sex from 1990 to 2013.

EVIDENCE REVIEW

The general methodology of the Global Burden of Disease (GBD) 2013 study was used. Cancer registries were the source for cancer incidence data as well as mortality incidence (MI) ratios. Sources for cause of death data include vital registration system data, verbal autopsy studies, and other sources. The MI ratios were used to transform incidence data to mortality estimates and cause of death estimates to incidence estimates. Cancer prevalence was estimated using MI ratios as surrogates for survival data; YLDs were calculated by multiplying prevalence estimates with disability weights, which were derived from population-based surveys; YLLs were computed by multiplying the number of estimated cancer deaths at each age with a reference life expectancy; and DALYs were calculated as the sum of YLDs and YLLs.

FINDINGS

In 2013 there were 14.9 million incident cancer cases, 8.2 million deaths, and 196.3 million DALYs. Prostate cancer was the leading cause for cancer incidence (1.4 million) for men and breast cancer for women (1.8 million). Tracheal, bronchus, and lung (TBL) cancer was the leading cause for cancer death in men and women, with 1.6 million deaths. For men, TBL cancer was the leading cause of DALYs (24.9 million). For women, breast cancer was the leading cause of DALYs (13.1 million). Age-standardized incidence rates (ASIRs) per 100 000 and age-standardized death rates (ASDRs) per 100 000 for both sexes in 2013 were higher in developing vs developed countries for stomach cancer (ASIR, 17 vs 14; ASDR, 15 vs 11), liver cancer (ASIR, 15 vs 7; ASDR, 16 vs 7), esophageal cancer (ASIR, 9 vs 4; ASDR, 9 vs 4), cervical cancer (ASIR, 8 vs 5; ASDR, 4 vs 2), lip and oral cavity cancer (ASIR, 7 vs 6; ASDR, 2 vs 2), and nasopharyngeal cancer (ASIR, 1.5 vs 0.4; ASDR, 1.2 vs 0.3). Between 1990 and 2013, ASIRs for all cancers combined (except nonmelanoma skin cancer and Kaposi sarcoma) increased by more than 10% in 113 countries and decreased by more than 10% in 12 of 188 countries.

CONCLUSIONS AND RELEVANCE

Cancer poses a major threat to public health worldwide, and incidence rates have increased in most countries since 1990. The trend is a particular threat to developing nations with health systems that are ill-equipped to deal with complex and expensive cancer treatments. The annual update on the Global Burden of Cancer will provide all stakeholders with timely estimates to guide policy efforts in cancer prevention, screening, treatment, and palliation.

Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013

BACKGROUND

China has experienced a remarkable epidemiological and demographic transition during the past three decades. Far less is known about this transition at the subnational level. Timely and accurate assessment of the provincial burden of disease is needed for evidence-based priority setting at the local level in China.

METHODS

Following the methods of the Global Burden of Disease Study 2013 (GBD 2013), we have systematically analysed all available demographic and epidemiological data sources for China at the provincial level. We developed methods to aggregate county-level surveillance data to inform provincial-level analysis, and we used local data to develop specific garbage code redistribution procedures for China. We assessed levels of and trends in all-cause mortality, causes of death, and years of life lost (YLL) in all 33 province-level administrative units in mainland China, all of which we refer to as provinces, for the years between 1990 and 2013.

FINDINGS

All provinces in mainland China have made substantial strides to improve life expectancy at birth between 1990 and 2013. Increases ranged from 4.0 years in Hebei province to 14.2 years in Tibet. Improvements in female life expectancy exceeded those in male life expectancy in all provinces except Shanghai, Macao, and Hong Kong. We saw significant heterogeneity among provinces in life expectancy at birth and probability of death at ages 0-14, 15-49, and 50-74 years. Such heterogeneity is also present in cause of death structures between sexes and provinces. From 1990 to 2013, leading causes of YLLs changed substantially. In 1990, 16 of 33 provinces had lower respiratory infections or preterm birth complications as the leading causes of YLLs. 15 provinces had cerebrovascular disease and two (Hong Kong and Macao) had ischaemic heart disease. By 2013, 27 provinces had cerebrovascular disease as the leading cause, five had ischaemic heart disease, and one had lung cancer (Hong Kong). Road injuries have become a top ten cause of death in all provinces in mainland China. The most common non-communicable diseases, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and cancers (liver, stomach, and lung), contributed much more to YLLs in 2013 compared with 1990.

INTERPRETATION

Rapid transitions are occurring across China, but the leading health problems and the challenges imposed on the health system by epidemiological and demographic change differ between groups of Chinese provinces. Localised health policies need to be implemented to tackle the diverse challenges faced by local health-care systems.

FUNDING

China National Science & Technology Pillar Program 2013 (2013BAI04B02) and Bill & Melinda Gates Foundation.

Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition

BACKGROUND

The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development.

METHODS

We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time.

FINDINGS

Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries.

INTERPRETATION

Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition--in which increasing sociodemographic status brings structured change in disease burden--is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions.

FUNDING

Bill & Melinda Gates Foundation.

Sources and Focus of Health Development Assistance, 1990-2014

IMPORTANCE

The governments of high-income countries and private organizations provide billions of dollars to developing countries for health. This type of development assistance can have a critical role in ensuring that life-saving health interventions reach populations in need.

OBJECTIVES

To identify the amount of development assistance that countries and organizations provided for health and to determine the health areas that received these funds.

EVIDENCE REVIEW

Budget, revenue, and expenditure data on the primary agencies and organizations (n = 38) that provided resources to developing countries (n = 146-183, depending on the year) for health from 1990 through 2014 were collected. For each channel (the international agency or organization that directed the resources toward the implementing institution or government), the source and recipient of the development assistance were determined and redundant accounting of the same dollar, which occurs when channels transfer funds among each other, was removed. This research derived the flow of resources from source to intermediary channel to recipient. Development assistance for health (DAH) was divided into 11 mutually exclusive health focus areas, such that every dollar of development assistance was assigned only 1 health focus area.

FINDINGS

Since 1990, $458.0 billion of development assistance has been provided to maintain or improve health in developing countries. The largest source of funding was the US government, which provided $143.1 billion between 1990 and 2014, including $12.4 billion in 2014. Of resources that originated with the US government, 70.6% were provided through US government agencies, and 41.0% were allocated for human immunodeficiency virus (HIV)/AIDS. The second largest source of development assistance for health was private philanthropic donors, including the Bill and Melinda Gates Foundation and other private foundations, which provided $69.9 billion between 1990 and 2014, including $6.2 billion in 2014. These resources were provided primarily through private foundations and nongovernmental organizations and were allocated for a diverse set of health focus areas. Since 1990, 28.0% of all DAH was allocated for maternal health and newborn and child health; 23.2% for HIV/AIDS, 4.3% for malaria, 2.8% for tuberculosis, and 1.5% for noncommunicable diseases. Between 2000 and 2010, DAH increased 11.3% annually. However, since 2010, total DAH has not increased as substantially.

CONCLUSIONS AND RELEVANCE

Funding for health in developing countries has increased substantially since 1990, with a focus on HIV/AIDS, maternal health, and newborn and child health. Funding from the US government has played a substantial role in this expansion. Funding for noncommunicable diseases has been limited. Understanding how funding patterns have changed across time and the priorities of sources of international funding across distinct channels, recipients, and health focus areas may help identify where funding gaps persist and where cost-effective interventions could save lives.