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1.
Am J Respir Crit Care Med ; 207(2): 183-192, 2023 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-35997678

RESUMEN

Rationale: Respiratory conditions account for a large proportion of health care spending in the United States. A full characterization of spending across multiple conditions and over time has not been performed. Objectives: To estimate health care spending in the United States for 11 respiratory conditions from 1996 to 2016, providing detailed trends and an evaluation of factors associated with spending growth. Methods: We extracted data from the Institute of Health Metrics and Evaluation's Disease Expenditure Project Database, producing annual estimates in spending for 38 age and sex groups, 7 types of care, and 3 payer types. We performed a decomposition analysis to estimate the change in spending associated with changes in each of five factors (population growth, population aging, disease prevalence, service usage, and service price and intensity). Measurements and Main Results: Total spending across all respiratory conditions in 2016 was $170.8 billion (95% confidence interval [CI], $164.2-179.2 billion), increasing by $71.7 billion (95% CI, $63.2-80.8 billion) from 1996. The respiratory conditions with the highest spending in 2016 were asthma and chronic obstructive pulmonary disease, contributing $35.5 billion (95% CI, $32.4-38.2 billion) and $34.3 billion (95% CI, $31.5-37.3 billion), respectively. Increasing service price and intensity were associated with 81.4% (95% CI, 70.3-93.0%) growth from 1996 to 2016. Conclusions: U.S. spending on respiratory conditions is high, particularly for chronic conditions like asthma and chronic obstructive pulmonary disease. Our findings suggest that service price and intensity, particularly for pharmaceuticals, should be a key focus of attention for policymakers seeking to reduce health care spending growth.


Asunto(s)
Asma , Enfermedad Pulmonar Obstructiva Crónica , Trastornos Respiratorios , Enfermedades Respiratorias , Humanos , Estados Unidos/epidemiología , Gastos en Salud , Atención a la Salud , Trastornos Respiratorios/epidemiología , Trastornos Respiratorios/terapia , Enfermedades Respiratorias/epidemiología , Enfermedades Respiratorias/terapia , Asma/epidemiología , Asma/terapia
2.
Alzheimers Dement ; 20(4): 2742-2751, 2024 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-38411287

RESUMEN

INTRODUCTION: Dementia is the fourth largest cause of death for individuals 70 years of age and older in the United States, and it is tremendously costly. Existing estimates of the indirect costs of dementia are dated and do not report on differences across the United States. METHODS: We used data from multiple surveys to create cost estimates and projections for informal dementia caregiving at the U.S. state level from 2010 through 2050. RESULTS: In 2019, the annual replacement cost of informal caregiving was $42,422 per prevalent case, and the forgone wage cost was $10,677 per prevalent case. In 2019, it would have cost $230 billion to hire home health aides to provide all this care. If past trends persist, this cost is expected to grow to $404 billion per year in 2050. DISCUSSION: The cost of informal care varied substantially by state and is expected to grow through at least 2050. HIGHLIGHTS: In the United States in 2019, foregone wages due to informal dementia care was $58 billion. Replacing informal dementia care with health aides would have cost $230 billion. These costs vary dramatically by state, even when assessed per prevalent case. These costs are expected to nearly double by 2050.


Asunto(s)
Cuidadores , Demencia , Humanos , Estados Unidos , Costos de la Atención en Salud , Costo de Enfermedad , Predicción
3.
PLoS Med ; 20(4): e1004205, 2023 04.
Artículo en Inglés | MEDLINE | ID: mdl-37014826

RESUMEN

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.


Asunto(s)
Isquemia Miocárdica , Neoplasias , Insuficiencia Renal Crónica , Humanos , Adulto , Estados Unidos/epidemiología , Adolescente , Adulto Joven , Persona de Mediana Edad , Multimorbilidad , Enfermedad Crónica , Prevalencia
4.
BMC Med ; 21(1): 201, 2023 06 06.
Artículo en Inglés | MEDLINE | ID: mdl-37277874

RESUMEN

BACKGROUND: Norway is a high-income nation with universal tax-financed health care and among the highest per person health spending in the world. This study estimates Norwegian health expenditures by health condition, age, and sex, and compares it with disability-adjusted life-years (DALYs). METHODS: Government budgets, reimbursement databases, patient registries, and prescription databases were combined to estimate spending for 144 health conditions, 38 age and sex groups, and eight types of care (GPs; physiotherapists & chiropractors; specialized outpatient; day patient; inpatient; prescription drugs; home-based care; and nursing homes) totaling 174,157,766 encounters. Diagnoses were in accordance with the Global Burden of Disease study (GBD). The spending estimates were adjusted, by redistributing excess spending associated with each comorbidity. Disease-specific DALYs were gathered from GBD 2019. RESULTS: The top five aggregate causes of Norwegian health spending in 2019 were mental and substance use disorders (20.7%), neurological disorders (15.4%), cardiovascular diseases (10.1%), diabetes, kidney, and urinary diseases (9.0%), and neoplasms (7.2%). Spending increased sharply with age. Among 144 health conditions, dementias had the highest health spending, with 10.2% of total spending, and 78% of this spending was incurred at nursing homes. The second largest was falls estimated at 4.6% of total spending. Spending in those aged 15-49 was dominated by mental and substance use disorders, with 46.0% of total spending. Accounting for longevity, spending per female was greater than spending per male, particularly for musculoskeletal disorders, dementias, and falls. Spending correlated well with DALYs (Correlation r = 0.77, 95% CI 0.67-0.87), and the correlation of spending with non-fatal disease burden (r = 0.83, 0.76-0.90) was more pronounced than with mortality (r = 0.58, 0.43-0.72). CONCLUSIONS: Health spending was high for long-term disabilities in older age groups. Research and development into more effective interventions for the disabling high-cost diseases is urgently needed.


Asunto(s)
Demencia , Personas con Discapacidad , Trastornos Relacionados con Sustancias , Humanos , Masculino , Femenino , Anciano , Años de Vida Ajustados por Calidad de Vida , Sistema de Registros , Salud Global
5.
Scand J Public Health ; : 14034948231188237, 2023 Jul 28.
Artículo en Inglés | MEDLINE | ID: mdl-37501582

RESUMEN

AIM: The inclusion of production losses in health care priority setting is extensively debated. However, few studies allow for a comparison of these losses across relevant clinical and demographic categories. Our objective was to provide comprehensive estimates of Norwegian production losses from morbidity and mortality by age, sex and disease category. METHODS: National registries, tax records, labour force surveys, household and population statistics and data from the Global Burden of Disease were combined to estimate production losses for 12 disease categories, 38 age and sex groups and four causes of production loss. The production losses were estimated via lost wages in accordance with a human capital approach for 2019. RESULTS: The main causes of production losses in 2019 were mental and substance use disorders, totalling NOK121.6bn (32.7% of total production losses). This was followed by musculoskeletal disorders, neurological disorders, injuries, and neoplasms, which accounted for 25.2%, 7.4%, 7.4% and 6.5% of total production losses, respectively. Production losses due to sick leave, disability insurance and work assessment allowance were higher for females than for males, whereas production losses due to premature mortality were higher for males. The latter was related to neoplasms, cardiovascular disease and injuries. Across age categories, non-fatal conditions with a high prevalence among working populations caused the largest production losses. CONCLUSIONS: The inclusion of production losses in health care priority debates in Norway could result in an emphasis on chronic diseases that occur among younger populations at the expense of fatal diseases among older age groups.

6.
Ann Intern Med ; 175(8): 1057-1064, 2022 08.
Artículo en Inglés | MEDLINE | ID: mdl-35759765

RESUMEN

BACKGROUND: Life expectancy (LE) differences within and between states by race/ethnicity have not been examined. OBJECTIVE: To estimate LE for selected race/ethnicity groups in states from 1990 to 2019. DESIGN: Cross-sectional time-series analysis. SETTING: United States. PARTICIPANTS: Deidentified death records and Census data were used to construct regression models with smoothed time series of mortality from 1990 to 2019. MEASUREMENTS: LE at birth, by sex and year, for subgroups of people reporting Hispanic, non-Hispanic Black, or non-Hispanic White race/ethnicity. RESULTS: Disparities in LE across states were 8.0 years for females and 12.2 years for males in 1990 and 7.9 years for females and 7.8 years for males in 2019. When race/ethnicity groups were accounted for, disparities across states were 20.7 years for females and 24.5 years for males in 1990, decreasing to 18.5 years for females and 23.7 years for males in 2019. Disparities across states increased within each race/ethnicity group between 1990 and 2019, with the largest increase for non-Hispanic White males and the smallest for Hispanic females. The disparity between race/ethnicity groups within states decreased for most of the 23 states with estimates for all 3 groups but increased for females in 7 states and males in 5 states. LIMITATION: Because of small sample size, LE was not estimated for 37 of 153 state-race/ethnicity groups. CONCLUSION: Disparity in LE across states was greater when race/ethnicity groups were considered. Disparities across all state-race/ethnicity groups in general have decreased over the past 3 decades. Within each race/ethnicity group, disparities across states have increased. Although racial/ethnic disparities decreased in most of the 23 states for which LE was estimated for all 3 groups, they increased for females in 7 states and males in 5 states. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute.


Asunto(s)
Negro o Afroamericano , Etnicidad , Estudios Transversales , Femenino , Hispánicos o Latinos , Humanos , Recién Nacido , Esperanza de Vida , Masculino , Estados Unidos/epidemiología
7.
Circulation ; 144(4): 271-282, 2021 07 27.
Artículo en Inglés | MEDLINE | ID: mdl-33926203

RESUMEN

BACKGROUND: Spending on cardiovascular disease and cardiovascular risk factors (cardiovascular spending) accounts for a significant portion of overall US health care spending. Our objective was to describe US adult cardiovascular spending patterns in 2016, changes from 1996 to 2016, and factors associated with changes over time. METHODS: We extracted information on adult cardiovascular spending from the Institute for Health Metrics and Evaluation's disease expenditure project, which combines data on insurance claims, emergency department and ambulatory care visits, inpatient and nursing care facility stays, and drug prescriptions to estimate >85% of all US health care spending. Cardiovascular spending (2016 US dollars) was stratified by age, sex, type of care, payer, and cardiovascular cause. Time trend and decomposition analyses quantified contributions of epidemiology, service price and intensity (spending per unit of utilization, eg, spending per inpatient bed-day), and population growth and aging to the increase in cardiovascular spending from 1996 to 2016. RESULTS: Adult cardiovascular spending increased from $212 billion in 1996 to $320 billion in 2016, a period when the US population increased by >52 million people, and median age increased from 33.2 to 36.9 years. Over this period, public insurance was responsible for the majority of cardiovascular spending (54%), followed by private insurance (37%) and out-of-pocket spending (9%). Health services for ischemic heart disease ($80 billion) and hypertension ($71 billion) led to the most spending in 2016. Increased spending between 1996 and 2016 was primarily driven by treatment of hypertension, hyperlipidemia, and atrial fibrillation/flutter, for which spending rose by $42 billion, $18 billion, and $16 billion, respectively. Increasing service price and intensity alone were associated with a 51%, or $88 billion, cardiovascular spending increase from 1996 to 2016, whereas changes in disease prevalence were associated with a 37%, or $36 billion, spending reduction over the same period, after taking into account population growth and population aging. CONCLUSIONS: US adult cardiovascular spending increased by >$100 billion from 1996 to 2016. Policies tailored to control service price and intensity and preferentially reimburse higher quality care could help counteract future spending increases caused by population aging and growth.


Asunto(s)
Enfermedades Cardiovasculares/epidemiología , Costos de la Atención en Salud/estadística & datos numéricos , Atención Ambulatoria/economía , Enfermedades Cardiovasculares/etiología , Enfermedades Cardiovasculares/historia , Costos de los Medicamentos , Análisis Factorial , Gastos en Salud , Factores de Riesgo de Enfermedad Cardiaca , Historia del Siglo XX , Historia del Siglo XXI , Humanos , Seguro de Salud/economía , Vigilancia en Salud Pública , Estados Unidos/epidemiología
8.
Lancet ; 398(10314): 1875-1893, 2021 11 20.
Artículo en Inglés | MEDLINE | ID: mdl-34742369

RESUMEN

BACKGROUND: Childhood immunisation is one of the most cost-effective health interventions. However, despite its known value, global access to vaccines remains far from complete. Although supply-side constraints lead to inadequate vaccine coverage in many health systems, there is no comprehensive analysis of the funding for immunisation. We aimed to fill this gap by generating estimates of funding for immunisation disaggregated by the source of funding and the type of activities in order to highlight the funding landscape for immunisation and inform policy making. METHODS: For this financial modelling study, we estimated annual spending on immunisations for 135 low-income and middle-income countries (as determined by the World Bank) from 2000 to 2017, with a focus on government, donor, and out-of-pocket spending, and disaggregated spending for vaccines and delivery costs, and routine schedules and supplementary campaigns. To generate these estimates, we extracted data from National Health Accounts, the WHO-UNICEF Joint Reporting Forms, comprehensive multi-year plans, databases from Gavi, the Vaccine Alliance, and the Institute for Health Metrics and Evaluation's 2019 development assistance for health database. We estimated total spending on immunisation by aggregating the government, donor, prepaid private, and household spending estimates. FINDINGS: Between 2000 and 2017, funding for immunisation totalled US$112·4 billion (95% uncertainty interval 108·5-118·5). Aggregated across all low-income and middle-income countries, government spending consistently remained the largest source of funding, providing between 60·0% (57·7-61·9) and 79·3% (73·8-81·4) of total immunisation spending each year (corresponding to between $2·5 billion [2·3-2·8] and $6·4 billion [6·0-7·0] each year). Across income groups, immunisation spending per surviving infant was similar in low-income and lower-middle-income countries and territories, with average spending of $40 (38-42) in low-income countries and $42 (39-46) in lower-middle-income countries, in 2017. In low-income countries and territories, development assistance made up the largest share of total immunisation spending (69·4% [64·6-72·0]; $630·2 million) in 2017. Across the 135 countries, we observed higher vaccine coverage and increased government spending on immunisation over time, although in some countries, predominantly in Latin America and the Caribbean and in sub-Saharan Africa, vaccine coverage decreased over time, while spending increased. INTERPRETATION: These estimates highlight the progress over the past two decades in increasing spending on immunisation. However, many challenges still remain and will require dedication and commitment to ensure that the progress made in the previous decade is sustained and advanced in the next decade for the Immunization Agenda 2030. FUNDING: Bill & Melinda Gates Foundation.


Asunto(s)
Países en Desarrollo/economía , Inmunización/economía , Niño , Preescolar , Países en Desarrollo/estadística & datos numéricos , Financiación Gubernamental/economía , Gastos en Salud , Financiación de la Atención de la Salud , Humanos , Inmunización/estadística & datos numéricos , Programas de Inmunización/economía , Lactante , Agencias Internacionales/economía , Vacunas/economía
9.
Hum Resour Health ; 20(1): 51, 2022 06 10.
Artículo en Inglés | MEDLINE | ID: mdl-35689228

RESUMEN

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 $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.


Asunto(s)
COVID-19 , Pandemias , COVID-19/epidemiología , Países en Desarrollo , Salud Global , Recursos en Salud , Humanos , Desarrollo Sostenible , Recursos Humanos
10.
JAMA ; 326(7): 649-659, 2021 08 17.
Artículo en Inglés | MEDLINE | ID: mdl-34402829

RESUMEN

Importance: Measuring health care spending by race and ethnicity is important for understanding patterns in utilization and treatment. Objective: To estimate, identify, and account for differences in health care spending by race and ethnicity from 2002 through 2016 in the US. Design, Setting, and Participants: This exploratory study included data from 7.3 million health system visits, admissions, or prescriptions captured in the Medical Expenditure Panel Survey (2002-2016) and the Medicare Current Beneficiary Survey (2002-2012), which were combined with the insured population and notified case estimates from the National Health Interview Survey (2002; 2016) and health care spending estimates from the Disease Expenditure project (1996-2016). Exposure: Six mutually exclusive self-reported race and ethnicity groups. Main Outcomes and Measures: Total and age-standardized health care spending per person by race and ethnicity for each year from 2002 through 2016 by type of care. Health care spending per notified case by race and ethnicity for key diseases in 2016. Differences in health care spending across race and ethnicity groups were decomposed into differences in utilization rate vs differences in price and intensity of care. Results: In 2016, an estimated $2.4 trillion (95% uncertainty interval [UI], $2.4 trillion-$2.4 trillion) was spent on health care across the 6 types of care included in this study. The estimated age-standardized total health care spending per person in 2016 was $7649 (95% UI, $6129-$8814) for American Indian and Alaska Native (non-Hispanic) individuals; $4692 (95% UI, $4068-$5202) for Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals; $7361 (95% UI, $6917-$7797) for Black (non-Hispanic) individuals; $6025 (95% UI, $5703-$6373) for Hispanic individuals; $9276 (95% UI, $8066-$10 601) for individuals categorized as multiple races (non-Hispanic); and $8141 (95% UI, $8038-$8258) for White (non-Hispanic) individuals, who accounted for an estimated 72% (95% UI, 71%-73%) of health care spending. After adjusting for population size and age, White individuals received an estimated 15% (95% UI, 13%-17%; P < .001) more spending on ambulatory care than the all-population mean. Black (non-Hispanic) individuals received an estimated 26% (95% UI, 19%-32%; P < .001) less spending than the all-population mean on ambulatory care but received 19% (95% UI, 3%-32%; P = .02) more on inpatient and 12% (95% UI, 4%-24%; P = .04) more on emergency department care. Hispanic individuals received an estimated 33% (95% UI, 26%-37%; P < .001) less spending per person on ambulatory care than the all-population mean. Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals received less spending than the all-population mean on all types of care except dental (all P < .001), while American Indian and Alaska Native (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 90% more; 95% UI, 11%-165%; P = .04), and multiple-race (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 40% more; 95% UI, 19%-63%; P = .006). All 18 of the statistically significant race and ethnicity spending differences by type of care corresponded with differences in utilization. These differences persisted when controlling for underlying disease burden. Conclusions and Relevance: In the US from 2002 through 2016, health care spending varied by race and ethnicity across different types of care even after adjusting for age and health conditions. Further research is needed to determine current health care spending by race and ethnicity, including spending related to the COVID-19 pandemic.


Asunto(s)
Etnicidad/estadística & datos numéricos , Gastos en Salud/estadística & datos numéricos , Disparidades en Atención de Salud/etnología , Grupos Raciales/estadística & datos numéricos , Encuestas de Atención de la Salud , Humanos , Estados Unidos
11.
Lancet ; 393(10181): 1628-1640, 2019 Apr 20.
Artículo en Inglés | MEDLINE | ID: mdl-30878225

RESUMEN

BACKGROUND: Previous analyses of democracy and population health have focused on broad measures, such as life expectancy at birth and child and infant mortality, and have shown some contradictory results. We used a panel of data spanning 170 countries to assess the association between democracy and cause-specific mortality and explore the pathways connecting democratic rule to health gains. METHODS: We extracted cause-specific mortality and HIV-free life expectancy estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 and information on regime type from the Varieties of Democracy project. These data cover 170 countries and 46 years. From the Financing Global Health database, we extracted gross domestic product (GDP) per capita, also covering 46 years, and Development Assistance for Health estimates starting from 1990 and domestic health spending estimates starting from 1995. We used a diverse set of empirical methods-synthetic control, within-country variance decomposition, structural equation models, and fixed-effects regression-which together provide a robust analysis of the association between democratisation and population health. FINDINGS: HIV-free life expectancy at age 15 years improved significantly during the study period (1970-2015) in countries after they transitioned to democracy, on average by 3% after 10 years. Democratic experience explains 22·27% of the variance in mortality within a country from cardiovascular diseases, 16·53% for tuberculosis, and 17·78% for transport injuries, and a smaller percentage for other diseases included in the study. For cardiovascular diseases, transport injuries, cancers, cirrhosis, and other non-communicable diseases, democratic experience explains more of the variation in mortality than GDP. Over the past 20 years, the average country's increase in democratic experience had direct and indirect effects on reducing mortality from cardiovascular disease (-9·64%, 95% CI -6·38 to -12·90), other non-communicable diseases (-9·14%, -4·26 to -14·02), and tuberculosis (-8·93%, -2·08 to -15·77). Increases in a country's democratic experience were not correlated with GDP per capita between 1995 and 2015 (ρ=-0·1036; p=0·1826), but were correlated with declines in mortality from cardiovascular disease (ρ=-0·3873; p<0·0001) and increases in government health spending (ρ=0·4002; p<0·0001). Removal of free and fair elections from the democratic experience variable resulted in loss of association with age-standardised mortality from non-communicable diseases and injuries. INTERPRETATION: When enforced by free and fair elections, democracies are more likely than autocracies to lead to health gains for causes of mortality (eg, cardiovascular diseases and transport injuries) that have not been heavily targeted by foreign aid and require health-care delivery infrastructure. International health agencies and donors might increasingly need to consider the implications of regime type in their efforts to maximise health gains, particularly in the context of ageing populations and the growing burden of non-communicable diseases. FUNDING: Bloomberg Philanthropies and the Bill & Melinda Gates Foundation.


Asunto(s)
Democracia , Salud Global , Estado de Salud , Adulto , Causas de Muerte , Bases de Datos Factuales , Femenino , Carga Global de Enfermedades/economía , Humanos , Masculino
12.
Lancet ; 394(10193): 173-183, 2019 Jul 13.
Artículo en Inglés | MEDLINE | ID: mdl-31257126

RESUMEN

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.


Asunto(s)
Salud Global/economía , Salud Global/tendencias , Política de Salud , Financiación de la Atención de la Salud , Predicción , Gastos en Salud/tendencias , Humanos , Cooperación Internacional
13.
Global Health ; 16(1): 14, 2020 02 04.
Artículo en Inglés | MEDLINE | ID: mdl-32019554

RESUMEN

BACKGROUND: Donor countries in the Middle East and North Africa (MENA) including Saudi Arabia, Kuwait and United Arab Emirates (UAE) have been among the largest donors in the world. However, little is known about their contributions for health. In this study, we addressed this gap by estimating the amount of development assistance for health (DAH) contributed by MENA country donors from 2000 to 2017. METHODS: We tracked DAH provided and received by the MENA region leveraging publicly available development assistance data in the Development Assistance Committee (DAC) database of the Organisation for Economic Co-operation and Development (OECD), government agency reports and financial statements from key international development agencies. We generated estimates of DAH provided by the three largest donor countries in the MENA region (UAE, Kuwait, Saudi Arabia) and compared contributions to their relative gross domestic product (GDP) and government spending; We captured DAH contributions by other MENA country governments (Egypt, Iran, Qatar, Turkey, etc.) disbursed through multilateral agencies. Additionally, we compared DAH contributed from and provided to the MENA region. RESULTS: In 2017, DAH contributed by the MENA region reached $514.8 million. While UAE ($220.1 million, 43.2%), Saudi Arabia ($177.3 million, 34.8%) and Kuwait ($59.8 million, 11.6%) as sources contributed the majority of DAH in 2017, 58.5% of total DAH from MENA was disbursed through their bilateral agencies, 12.0% through the World Health Organization (WHO) and 3.3% through other United Nations agencies. 44.8% of DAH contributions from MENA was directed to health system strengthening/sector-wide approaches. Relative to their GDP and government spending, DAH level fluctuated across 2000 to 2017 but UAE and Saudi Arabia indicated increasing trends. While considering all MENA countries as recipients, only 10.5% of DAH received by MENA countries were from MENA donors in 2017. CONCLUSION: MENA country donors especially UAE, Saudi Arabia and Kuwait have been providing substantial amount of DAH, channeled through their bilateral agencies, WHO and other multilateral agencies, with a prioritized focus on health system strengthening. DAH from the MENA region has been increasing for the past decade and could lend itself to important contributions for the region and the globe.


Asunto(s)
Salud Global/economía , Cooperación Internacional , África del Norte , Humanos , Medio Oriente
14.
JAMA ; 323(9): 863-884, 2020 03 03.
Artículo en Inglés | MEDLINE | ID: mdl-32125402

RESUMEN

Importance: US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how these amounts have changed over time. Objective: To estimate US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. Design and Setting: Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. Exposures: Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. Main Outcomes and Measures: National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. Results: Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product [GDP]; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending (estimated at $129.8 billion [95% CI, $116.3-$149.7 billion]) and most had private insurance (56.4% [95% CI, 52.6%-59.3%]). Diabetes accounted for the third highest amount of the health care spending (estimated at $111.2 billion [95% CI, $105.7-$115.9 billion]) and most had public insurance (49.8% [95% CI, 44.4%-56.0%]). Other conditions estimated to have substantial health care spending in 2016 were ischemic heart disease ($89.3 billion [95% CI, $81.1-$95.5 billion]), falls ($87.4 billion [95% CI, $75.0-$100.1 billion]), urinary diseases ($86.0 billion [95% CI, $76.3-$95.9 billion]), skin and subcutaneous diseases ($85.0 billion [95% CI, $80.5-$90.2 billion]), osteoarthritis ($80.0 billion [95% CI, $72.2-$86.1 billion]), dementias ($79.2 billion [95% CI, $67.6-$90.8 billion]), and hypertension ($79.0 billion [95% CI, $72.6-$86.8 billion]). The conditions with the highest spending varied by type of payer, age, sex, type of care, and year. After adjusting for changes in inflation, population size, and age groups, public insurance spending was estimated to have increased at an annualized rate of 2.9% (95% CI, 2.9%-2.9%); private insurance, 2.6% (95% CI, 2.6%-2.6%); and out-of-pocket payments, 1.1% (95% CI, 1.0%-1.1%). Conclusions and Relevance: Estimates of US spending on health care showed substantial increases from 1996 through 2016, with the highest increases in population-adjusted spending by public insurance. Although spending on low back and neck pain, other musculoskeletal disorders, and diabetes accounted for the highest amounts of spending, the payers and the rates of change in annual spending growth rates varied considerably.


Asunto(s)
Enfermedad/economía , Gastos en Salud/tendencias , Seguro de Salud/economía , Adolescente , Adulto , Distribución por Edad , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Femenino , Gastos en Salud/estadística & datos numéricos , Estado de Salud , Humanos , Lactante , Seguro de Salud/tendencias , Masculino , Persona de Mediana Edad , Distribución por Sexo , Estados Unidos , Adulto Joven
15.
16.
Global Health ; 14(1): 98, 2018 10 17.
Artículo en Inglés | MEDLINE | ID: mdl-30333038

RESUMEN

BACKGROUND: Skilled health professionals are a critical component of the effective delivery of lifesaving health interventions. The inadequate number of skilled health professionals in many low- and middle-income countries has been identified as a constraint to the achievement of improvements in health outcomes. In response, more international development agencies have provided funds toward broader health system initiatives and health workforce activities in particular. Nonetheless, estimates of the amount of donor funding targeting investments in human resources for health activities are few. METHODS: We utilize data from the Institute for Health Metrics and Evaluation's annual database on development assistance for health. The estimates in the database are generated using data from publicly available databases that track development assistance. To estimate development assistance for human resources for health, we use keywords to identify projects targeted toward human resource processes. We track development for human resources for health from 1990 through 2016. We categorize the types of human-resources-related projects funded and examine the availability of human resources, development assistance for human resources for health, and disease burden. RESULTS: We find that the amount of donor funding directed toward human resources for health has increased from only $34 million in 1990 to $1.5 billion in 2016 (in 2017 US dollars). Overall, $18.5 billion in 2017 US dollars was targeted toward human resources for health between 1990 and 2016. The primary regions receiving these resources were sub-Saharan Africa and Southeast Asia, East Asia, and Oceania. The main donor countries were the United States, Canada, Australia and the United Kingdom. The main agencies through which these resources were disbursed are non-governmental organizations (NGOs), US bilateral agencies, and UN agencies. CONCLUSION: In 2016, less than 4% of development assistance for health could be tied to funding for human resources. Given the central role skilled health workers play in health systems, in order to make credible progress in reducing disparities in health and attaining the goal of universal health coverage for all by 2030, it may be appropriate for more resources to be mobilized in order to guarantee adequate manpower to deliver key health interventions.


Asunto(s)
Fuerza Laboral en Salud/economía , Cooperación Internacional , África del Sur del Sahara , Asia Sudoriental , Australia , Canadá , Bases de Datos Factuales , Asia Oriental , Humanos , Oceanía , Reino Unido , Estados Unidos
17.
Lancet ; 387(10037): 2536-44, 2016 Jun 18.
Artículo en Inglés | MEDLINE | ID: mdl-27086170

RESUMEN

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.


Asunto(s)
Países en Desarrollo/economía , Desarrollo Económico/tendencias , Salud Global/tendencias , Cooperación Internacional , Salud Global/economía , Financiación de la Atención de la Salud , Humanos , Agencias Internacionales/economía , Agencias Internacionales/tendencias
18.
Lancet ; 387(10037): 2521-35, 2016 Jun 18.
Artículo en Inglés | MEDLINE | ID: mdl-27086174

RESUMEN

BACKGROUND: A general consensus exists that as a country develops economically, health spending per capita rises and the share of that spending that is prepaid through government or private mechanisms also rises. However, the speed and magnitude of these changes vary substantially across countries, even at similar levels of development. In this study, we use past trends and relationships to estimate future health spending, disaggregated by the source of those funds, to identify the financing trajectories that are likely to occur if current policies and trajectories evolve as expected. METHODS: We extracted data from WHO's Health Spending Observatory and the Institute for Health Metrics and Evaluation's Financing Global Health 2015 report. We converted these data to a common purchasing power-adjusted and inflation-adjusted currency. We used a series of ensemble models and observed empirical norms to estimate future government out-of-pocket private prepaid health spending and development assistance for health. We aggregated each country's estimates to generate total health spending from 2013 to 2040 for 184 countries. We compared these estimates with each other and internationally recognised benchmarks. FINDINGS: Global spending on health is expected to increase from US$7·83 trillion in 2013 to $18·28 (uncertainty interval 14·42-22·24) trillion in 2040 (in 2010 purchasing power parity-adjusted dollars). We expect per-capita health spending to increase annually by 2·7% (1·9-3·4) in high-income countries, 3·4% (2·4-4·2) in upper-middle-income countries, 3·0% (2·3-3·6) in lower-middle-income countries, and 2·4% (1·6-3·1) in low-income countries. Given the gaps in current health spending, these rates provide no evidence of increasing parity in health spending. In 1995 and 2015, low-income countries spent $0·03 for every dollar spent in high-income countries, even after adjusting for purchasing power, and the same is projected for 2040. Most importantly, health spending in many low-income countries is expected to remain low. Estimates suggest that, by 2040, only one (3%) of 34 low-income countries and 36 (37%) of 98 middle-income countries will reach the Chatham House goal of 5% of gross domestic product consisting of government health spending. INTERPRETATION: Despite remarkable health gains, past health financing trends and relationships suggest that many low-income and lower-middle-income countries will not meet internationally set health spending targets and that spending gaps between low-income and high-income countries are unlikely to narrow unless substantive policy interventions occur. Although gains in health system efficiency can be used to make progress, current trends suggest that meaningful increases in health system resources will require concerted action. FUNDING: Bill & Melinda Gates Foundation.


Asunto(s)
Salud Global/tendencias , Gastos en Salud/tendencias , Financiación Gubernamental/tendencias , Predicción , Salud Global/economía , Producto Interno Bruto/tendencias , Humanos , Renta
19.
BMC Health Serv Res ; 17(1): 681, 2017 Sep 26.
Artículo en Inglés | MEDLINE | ID: mdl-28950899

RESUMEN

BACKGROUND: Many children in low and middle-income countries remain unvaccinated, and vaccines do not always produce immunity. Extensive research has sought to understand why, but most studies have been limited in breadth and depth. This study documents existing evidence on determinants of vaccination and immunization and presents a conceptual framework of determinants. METHODS: We used systematic review, content analysis, thematic analysis and interpretive synthesis to document and analyze the existing evidence on determinants of childhood vaccination and immunization. RESULTS: We documented 1609 articles, including content analysis of 78 articles. Three major thematic models were described in the context of one another. Interpretive synthesis identified similarities and differences between studies, resulting in a conceptual framework with three principal vaccine utilization determinants: 1) Intent to Vaccinate, 2) Community Access and 3) Health Facility Readiness. CONCLUSION: This study presents the most comprehensive systematic review of vaccine determinants to date. The conceptual framework represents a synthesis of multiple existing frameworks, is applicable in low and middle-income countries, and is quantitatively testable. Future researchers can use these results to develop competing conceptual frameworks, or to analyze data in a theoretically-grounded way. This review enables better research in the future, further understanding of immunization determinants, and greater progress against vaccine preventable diseases around the world.


Asunto(s)
Programas de Inmunización , Vacunación/estadística & datos numéricos , Niño , Países en Desarrollo , Humanos , Aceptación de la Atención de Salud
20.
JAMA ; 318(17): 1668-1678, 2017 11 07.
Artículo en Inglés | MEDLINE | ID: mdl-29114831

RESUMEN

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.


Asunto(s)
Gastos en Salud/tendencias , Servicios de Salud/economía , Dinámica Poblacional , Factores de Edad , Epidemiología , Femenino , Servicios de Salud/estadística & datos numéricos , Humanos , Masculino , Estados Unidos
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