118 research outputs found

    Motivation and incentives of rural maternal and neonatal health care providers: a comparison of qualitative findings from Burkina Faso, Ghana and Tanzania.

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    In Burkina Faso, Ghana and Tanzania strong efforts are being made to improve the quality of maternal and neonatal health (MNH) care. However, progress is impeded by challenges, especially in the area of human resources. All three countries are striving not only to scale up the number of available health staff, but also to improve performance by raising skill levels and enhancing provider motivation. In-depth interviews were used to explore MNH provider views about motivation and incentives at primary care level in rural Burkina Faso, Ghana and Tanzania. Interviews were held with 25 MNH providers, 8 facility and district managers, and 2 policy-makers in each country. Across the three countries some differences were found in the reasons why people became health workers. Commitment to remaining a health worker was generally high. The readiness to remain at a rural facility was far less, although in all settings there were some providers that were willing to stay. In Burkina Faso it appeared to be particularly difficult to recruit female MNH providers to rural areas. There were indications that MNH providers in all the settings sometimes failed to treat their patients well. This was shown to be interlinked with differences in how the term 'motivation' was understood, and in the views held about remuneration and the status of rural health work. Job satisfaction was shown to be quite high, and was particularly linked to community appreciation. With some important exceptions, there was a strong level of agreement regarding the financial and non-financial incentives that were suggested by these providers, but there were clear country preferences as to whether incentives should be for individuals or teams. Understandings of the terms and concepts pertaining to motivation differed between the three countries. The findings from Burkina Faso underline the importance of gender-sensitive health workforce planning. The training that all levels of MNH providers receive in professional ethics, and the way this is reinforced in practice require closer attention. The differences in the findings across the three settings underscore the importance of in-depth country-level research to tailor the development of incentives schemes

    Specialist training in Fiji: Why do graduates migrate, and why do they remain? A qualitative study

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    <p>Abstract</p> <p>Background</p> <p>Specialist training was established in the late 1990s at the Fiji School of Medicine. Losses of graduates to overseas migration and to the local private sector prompted us to explore the reasons for these losses from the Fiji public workforce.</p> <p>Methods</p> <p>Data were collected on the whereabouts and highest educational attainments of the 66 Fiji doctors who had undertaken specialist training to at least the diploma level between 1997 and 2004. Semistructured interviews focusing on career decisions were carried out with 36 of these doctors, who were purposively sampled to include overseas migrants, temporary overseas trainees, local private practitioners and public sector doctors.</p> <p>Results</p> <p>120 doctors undertook specialist training to at least the diploma level between 1997 and 2004; 66 of the graduates were Fiji citizens or permanent residents; 54 originated from other countries in the region. Among Fiji graduates, 42 completed a diploma and 24 had either completed (21) or were enrolled (3) in a master's programme. Thirty-two (48.5%) were working in the public sectors, four (6.0%) were temporarily training overseas, 30.3% had migrated overseas and the remainder were mostly in local private practice. Indo-Fijian ethnicity and non-completion of full specialist training were associated with lower retention in the public sectors, while gender had little impact. Decisions to leave the public sectors were complex, with concerns about political instability and family welfare predominating for overseas migrants, while working conditions not conducive to family life or frustrations with career progression predominated for local private practitioners. Doctors remaining in the public sectors reported many satisfying aspects to their work despite frustrations, though 40% had seriously considered resigning from the public service and 60% were unhappy with their career progression.</p> <p>Conclusion</p> <p>Overall, this study provides some support for the view that local or regional postgraduate training may increase retention of doctors. Attention to career pathways and other sources of frustration, in addition to encouragement to complete training, should increase the likelihood of such programmes' reaching their full potentials.</p

    End of life care in sub-Saharan Africa: a systematic review of the qualitative literature

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    <p>Abstract</p> <p>Background</p> <p>End of life (EoL) care in sub-Saharan Africa still lacks the sound evidence-base needed for the development of effective, appropriate service provision. It is essential to make evidence from all types of research available alongside clinical and health service data, to ensure that EoL care is ethical and culturally appropriate. This article aims to synthesize qualitative research on EoL care in sub-Saharan Africa to inform policy, practice and further research. It seeks to identify areas of existing research; describe findings specifically relevant to the African context; and, identify areas lacking evidence.</p> <p>Methods</p> <p>Relevant literature was identified through eight electronic databases: AMED, British Nursing Index & Archive, CINAHL, EMBASE, IBSS, MEDLINE, PsycINFO, and the Social Sciences Citation Index; and hand searches. Inclusion criteria were: published qualitative or mixed-method studies in sub-Saharan Africa, about EoL care. Study quality was assessed using a standard grading scale. Relevant data including findings and practice recommendations were extracted and compared in tabular format.</p> <p>Results</p> <p>Of the 407 articles initially identified, 51 were included in the qualitative synthesis. Nineteen came from South Africa and the majority (38) focused on HIV/AIDS. Nine dealt with multiple or unspecified conditions and four were about cancer. Study respondents included health professionals, informal carers, patients, community members and bereaved relatives. Informal carers were typically women, the elderly and children, providing total care in the home, and lacking support from professionals or the extended family. Twenty studies focused on home-based care, describing how programmes function in practice and what is needed to make them effective. Patients and carers were reported to prefer institutional care but this needs to be understood in context. Studies focusing on culture discussed good and bad death, culture-specific approaches to symptoms and illness, and the bereavement process.</p> <p>Conclusions</p> <p>The data support or complement the findings from quantitative research. The review prompts a reconsideration of the assumption that in Africa the extended family care for the sick, and that people prefer home-based care. The review identifies areas relevant for a research agenda on socio-cultural issues at the EoL in sub-Saharan Africa.</p

    A computerised decision support system for cardiovascular risk management ‘live’ in the electronic health record environment: development, validation and implementation—the Utrecht Cardiovascular Cohort Initiative

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    PURPOSE: We set out to develop a real-time computerised decision support system (CDSS) embedded in the electronic health record (EHR) with information on risk factors, estimated risk, and guideline-based advice on treatment strategy in order to improve adherence to cardiovascular risk management (CVRM) guidelines with the ultimate aim of improving patient healthcare. METHODS: We defined a project plan including the scope and requirements, infrastructure and interface, data quality and study population, validation and evaluation of the CDSS. RESULTS: In collaboration with clinicians, data scientists, epidemiologists, ICT architects, and user experience and interface designers we developed a CDSS that provides ‘live’ information on CVRM within the environment of the EHR. The CDSS provides information on cardiovascular risk factors (age, sex, medical and family history, smoking, blood pressure, lipids, kidney function, and glucose intolerance measurements), estimated 10-year cardiovascular risk, guideline-compliant suggestions for both pharmacological and non-pharmacological treatment to optimise risk factors, and an estimate on the change in 10-year risk of cardiovascular disease if treatment goals are adhered to. Our pilot study identified a number of issues that needed to be addressed, such as missing data, rules and regulations, privacy, and patient participation. CONCLUSION: Development of a CDSS is complex and requires a multidisciplinary approach. We identified opportunities and challenges in our project developing a CDSS aimed at improving adherence to CVRM guidelines. The regulatory environment, including guidance on scientific evaluation, legislation, and privacy issues needs to evolve within this emerging field of eHealth

    Developing a tool to assess motivation among health service providers working with public health system in India

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    BACKGROUND: Addressing the shortage of health service providers (doctors and nurses) in rural health centres remains a huge challenge. The lack of motivation of health service providers to serve in rural areas is one of the major reasons for such shortage. While many studies have aimed at analysing the reasons for low motivation, hardly any studies in India have focused on developing valid and reliable tools to measure motivation among health service providers. Hence, the objective of the study was to test and develop a valid and reliable instrument to assess the motivation of health service providers working with the public health system in India and the extent to which the motivation factors included in the study motivate health service providers to perform better at work. METHODS: The present study adapted an already developed tool on motivation. The reliability and validity of the tool were established using different methods. The first stage of the tool development involved content development and assessment where, after a detailed literature review, a predeveloped tool with 19 items was adapted. However, in light of the literature review and pilot test, the same tool was modified to suit the local context by adding 7 additional items so that the final modified tool comprised of 26 items. A correlation matrix was applied to check the pattern of relationships among the items. The total sample size for the study was 154 health service providers from one Western state in India. To understand the sampling adequacy, the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity were applied and finally factor analysis was carried out to calculate the eigenvalues and to understand the relative impact of factors affecting motivation. RESULTS: A correlation matrix value of 0.017 was obtained narrating multi-co-linearity among the observations. Based on initial factor analysis, 8 out of 26 study factors were excluded from the study components with a cutoff range of less than 0.6. Running the factor analysis again suggested the inclusion of 18 items which were subsequently labelled under the following heads: transparency, goals, security, convenience, benefits, encouragement, adequacy of earnings and further growth and power. CONCLUSIONS: There is a great need to develop instruments aimed at assessing the motivation of health service providers. The instrument used in the study has good psychometric properties and may serve as a useful tool to assess motivation among healthcare providers

    Bright light therapy in pregnant women with major depressive disorder: Study protocol for a randomized, double-blind, controlled clinical trial

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    Background: Depression during pregnancy is a common and high impact disease. Generally, 5-10 % of pregnant women suffer from depression. Children who have been exposed to maternal depression during pregnancy have a higher risk of adverse birth outcomes and more often show cognitive, emotional and behavioural problems. Therefore, early detection and treatment of antepartum depression is necessary. Both psychotherapy and antidepressant medication, first choice treatments in a non-pregnant population, have limitations in treating depression during pregnancy. Therefore, it is urgent and relevant to investigate alternative treatments for antepartum depression. Bright light therapy (BLT) is a promising treatment for pregnant women with depressive disorder, for it combines direct availability, sufficient efficacy, low costs and high safety, taking the safety for the unborn child into account as well. Methods: In this study, 150 pregnant women (12-18 weeks pregnant) with a DSM-V diagnosis of depressive disorder will be randomly allocated in a 1:1 ratio to one of the two treatment arms: treatment with BLT (9.000 lux) or treatment with dim red light therapy (100 lux). Both groups will be treated for 6 weeks at home on a daily basis for 30 min, within 30 min of habitual wake-up time. Follow-up will take place after 6 weeks of therapy, 3 and 10 weeks after end of therapy, at birth and 2, 6 and 18 months postpartum. Primary outcome will be the average change in depressive symptoms between the two groups, as measured by the Structured Interview Guide for the Hamilton Depression Scale - Seasonal Affective Disorder version and the Edinburg Postnatal Depression Scale. Changes in rating scale scores of these questionnaires over time will be analysed using generalized linear mixed models. Secondary outcomes will be the changes in maternal cortisol and melatonin levels, in maternal sleep quality and gestational age, birth weight, infant behaviour, infant cortisol exposure and infant cortisol stress response. Discussion: If BLT reduces depressive symptoms in pregnant women, it will provide a safe, cheap, non-pharmacological and efficacious alternative treatment for psychotherapy and antidepressant medication in treating antepartum depression, without any expected adverse reactions for the unborn child. Trial registration: Netherlands Trial Register NTR5476. Registered 5 November 2015

    Evolution and patterns of global health financing 1995-2014 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

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    Background An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends. Methods We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development. Findings Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted 5221percapitabasedonanannualgrowthrateof3.05221 per capita based on an annual growth rate of 3.0%. The largest health spending growth rates were in upper-middle-income (5.9) and lower-middle-income groups (5.0), which both increased spending at more than 5% per year, and spent 914 and 267percapitain2014,respectively.Spendinginlowincomecountriesgrewnearlyasfast,at4.6267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4.6%, and health spending increased from 51 to 120percapita.In2014,59.2120 per capita. In 2014, 59.2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29.1% and 58.0% of spending was OOP spending and 35.7% and 3.0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1.8%, and reached US37.6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount. Interpretation Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.Peer reviewe

    Past, present, and future of global health financing : a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995-2050

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    Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4.00% (95% uncertainty interval 3.89-4.12) annually, although it grew slower in per capita terms (2.72% [2.61-2.84]) and increased by less than 1percapitaoverthisperiodin22of195countries.Thehighestannualgrowthratesinpercapitahealthspendingwereobservedinuppermiddleincomecountries(5.55 1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5.55% [5.18-5.95]), mainly due to growth in government health spending, and in lower-middle-income countries (3.71% [3.10-4.34]), mainly from DAH. Health spending globally reached 8.0 trillion (7.8-8.1) in 2016 (comprising 8.6% [8.4-8.7] of the global economy and 10.3trillion[10.110.6]inpurchasingpowerparityadjusteddollars),withapercapitaspendingofUS 10.3 trillion [10.1-10.6] in purchasing-power parity-adjusted dollars), with a per capita spending of US 5252 (5184-5319) in high-income countries, 491(461524)inuppermiddleincomecountries, 491 (461-524) in upper-middle-income countries, 81 (74-89) in lower-middle-income countries, and 40(3843)inlowincomecountries.In2016,0.4 40 (38-43) in low-income countries. In 2016, 0.4% (0.3-0.4) of health spending globally was in low-income countries, despite these countries comprising 10.0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ( 9.5 billion, 24.3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6.27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH (644.7millionin2018).Globally,healthspendingisprojectedtoincreaseto 644.7 million in 2018). Globally, health spending is projected to increase to 15.0 trillion (14.0-16.0) by 2050 (reaching 9.4% [7.6-11.3] of the global economy and $ 21.3 trillion [19.8-23.1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1.84% (1.68-2.02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0.6% (0.6-0.7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15.7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130.2 (122.9-136.9) in 2016 and is projected to remain at similar levels in 2050 (125.9 [113.7-138.1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.Peer reviewe

    Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995–2050

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    Background: Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories—government, out-of-pocket, and prepaid private health spending—and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89–4·12) annually, although it grew slower in per capita terms (2·72% [2·61–2·84]) and increased by less than 1percapitaoverthisperiodin22of195countries.Thehighestannualgrowthratesinpercapitahealthspendingwereobservedinuppermiddleincomecountries(555inlowermiddleincomecountries(3711 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55% [5·18–5·95]), mainly due to growth in government health spending, and in lower-middle-income countries (3·71% [3·10–4·34]), mainly from DAH. Health spending globally reached 8·0 trillion (7·8–8·1) in 2016 (comprising 8·6% [8·4–8·7] of the global economy and 103trillion[101106]inpurchasingpowerparityadjusteddollars),withapercapitaspendingofUS10·3 trillion [10·1–10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US5252 (5184–5319) in high-income countries, 491(461524)inuppermiddleincomecountries,491 (461–524) in upper-middle-income countries, 81 (74–89) in lower-middle-income countries, and 40(3843)inlowincomecountries.In2016,04countries,despitethesecountriescomprising100DAHtargetedHIV/AIDS(40 (38–43) in low-income countries. In 2016, 0·4% (0·3–0·4) of health spending globally was in low-income countries, despite these countries comprising 10·0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS (9·5 billion, 24·3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China’s contribution to DAH (6447millionin2018).Globally,healthspendingisprojectedtoincreaseto644·7 million in 2018). Globally, health spending is projected to increase to 15·0 trillion (14·0–16·0) by 2050 (reaching 9·4% [7·6–11·3] of the global economy and $21·3 trillion [19·8–23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1·84% (1·68–2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0·6% (0·6–0·7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130·2 (122·9–136·9) in 2016 and is projected to remain at similar levels in 2050 (125·9 [113·7–138·1]). The decomposition analysis identified governments’ increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending Interpretation: Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets. Funding: Bill & Melinda Gates Foundatio

    Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3

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    Background: Sustainable Development Goal (SDG) 3 aims to “ensure healthy lives and promote well-being for all at all ages”. While a substantial effort has been made to quantify progress towards SDG3, less research has focused on tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas of SDG3, examine the association between outcomes and financing, and identify where resource gains are most needed to achieve the SDG3 indicators for which data are available. Methods: We estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in 106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from 1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until 2030. We report all spending estimates in inflation-adjusted 2019 US,unlessotherwisestated.Findings:SincethedevelopmentandimplementationoftheSDGsin2015,globalhealthspendinghasincreased,reaching, unless otherwise stated. Findings: Since the development and implementation of the SDGs in 2015, global health spending has increased, reaching 7·9 trillion (95% uncertainty interval 7·8–8·0) in 2017 and is expected to increase to 110trillion(107112)by2030.In2017,inlowincomeandmiddleincomecountriesspendingonHIV/AIDSwas11·0 trillion (10·7–11·2) by 2030. In 2017, in low-income and middle-income countries spending on HIV/AIDS was 20·2 billion (17·0–25·0) and on tuberculosis it was 109billion(103118),andinmalariaendemiccountriesspendingonmalariawas10·9 billion (10·3–11·8), and in malaria-endemic countries spending on malaria was 5·1 billion (4·9–5·4). Development assistance for health was 406billionin2019andHIV/AIDShasbeenthehealthfocusareatoreceivethehighestcontributionsince2004.In2019,40·6 billion in 2019 and HIV/AIDS has been the health focus area to receive the highest contribution since 2004. In 2019, 374 million of DAH was provided for pandemic preparedness, less than 1% of DAH. Although spending has increased across HIV/AIDS, tuberculosis, and malaria since 2015, spending has not increased in all countries, and outcomes in terms of prevalence, incidence, and per-capita spending have been mixed. The proportion of health spending from pooled sources is expected to increase from 81·6% (81·6–81·7) in 2015 to 83·1% (82·8–83·3) in 2030. Interpretation: Health spending on SDG3 priority areas has increased, but not in all countries, and progress towards meeting the SDG3 targets has been mixed and has varied by country and by target. The evidence on the scale-up of spending and improvements in health outcomes suggest a nuanced relationship, such that increases in spending do not always results in improvements in outcomes. Although countries will probably need more resources to achieve SDG3, other constraints in the broader health system such as inefficient allocation of resources across interventions and populations, weak governance systems, human resource shortages, and drug shortages, will also need to be addressed. Funding: The Bill & Melinda Gates Foundatio
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