Assessing public financing for nutrition in Bhutan, Nepal and Sri Lanka.

The objective of this study was to assess public financing for nutrition in Bhutan, Nepal and Sri Lanka to identify limitations of available data and to discuss policy implications. A variant of the Scaling Up Nutrition Movement methodology was used. Budget allocations and expenditures for relevant government ministries during 2012-2018 were identified. Nutrition-related line items were tagged using definitions of nutrition-specific and nutrition-sensitive interventions. Data were aggregated by year and calculated in constant United States dollars (USD). Expenditures by year were presented as a proportion of gross domestic product and general government expenditures. The percent utilization of budget allocations and proportion of funding from central government sources were determined. Per capita expenditures on nutrition-specific interventions varied from USD 1.08-8.76 and for nutrition-sensitive interventions varied from USD 20.22-51.20. Nutrition-specific expenditures as a percent of gross domestic product ranged from 0.08% in Sri Lanka in 2017% to 0.34% in Nepal in 2016. The median utilization rate was 64% for nutrition-specific and 84% for nutrition-sensitive interventions. Nutrition-specific funding financed by the central government was 90.7% in Bhutan and 99.4% in Sri Lanka. This study revealed the need to prioritize and invest in evidence-based interventions, including balancing investments in nutrition-specific versus -sensitive interventions. Challenges in estimation of nutrition expenditures and cross-country comparison were also observed, highlighting the need for appropriate nutrition line item tagging and standardized systems for data collection.

The G20 and development assistance for health: historical trends and crucial questions to inform a new era.

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.

From Universal Health Coverage services packages to budget appropriation: the long journey to implementation.

Essential packages of health services (EPHS) potentially contribute to universal health coverage (UHC) financing through several pathways. Generally, expectations on what an EPHS can achieve for health financing are high, yet stakeholders rarely spell out mechanisms to reach desired outcomes. This paper analyses how EPHS relate to the three health financing functions (revenue raising, risk pooling and purchasing) and to public financial management (PFM). Our review of country experiences found that using EPHS to directly leverage funds for health has rarely been effective. Indirectly, EPHS can translate into increased revenue through fiscal measures, including health taxes. Through improved dialogue with public finance authorities, health policy-makers can use EPHS or health benefit packages to communicate the value of additional public spending connected with UHC indicators. Overall, however, empirical evidence on EPHS contribution to resource mobilisation is still pending. EPHS development exercises have been more successful in advancing resource pooling across different schemes: EPHS can help comparing performance of coverage schemes, occasionally leading to harmonisation of UHC interventions and identifying gaps between health financing and service delivery. EPHS development and iterative revisions play an essential role in core strategic purchasing activities as countries develop their health technology assessment capacity. Ultimately, packages need to translate into adequate public financing appropriations through country health programme design, ensuring funding flows directly address obstacles to increased coverage.

Addiction to a bad idea, especially in low- and middle-income countries: Contributory health insurance.

Despite limited evidence of successful development and implementation of contributory health insurance and low and middle income countries, many countries are in the process implementing such schemes. This commentary summarizes all available evidence on the limitations of contributory health insurance including the lack of good theoretical underpinning and the considerable evidence of inequity and fragmentation created by such schemes. Moreover, the initiation of a contributory health insurance scheme has not been found to increase revenues to the health sector or help health countries achieve universal health coverage. Low and middle income countries can improve equity and efficiency of the health sector by replacing out-of-pocket spending with pre-paid pooling mechanisms, but that is best done through budget transfers and not by contributory insurance that links payment to sub-population entitlements.

Adverse birth outcomes among women with 'low-risk' pregnancies in India: findings from the Fifth National Family Health Survey, 2019-21.

Background: Despite substantial progress in improving maternal and newborn health, India continues to experience high rates of newborn mortality and stillbirths. One reason may be that many births happen in health facilities that lack advanced services-such as Caesarean section, blood transfusion, or newborn intensive care. Stratification based on pregnancy risk factors is used to guide 'high-risk' women to advanced facilities. To assess the utility of risk stratification for guiding the choice of facility, we estimated the frequency of adverse newborn outcomes among women classified as 'low risk' in India. Methods: We used the 2019-21 Fifth National Family Health Survey (NFHS-5)-India's Demographic and Health Survey-which includes modules administered to women aged 15-49 years. In addition to pregnancy history and outcomes, the survey collected a range of risk factors, including biomarkers. We used national obstetric risk guidelines to classify women as 'high risk' versus 'low risk' and assessed the frequency of stillbirths, newborn deaths, and unplanned Caesarean sections for the respondent's last pregnancy lasting 7 or more months in the past five years. We calculated the proportion of deliveries occurring at non-hospital facilities in all the Indian states. Findings: Using data from nearly 176,699 recent pregnancies, we found that 46.6% of India's newborn deaths and 56.3% of stillbirths were among women who were 'low risk' according to national guidelines. Women classified as 'low risk' had a Caesarean section rate of 8.4% (95% CI 8.1-8.7%), marginally lower than the national average of 10.0% (95% CI 9.8-10.3%). In India as a whole, 32.0% (95% CI 31.5-32.5%) of deliveries occurred in facilities that were likely to lack advanced services. There was substantial variation across the country, with less than 5% non-hospital public facility deliveries in Punjab, Kerala, and Delhi compared to more than 40% in Odisha, Madhya Pradesh, and Rajasthan. Newborn mortality tended to be lower in states with highest hospital delivery rates. Interpretation: Individual risk stratification based on factors identified in pregnancy fails to accurately predict which women will have delivery complications and experience stillbirth and newborn death in India. Thus a determination of 'low risk' should not be used to guide women to health facilities lacking key life saving services, including Caesarean section, blood transfusion, and advanced newborn resuscitation and care. Funding: Bill and Melinda Gates Foundation and the World Bank. The findings, interpretations and conclusions expressed in the paper are entirely those of the authors, and do not represent the views of the Gates Foundation or of the World Bank, its Executive Directors, or the countries they represent.

Redistribution and the health financing transition.

Public financing is necessary for realizing universal health coverage (UHC), a policy commitment that emphasizes that everyone should have access to health services they need, of sufficient quality to be effective, and that the use of these services does not expose individuals to financial hardship. As countries undergo their health financing transitions, moving away from external and out-of-pocket (OOP) financing toward domestically-sourced public financing, finding ways to increase public financing in an efficient, equitable, and sustainable manner is front and center in the policy dialogue around UHC. This paper focuses on one aspect of the health financing transition that has generally received less attention: that UHC is also intrinsically about a policy direction that emphasizes at its core redistribution of resources from the well-off to the poor. Differences in the level and organization of public financing for health for a given level of national income also reflect differences in social and political preferences for redistribution and equity across countries. Hence, navigation of a country's health financing transition in ways that accelerates progress towards UHC also implies that public resources are targeted and expended in ways to improve effective service coverage and reduce OOP spending specifically for the poor. To leverage a country's health financing transition for UHC, mechanisms should be introduced for: (i) ensuring that benefit entitlements are explicit and intertemporally commensurate with levels of public financing; (ii) fragmentation in pooling mechanisms is reduced to facilitate cross-subsidization without jeopardizing equity; (iii) levels of OOP and complementary sources of financing are nudged towards the well-off until core levels of public financing are adequate to provide similar levels of coverage for all; and (v) that purchasing of services is done in ways that helps reduce geographic- and income-related inequities in access and supply of quality health services. This implies careful policy choices need to be made, ones that require looking beyond the simplistic dichotomy between OOP and public sources of financing for UHC at the aggregate level to more nuanced and disaggregated assessments of the organization, use, and net fiscal incidence of financing and expenditures.

Will the Quest for UHC be Derailed?

COVID-19 has shocked all countries' economic and health systems. The combined direct health impact and the current macro-fiscal picture present real and present risks to health financing that facilitate progress toward universal health coverage (UHC). This paper lays out the health financing mechanisms through which the UHC objectives of service coverage and financial protection may be impacted. Macroeconomic, fiscal capacity, and poverty indicators and trends are analyzed in conjunction with health financing indicators to present spending scenarios. The analysis shows that falling or reduced economic growth, combined with rising poverty, is likely to lead to a fall in service use and coverage, while any observed reductions in out-of-pocket spending have to be analyzed carefully to make sure they reflect improved financial protection and not just decreased utilization of services. Potential decreases in out-of-pocket spending will likely be drive by households' financial constraints that lead to less service use. In this way, it is critical to measure and monitor both the service coverage and financial protection indicators of UHC to have a complete picture of downstream effects. The analysis of historical data, including available evidence since the start of the COVID-19 pandemic, lay the foundation for health financing-related policy options that can effectively safeguard UHC progress particularly for the poor and most vulnerable. These targeted policy options are based on documented evidence of effective country responses to previous crises as well as the overall evidence base around health financing for UHC.

From slippery slopes to steep hills: Contrasting landscapes of economic growth and public spending for health.

Identifying ways to increase public spending on health is critical for the achievement of universal health coverage. While policymakers and donors often look at available options for increasing public spending for health in the medium-term, examining trends and drivers of past growth can help countries elucidate important lessons and to anticipate changes in the future. This note analyzes trends in inflation-adjusted per capita public spending for health vis-à-vis economic growth within and across a sample of 150 countries over the 2000-2017 period. Since 2000, per capita public spending for health across low- and middle-income countries has more than doubled. Less than one-fifth of this increase, however, resulted from a higher priority for health in government budgets. The remainder was largely due to conducive macroeconomic conditions such as economic growth and increases in total public spending. Furthermore, across most countries, a single time trend does not adequately capture the evolution either of economic growth or of per capita public spending on health. Instability in growth rates is large for both indicators, revealing distinct episodic patterns.

Economic Contraction from COVID-19 in the Pacific: Implications for Health Financing.

Pacific Island countries (PIC) have emerged as among the most at-risk globally from the collateral economic damage resulting from the COVID-19 pandemic, despite being largely spared its direct health effects so far. Current projections indicate that all PIC will experience an economic contraction in 2020, ranging from -1.0% in Tuvalu to -21.7% in Fiji, worse than most countries globally on average. Given that more than 80% of financing for health in the Pacific comes from domestic and external public sources, the net impact of the economic contraction on resources for health will depend on whether overall public spending can offset the decline in economic activity and how health will be prioritized in government budgets relative to other sectors. Without active reprioritization, most countries could see a slowdown or even decline in per capita levels of public spending for health in the region, risking gains made in advancing universal health coverage in recent years. If health ministries do not act quickly and in consort with other ministries (particularly ministries of finance), including by taking active steps to improve the efficient use of existing resources and other measures to mitigate the economic effects of the crisis on resources for health, it is likely that current economic circumstances will result in unplanned changes. These changes may not deliver the health outcomes that the health ministries would select themselves and may result in a reversal of hard-fought health gains.

The Case Against Labor-Tax-Financed Social Health Insurance For Low- And Low-Middle-Income Countries.

An increasing interest in initiating and expanding social health insurance through labor taxes in low- and low-middle-income countries goes against available empirical evidence. This article builds on existing recommendations by leading health financing experts and summarizes recent research that makes the case against labor-tax financing of health care in low- and low-middle-income countries. We found very little evidence to justify the pursuit of labor-tax financing for health care in these countries and persistent evidence that such policies could lead to increased inequality and fragmentation of the health system. We recommend that countries considering such policies heed the evidence on labor-tax financing and seek alternative approaches to health financing: primarily using general taxes or, depending on the context, general taxes combined with adequately regulated insurance premiums.

Depression, chronic diseases, and decrements in health: results from the World Health Surveys.

BACKGROUND: Depression is an important public-health problem, and one of the leading causes of disease burden worldwide. Depression is often comorbid with other chronic diseases and can worsen their associated health outcomes. Few studies have explored the effect of depression, alone or as a comorbidity, on overall health status. METHODS: The WHO World Health Survey (WHS) studied adults aged 18 years and older to obtain data for health, health-related outcomes, and their determinants. Prevalence of depression in respondents based on ICD-10 criteria was estimated. Prevalence values for four chronic physical diseases--angina, arthritis, asthma, and diabetes--were also estimated using algorithms derived via a Diagnostic Item Probability Study. Mean health scores were constructed using factor analysis and compared across different disease states and demographic variables. The relation of these disease states to mean health scores was determined through regression modelling. FINDINGS: Observations were available for 245 404 participants from 60 countries in all regions of the world. Overall, 1-year prevalence for ICD-10 depressive episode alone was 3.2% (95% CI 3.0-3.5); for angina 4.5% (4.3-4.8); for arthritis 4.1% (3.8-4.3); for asthma 3.3% (2.9-3.6); and for diabetes 2.0% (1.8-2.2). An average of between 9.3% and 23.0% of participants with one or more chronic physical disease had comorbid depression. This result was significantly higher than the likelihood of having depression in the absence of a chronic physical disease (p<0.0001). After adjustment for socioeconomic factors and health conditions, depression had the largest effect on worsening mean health scores compared with the other chronic conditions. Consistently across countries and different demographic characteristics, respondents with depression comorbid with one or more chronic diseases had the worst health scores of all the disease states. INTERPRETATION: Depression produces the greatest decrement in health compared with the chronic diseases angina, arthritis, asthma, and diabetes. The comorbid state of depression incrementally worsens health compared with depression alone, with any of the chronic diseases alone, and with any combination of chronic diseases without depression. These results indicate the urgency of addressing depression as a public-health priority to reduce disease burden and disability, and to improve the overall health of populations.

Validity of reported vaccination coverage in 45 countries.

BACKGROUND: Monitoring and assessment of coverage rates in national health programmes is becoming increasingly important. We aimed to assess the accuracy of officially reported coverage rates of vaccination with diphtheria-tetanus-pertussis vaccine (DTP3), which is commonly used to monitor child health interventions. METHODS: We compared officially reported national data for DTP3 coverage with those from the household Demographic and Health Surveys (DHS) in 45 countries between 1990 and 2000. We adjusted survey data to reflect the number of valid vaccinations (ie, those administered in accordance with the schedule recommended by WHO) using a probit model with sample selection. The model predicted the probability of valid vaccinations for children, including those without documented vaccinations, after correcting for bias from differences between the children with and without documented information on vaccination. We then assessed the extent of survey bias and differences between officially reported data and those from DHS estimates. FINDINGS: Our results suggest that officially reported DTP3 coverage is higher than that reported from household surveys. This size of the difference increases with the rate of reported coverage of DTP3. Results of time-trend analysis show that changes in reported coverage are not correlated with changes reported from household surveys. INTERPRETATION: Although reported data might be the most widely available information for assessment of vaccination coverage, their validity for measuring changes in coverage over time is highly questionable. Household surveys can be used to validate data collected by service providers. Strategies for measurement of the coverage of all health interventions should be grounded in careful assessments of the validity of data derived from various sources.

Access, utilization, quality, and effective coverage: an integrated conceptual framework and measurement strategy.

Health systems can primarily improve the health of individuals and populations by delivering high-quality interventions to those who may benefit from them. We propose a concept of effective coverage as the probability that individuals will receive health gain from an intervention if they need it. Understanding the extent to which health systems are delivering key interventions to those who will benefit from them and the factors that explain gaps in delivery are a critical input to decision-making at the local, national and global levels. We develop an integrated conceptual framework for monitoring and analyzing the delivery of high-quality interventions to those who need them. This framework can help clarify the inter-relationships between notions of access, demand for care, utilization, and coverage on the one hand and highlight the requirements for health information systems that can sustain this type of analysis. We discuss measurement strategies and demonstrate the concept by means of a simple simulation model.

From wealth to health: modelling the distribution of income per capita at the sub-national level using night-time light imagery.

BACKGROUND: Sub-national figures providing information about the wealth of the population are useful in defining the spatial distribution of both economic activity and poverty within any given country. Furthermore, since several health indicators such as life expectancy are highly correlated with household welfare, sub-national figures allow for the estimation of the distribution of these health indicators within countries when direct measurement is difficult.We have developed methods that utilize spatially distributed information, including night-time light imagery and population to model the distribution of income per capita, as a proxy for wealth, at the country and sub-national level to support the estimation of the distribution of correlated health indicators. RESULTS: A first set of analysis are performed in order to propose a new global model for the prediction of income per capita at the country level. A second set of analysis is then confirming the possibility to transfer the country level approach to the sub-national level on a country by country basis before underlining the difficulties to create a global or regional models for the extrapolation of sub-national figures when no country data set exists. CONCLUSIONS: The methods described provide promising results for the extrapolation of national and sub-national income per capita figures. These results are then discussed in order to evaluate if the proposed methods could not represent an alternative approach for the generation of consistent country specific and/or global poverty maps disaggregated to some sub-national level.

Healthy life expectancy: comparison of OECD countries in 2001.

OBJECTIVES: To compare average levels of population health for Australia and other OECD countries in 2001. METHODS: Healthy life expectancies (HALE) for OECD countries for 2001 are based on analysis of mortality data for OECD countries, country-specific estimates of health state prevalences for 135 causes from the Global Burden of Disease 2000 study, and an analysis of 34 health surveys in 28 OECD countries, using novel methods to improve the comparability of self-report data. RESULTS: HALE at birth ranges from a low of 59.8 years for Turkey to a high of 73.6 years in Japan in 2001. Australia ranks fourth among OECD countries at 71.6 years with a 95% uncertainty interval of 70.9 to 72.8 years, ahead of New Zealand in 13th place at 70.3 years. The equivalent 'lost' healthy years at birth range from around 10 years in OECD countries with lowest life expectancies to around eight years in those with high life expectancies at birth. There is a statistically significant association between higher levels of health expenditure and higher healthy life expectancy across OECD countries, although causal inferences require more sophisticated analyses of the health system and non-health system determinants of levels of health. CONCLUSIONS: The new methods used in the WHO Multi-Country Household Survey Study have increased the comparability of self-report data across OECD countries, a major step forward in the use of self-reported data on health. Building on this experience, WHO is developing improved health status measurement techniques for a World Health Survey to be carried out in 2002/03.

Global patterns of healthy life expectancy in the year 2002.

BACKGROUND: Healthy life expectancy--sometimes called health-adjusted life expectancy (HALE)--is a form of health expectancy indicator that extends measures of life expectancy to account for the distribution of health states in the population. The World Health Organization reports on healthy life expectancy for 192 WHO Member States. This paper describes variation in average levels of population health across these countries and by sex for the year 2002. METHODS: Mortality was analysed for 192 countries and disability from 135 causes assessed for 17 regions of the world. Health surveys in 61 countries were analyzed using new methods to improve the comparability of self-report data. RESULTS: Healthy life expectancy at birth ranged from 40 years for males in Africa to over 70 years for females in developed countries in 2002. The equivalent "lost" healthy years ranged from 15% of total life expectancy at birth in Africa to 8-9% in developed countries. CONCLUSION: People living in poor countries not only face lower life expectancies than those in richer countries but also live a higher proportion of their lives in poor health.

Reprioritizing government spending on health: pushing an elephant up the stairs?

Countries vary widely with respect to the share of government spending on health, a metric that can serve as a proxy for the extent to which health is prioritized by governments. World Health Organization (WHO) data estimate that, in 2011, health's share of aggregate government expenditure averaged 12% in the 170 countries for which data were available. However, country differences were striking: ranging from a low of 1% in Myanmar to a high of 28% in Costa Rica. Some of the observed differences in health's share of government spending across countries are unsurprisingly related to differences in national income. However, significant variations exist in health's share of government spending even after controlling for national income. This paper provides a global overview of health's share of government spending and summarizes some of the key theoretical and empirical perspectives on allocation of public resources to health vis-à-vis other sectors from the perspective of reprioritization, one of the modalities for realizing fiscal space for health. The paper argues that theory and cross-country empirical analyses do not provide clear-cut explanations for the observed variations in government prioritization of health. Standard economic theory arguments that are often used to justify public financing for health are equally applicable to many other sectors including defence, education and infrastructure. To date, empirical work on prioritization has been sparse: available cross-country econometric analyses suggest that factors such as democratization, lower levels of corruption, ethnolinguistic homogeneity and more women in public office are correlated with higher shares of public spending on health; however, these findings are not robust and are sensitive to model specification. Evidence from case studies suggests that country-specific political economy considerations are key, and that results-focused reform efforts - in particular efforts to explicitly expand the breadth and depth of health coverage as opposed to efforts focused only on government budgetary benchmarking targets - are more likely to result in sustained and politically feasible prioritization of health from a fiscal space perspective.