Disease control programme support costs: an update of WHO-CHOICE methodology, price databases and quantity assumptions.

BACKGROUND: Estimating health care costs, either in the context of understanding resource utilization in the implementation of a health plan, or in the context of economic evaluation, has become a common activity of health planners, health technology assessment agencies and academic groups. However, data sources for costs outside of direct service delivery are often scarce. WHO-CHOICE produces global price databases and guidance on quantity assumptions to support country level costing exercises. This paper presents updates to the WHO-CHOICE methodology and price databases for programme costs. METHODS: We collated publicly available databases for 14 non-traded cost variables, as well as a set of traded items used within health systems (traded goods are those which can be purchased from anywhere in the world, whereas non-traded goods are those which must be produced locally, such as human resources). Within each of the variables, missing data was present for some proportion of the WHO member states. For each variables statistical or econometric models were used to model prices for each of the 194 WHO member states in 2010 International Dollars. Literature reviews were used to update quantity assumptions associated with each variable to contribute to the support costs of disease control programmes. RESULTS: A full database of prices for disease control programme support costs is available for country-specific costing purposes. Human resources are the largest driver of disease control programme support costs, followed by supervision costs. CONCLUSIONS: Despite major advances in the availability of data since the previous version of this work, there are still some limitations in data availability to respond to the needs of those wishing to develop cost and cost-effectiveness estimates. Greater attention to programme support costs in cost data collection activities would contribute to an understanding of how these costs contribute to quality of health service delivery and should be encouraged.

Guidance on priority setting in health care (GPS-Health): the inclusion of equity criteria not captured by cost-effectiveness analysis.

This Guidance for Priority Setting in Health Care (GPS-Health), initiated by the World Health Organization, offers a comprehensive map of equity criteria that are relevant to health care priority setting and should be considered in addition to cost-effectiveness analysis. The guidance, in the form of a checklist, is especially targeted at decision makers who set priorities at national and sub-national levels, and those who interpret findings from cost-effectiveness analysis. It is also targeted at researchers conducting cost-effectiveness analysis to improve reporting of their results in the light of these other criteria. THE GUIDANCE WAS DEVELOP THROUGH A SERIES OF EXPERT CONSULTATION MEETINGS AND INVOLVED THREE STEPS: i) methods and normative concepts were identified through a systematic review; ii) the review findings were critically assessed in the expert consultation meetings which resulted in a draft checklist of normative criteria; iii) the checklist was validated though an extensive hearing process with input from a range of relevant stakeholders. The GPS-Health incorporates criteria related to the disease an intervention targets (severity of disease, capacity to benefit, and past health loss); characteristics of social groups an intervention targets (socioeconomic status, area of living, gender; race, ethnicity, religion and sexual orientation); and non-health consequences of an intervention (financial protection, economic productivity, and care for others).

The costs of improving health emergency preparedness: A systematic review and analysis of multi-country studies.

BACKGROUND: Investing in health emergency preparedness is critical to the safety, welfare and stability of communities and countries worldwide. Despite the global push to increase investments, questions remain around how much should be spent and what to focus on. We conducted a systematic review and analysis of studies that costed improvements to health emergency preparedness to help to answer these questions. METHODS: We searched for studies that estimated the costs of improving health emergency preparedness and that were published between 1 January 2000 and 14 May 2021, using PubMed, Web of Science, Google Scholar, EconLit, and National Health Service Economic Evaluation Databases (PROSPERO CRD42021254428). We also searched grey literature repositories and contacted subject experts. We included studies that estimated the costs of improving preparedness at the global level and/or at the national level across at least ten countries, covered two or more technical areas in the WHO Benchmarks for International Health Regulations (IHR) Capacities, and included activities focused on human health. We mapped costs across technical areas in the WHO Benchmarks for IHR Capacities. FINDINGS: Ten studies met our inclusion criteria. Costing methods varied substantially across included studies and cost estimates ranged from US$1·6 billion per year to improve capacities across 139 low- and middle-income countries (LMICs) to US$43 billion per year to support national-level activities worldwide and implement global-level initiatives, such as research and development for health technologies (diagnostics, therapeutics, and vaccines). Two recent studies estimated costs by drawing on IHR Monitoring and Evaluation Framework country capacity data, with one study estimating costs across 67 LMICs of US$15·4 billion per year (US$29·1 billion including upfront capital costs) and the other calculating costs for the 196 States Parties to the IHR of US$24·8 billion per year. Differences in included studies' methods, and the characteristics of countries considered, mean it is difficult to make like-for-like comparisons of the absolute costs or per-capita costs estimated by studies. INTERPRETATION: Improving health emergency preparedness worldwide will require substantial and sustained increases in investments. Further guidance on estimating the size of those investments can help to standardise methods, allowing greater interpretation and comparison across studies/countries. As well as greater transparency and detail in the reporting of methods by studies focused on this topic, this can help support estimates of global resource requirements and facilitate investments towards improving preparedness for future pandemics. FUNDING: None.

Introduction to the Special Issue on "The World Health Organization Choosing Interventions That Are Cost-Effective (WHO-CHOICE) Update".

The WHO-CHOICE (World Health Organization CHOosing Interventions that are Cost-Effective) approach is unique in the global health landscape, as it takes a "generalized" approach to cost-effectiveness analysis (CEA) that can be seen as a quantitative assessment of current and future efficiency within a health system. CEA is a critical contribution to the process of priority setting and decision-making in healthcare, contributing to deliberative dialogue processes to select services to be funded. WHO-CHOICE provides regional level estimates of cost-effectiveness, along with tools to support country level analyses. This series provides an update to the methodological approach used in WHO-CHOICE and presents updated cost-effectiveness estimates for 479 interventions. Five papers are presented, the first focusing on methodological updates, followed by three results papers on maternal, newborn and child health; HIV, tuberculosis and malaria; and non-communicable diseases and mental health. The final paper presents a set of example universal health coverage (UHC) benefit packages selected through only a value for money lens, showing that all disease areas have interventions which can fall on the efficiency frontier. Critical for all countries is institutionalizing decision-making processes. A UHC benefit package should not be static, as the countries needs and ability to pay change over time. Decisions will need to be continually revised and new interventions added to health benefit packages. This is a vital component of progressive realization, as the package is expanded over time. Developing an institutionalized process ensures this can be done consistently, fairly, and transparently, to ensure an equitable path to UHC.

Methods for the Economic Evaluation of Health Care Interventions for Priority Setting in the Health System: An Update From WHO CHOICE.

The World Health Organization's (WHO's) Choosing Interventions that are Cost-Effective (CHOICE) programme has been a global leader in the field of economic evaluation, specifically cost-effectiveness analysis for almost 20 years. WHO-CHOICE takes a "generalized" approach to cost-effectiveness analysis that can be seen as a quantitative assessment of current and future efficiency within a health system. This supports priority setting processes, ensuring that health stewards know how to spend resources in order to achieve the highest health gain as one consideration in strategic planning. This approach is unique in the global health landscape. This paper provides an overview of the methodological approach, updates to analytic framework over the past 10 years, and the added value of the WHO-CHOICE approach in supporting decision makers as they aim to use limited health resources to achieve the Sustainable Development Goals (SDGs) by 2030.

Progressive Realisation of Universal Health Coverage in Low- and Middle-Income Countries: Beyond the "Best Buys".

BACKGROUND: World Health Organization Choosing Interventions that are Cost-Effective (WHO CHOICE) has been a programme of the WHO for 20 years. In this latest update, we present for the first time a cross-programme analysis of the comparative cost-effectiveness of 479 intervention scenarios across 20 disease programmes and risk factors. METHODS: This analysis follows the standard WHO CHOICE approach to generalized cost-effectiveness analysis applied to two regions, Eastern sub-Saharan Africa and Southeast Asia. The scope of the analysis is all interventions included in programme specific WHO CHOICE analyses, using WHO treatment guidelines for major disease areas as the foundation. Costs are measured in 2010 international dollars, and benefits modelled beginning in 2010, or the nearest year for which validated data was available, both for a period of 100 years. RESULTS: Across both regions included in the analysis, interventions span multiple orders of magnitude in terms of cost-effectiveness ratios. A health benefit package optimized through a value for money lens incorporates interventions responding to all of the main drivers of disease burden. Interventions delivered through first level clinical and non-clinical services represent the majority of the high impact cost-effective interventions. CONCLUSION: Cost-effectiveness is one important criterion when selecting health interventions for benefit packages to progress towards universal health coverage (UHC), but it is not the only criterion and all calculations should be adapted to the local context. To support country decision-makers, WHO CHOICE has developed a downloadable tool to support the development of data for this criterion.

Challenges and experiences in linking community level reported out-of-pocket health expenditures to health provider recorded health expenditures: Experience from the iHOPE project in Northern Ghana.

Out of pocket health payment (OOPs) has been identified by the System of Health Accounts (SHA) as the largest source of health care financing in most low and middle-income countries. This means that most low and middle-income countries will rely on user fees and co-payments to generate revenue, rationalize the use of services, contain health systems costs or improve health system efficiency and service quality. However, the accurate measurement of OOPs has been challenged by several limitations which are attributed to both sampling and non-sampling errors when OOPs are estimated from household surveys, the primary source of information in LICs and LMICs. The incorrect measurement of OOP health payments can undermine the credibility of current health spending estimates, an otherwise important indicator for tracking UHC, hence there is the need to address these limitations and improve the measurement of OOPs. In an attempt to improve the measurement of OOPs in surveys, the INDEPTH-Network Household out-of-pocket expenditure project (iHOPE) developed new modules on household health utilization and expenditure by repurposing the existing Ghana Living Standards Survey instrument and validating these new tools with a 'gold standard' (provider data) with the aim of proposing alternative approaches capable of producing reliable data for estimating OOPs in the context of National Health Accounts and for the purpose of monitoring financial protection in health. This paper reports on the challenges and opportunities in using and linking household reported out-of-pocket health expenditures to their corresponding provider records for the purpose of validating household reported out-of-pocket health expenditure in the iHOPE project.

Investigating the effect of recall period on estimates of inpatient out-of-pocket expenditure from household surveys in Vietnam.

Out-of-pocket payments (OOPs), direct payments by households or individuals for healthcare are part of the health financing landscape. Data on OOPs is needed to monitor progress in financial risk protection, and the evaluation of health financing policies. In low-and-middle-income countries, estimates of OOPs rely heavily on self-reported data from household surveys. These surveys require respondents to recall events in the past and can suffer from recall biases. This study investigates the effect of recall period on the agreement of the amount and timing of inpatient OOPs between household reports and provider records in Bavi, Vietnam. We recruited 1397 households for interview using records from the district hospital. The households were interviewed with identical questionnaires except that the recall period was either 12 or 6 months. We linked household with provider data and excluded medicine costs from both household and provider OOPs since they could be purchased outside the hospital. We estimated the effect of recall period on the overall mean and variability of ratios of household to hospital reported OOPs using the Bland-Altman approach for method comparison. We estimated the effect of recall period on whether a transaction was recalled correctly in expenditure and time using multinomial regression. The households reported higher amounts of OOPs than did the hospital for both recall periods. There was no evidence of an effect of recall period on the mean of the ratios of household- to hospital-reported OOPs, although the confidence intervals are not inconsistent with previous studies indicating higher OOPs for shorter recall periods. The geometric mean ratio for the 6-month period was estimated to be a multiple of 1.4 (95% CI 0.9, 2.1) times that of the 12-month period. Similarly, there was no evidence of an effect of recall period on the risk of reporting lower or higher amounts than provider OOPs. The occurrence and timing of inpatient stays generally recalled well, with 70% remembered in the correct month declining slightly over time. Respondents for the 6-month recall period had a significantly lower risk of failing to report the event (RR 0.8 (0.7, 1.0)). The results suggest the best recall period may depend on whether the purpose of a survey is for the recall of the timing of events, in which case the 6 month period may be better, or the amounts of OOPs, where there was no significant difference and the provider records are not a gold standard but the 12 month period had a tendency to be in closer agreement with the provider OOPs.

Financing transformative health systems towards achievement of the health Sustainable Development Goals: a model for projected resource needs in 67 low-income and middle-income countries.

BACKGROUND: The ambitious development agenda of the Sustainable Development Goals (SDGs) requires substantial investments across several sectors, including for SDG 3 (healthy lives and wellbeing). No estimates of the additional resources needed to strengthen comprehensive health service delivery towards the attainment of SDG 3 and universal health coverage in low-income and middle-income countries have been published. METHODS: We developed a framework for health systems strengthening, within which population-level and individual-level health service coverage is gradually scaled up over time. We developed projections for 67 low-income and middle-income countries from 2016 to 2030, representing 95% of the total population in low-income and middle-income countries. We considered four service delivery platforms, and modelled two scenarios with differing levels of ambition: a progress scenario, in which countries' advancement towards global targets is constrained by their health system's assumed absorptive capacity, and an ambitious scenario, in which most countries attain the global targets. We estimated the associated costs and health effects, including reduced prevalence of illness, lives saved, and increases in life expectancy. We projected available funding by country and year, taking into account economic growth and anticipated allocation towards the health sector, to allow for an analysis of affordability and financial sustainability. FINDINGS: We estimate that an additional $274 billion spending on health is needed per year by 2030 to make progress towards the SDG 3 targets (progress scenario), whereas US$371 billion would be needed to reach health system targets in the ambitious scenario-the equivalent of an additional $41 (range 15-102) or $58 (22-167) per person, respectively, by the final years of scale-up. In the ambitious scenario, total health-care spending would increase to a population-weighted mean of $271 per person (range 74-984) across country contexts, and the share of gross domestic product spent on health would increase to a mean of 7·5% (2·1-20·5). Around 75% of costs are for health systems, with health workforce and infrastructure (including medical equipment) as the main cost drivers. Despite projected increases in health spending, a financing gap of $20-54 billion per year is projected. Should funds be made available and used as planned, the ambitious scenario would save 97 million lives and significantly increase life expectancy by 3·1-8·4 years, depending on the country profile. INTERPRETATION: All countries will need to strengthen investments in health systems to expand service provision in order to reach SDG 3 health targets, but even the poorest can reach some level of universality. In view of anticipated resource constraints, each country will need to prioritise equitably, plan strategically, and cost realistically its own path towards SDG 3 and universal health coverage. FUNDING: WHO.

Improving the use of research evidence in guideline development: 11. Incorporating considerations of cost-effectiveness, affordability and resource implications.

BACKGROUND: The World Health Organization (WHO), like many other organisations around the world, has recognised the need to use more rigorous processes to ensure that health care recommendations are informed by the best available research evidence. This is the 11th of a series of 16 reviews that have been prepared as background for advice from the WHO Advisory Committee on Health Research to WHO on how to achieve this. OBJECTIVES: We reviewed the literature on incorporating considerations of cost-effectiveness, affordability and resource implications in guidelines and recommendations. METHODS: We searched PubMed and three databases of methodological studies for existing systematic reviews and relevant methodological research. We did not conduct systematic reviews ourselves. Our conclusions are based on the available evidence, consideration of what WHO and other organisations are doing and logical arguments. KEY QUESTIONS AND ANSWERS: When is it important to incorporate cost-effectiveness, resource implications and affordability considerations in WHO guidelines (which topics)? For cost-effectiveness:The need for cost/effectiveness information should be dictated by the specific question, of which several may be addressed in a single guideline. It is proposed that the indications for undertaking a cost-effectiveness analysis (CEA) could be a starting point for determining which recommendation(s) in the guideline would benefit from such analysis. For resource implications/affordability:The resource implications of each individual recommendation need to be considered when implementation issues are being discussed. How can cost-effectiveness, resource implications and affordability be explicitly taken into account in WHO guidelines? For cost-effectiveness: composite function If data are available, the ideal time to consider cost-effectiveness is during the evidence gathering and synthesizing stage. However, because of the inconsistent availability of CEAs and the procedural difficulty associated with adjusting results from different CEAs to make them comparable, it is also possible for cost-effectiveness to be considered during the stage of developing recommendations. composite function Depending on the quantity and quality and relevance of the data available, such data can be considered in a qualitative way or in a quantitative way, ranging from a listing of the costs to a modelling exercise. At the very least, a qualitative approach like a commentary outlining the economic issues that need to be considered is necessary. If a quantitative approach is to be used, the full model should be transparent and comprehensive. For resource implications/affordability: composite function Resource implications, including health system changes, for each recommendation in a WHO guideline should be explored. At the minimum, a qualitative description that can serve as a gross indicator of the amount of resources needed, relative to current practice, should be provided. How does one provide guidance in contextualizing guideline recommendations at the country level based on considerations of cost-effectiveness, resource implications and affordability? All models should be made available and ideally are designed to allow for analysts to make changes in key parameters and reapply results in their own country. In the global guidelines, scenarios and extensive sensitivity/uncertainty analysis can be applied.Resource implications for WHO. From the above, it is clear that guidelines development groups will need a health economist. There is need to ensure that this is included in the budget for guidelines and that there is in-house support for this as well.

Achieving the WHO/UNAIDS antiretroviral treatment 3 by 5 goal: what will it cost?

The "3 by 5" goal to have 3 million people in low and middle income countries on antiretroviral therapy (ART) by the end of 2005 is ambitious. Estimates of the necessary resources are needed to facilitate resource mobilisation and rapid channelling of funds to where they are required. We estimated the financial costs needed to implement treatment protocols, by use of country-specific estimates for 34 countries that account for 90% of the need for ART in resource-poor settings. We first estimated the number of people needing ART and supporting programmes for each country. We then estimated the cost per patient for each programme by country to derive total costs. We estimate that between US5.1 billion dollars and US5.9 billion dollars will be needed by the end of 2005 to provide ART, support programmes, and cover country-level administrative and logistic costs for 3 by 5.

Systems for grading the quality of evidence and the strength of recommendations II: pilot study of a new system.

BACKGROUND: Systems that are used by different organisations to grade the quality of evidence and the strength of recommendations vary. They have different strengths and weaknesses. The GRADE Working Group has developed an approach that addresses key shortcomings in these systems. The aim of this study was to pilot test and further develop the GRADE approach to grading evidence and recommendations. METHODS: A GRADE evidence profile consists of two tables: a quality assessment and a summary of findings. Twelve evidence profiles were used in this pilot study. Each evidence profile was made based on information available in a systematic review. Seventeen people were given instructions and independently graded the level of evidence and strength of recommendation for each of the 12 evidence profiles. For each example judgements were collected, summarised and discussed in the group with the aim of improving the proposed grading system. Kappas were calculated as a measure of chance-corrected agreement for the quality of evidence for each outcome for each of the twelve evidence profiles. The seventeen judges were also asked about the ease of understanding and the sensibility of the approach. All of the judgements were recorded and disagreements discussed. RESULTS: There was a varied amount of agreement on the quality of evidence for the outcomes relating to each of the twelve questions (kappa coefficients for agreement beyond chance ranged from 0 to 0.82). However, there was fair agreement about the relative importance of each outcome. There was poor agreement about the balance of benefits and harms and recommendations. Most of the disagreements were easily resolved through discussion. In general we found the GRADE approach to be clear, understandable and sensible. Some modifications were made in the approach and it was agreed that more information was needed in the evidence profiles. CONCLUSION: Judgements about evidence and recommendations are complex. Some subjectivity, especially regarding recommendations, is unavoidable. We believe our system for guiding these complex judgements appropriately balances the need for simplicity with the need for full and transparent consideration of all important issues.

Generalized cost-effectiveness analysis for national-level priority-setting in the health sector.

Cost-effectiveness analysis (CEA) is potentially an important aid to public health decision-making but, with some notable exceptions, its use and impact at the level of individual countries is limited. A number of potential reasons may account for this, among them technical shortcomings associated with the generation of current economic evidence, political expediency, social preferences and systemic barriers to implementation. As a form of sectoral CEA, Generalized CEA sets out to overcome a number of these barriers to the appropriate use of cost-effectiveness information at the regional and country level. Its application via WHO-CHOICE provides a new economic evidence base, as well as underlying methodological developments, concerning the cost-effectiveness of a range of health interventions for leading causes of, and risk factors for, disease.The estimated sub-regional costs and effects of different interventions provided by WHO-CHOICE can readily be tailored to the specific context of individual countries, for example by adjustment to the quantity and unit prices of intervention inputs (costs) or the coverage, efficacy and adherence rates of interventions (effectiveness). The potential usefulness of this information for health policy and planning is in assessing if current intervention strategies represent an efficient use of scarce resources, and which of the potential additional interventions that are not yet implemented, or not implemented fully, should be given priority on the grounds of cost-effectiveness.Health policy-makers and programme managers can use results from WHO-CHOICE as a valuable input into the planning and prioritization of services at national level, as well as a starting point for additional analyses of the trade-off between the efficiency of interventions in producing health and their impact on other key outcomes such as reducing inequalities and improving the health of the poor.

Systems for grading the quality of evidence and the strength of recommendations I: critical appraisal of existing approaches The GRADE Working Group.

BACKGROUND: A number of approaches have been used to grade levels of evidence and the strength of recommendations. The use of many different approaches detracts from one of the main reasons for having explicit approaches: to concisely characterise and communicate this information so that it can easily be understood and thereby help people make well-informed decisions. Our objective was to critically appraise six prominent systems for grading levels of evidence and the strength of recommendations as a basis for agreeing on characteristics of a common, sensible approach to grading levels of evidence and the strength of recommendations. METHODS: Six prominent systems for grading levels of evidence and strength of recommendations were selected and someone familiar with each system prepared a description of each of these. Twelve assessors independently evaluated each system based on twelve criteria to assess the sensibility of the different approaches. Systems used by 51 organisations were compared with these six approaches. RESULTS: There was poor agreement about the sensibility of the six systems. Only one of the systems was suitable for all four types of questions we considered (effectiveness, harm, diagnosis and prognosis). None of the systems was considered usable for all of the target groups we considered (professionals, patients and policy makers). The raters found low reproducibility of judgements made using all six systems. Systems used by 51 organisations that sponsor clinical practice guidelines included a number of minor variations of the six systems that we critically appraised. CONCLUSIONS: All of the currently used approaches to grading levels of evidence and the strength of recommendations have important shortcomings.

Screening, prevention and treatment of cervical cancer -- a global and regional generalized cost-effectiveness analysis.

The paper calculates regional generalized cost-effectiveness estimates of screening, prevention, treatment and combined interventions for cervical cancer. Using standardised WHO-CHOICE methodology, a cervical cancer model was employed to provide estimates of screening, vaccination and treatment effectiveness. Intervention effectiveness was determined via a population state-transition model (PopMod) that simulates the evolution of a sub-regional population accounting for births, deaths and disease epidemiology. Economic costs of procedures and treatment were estimated, including programme overhead and training costs. In regions characterized by high income, low mortality and high existing treatment coverage, the addition of any screening programme to the current high treatment levels is very cost-effective. However, based on projections of the future price per dose (representing the economic costs of the vaccination excluding monopolistic rents and vaccine development cost) vaccination is the most cost-effective intervention. In regions characterized by low income, low mortality and existing treatment coverage around 50%, expanding treatment with or without combining it with screening appears to be cost-effective or very cost-effective. Abandoning treatment in favour of screening in a no-treatment scenario would not be cost-effective. Vaccination is usually the most cost-effective intervention. Penta or tri-annual PAP smears appear to be cost-effective, though when combined with HPV-DNA testing they are not cost-effective. In regions characterized by low income, high mortality and low treatment levels, expanding treatment with or without adding screening would be very cost-effective. A one off vaccination plus expanding treatment was usually very cost-effective. One-off PAP or VIA screening at age 40 are more cost-effective than other interventions though less effective overall. From a cost-effectiveness perspective, consideration should be given to implementing vaccination (depending on cost per dose and longevity of efficacy) and screening programmes on a worldwide basis to reduce the burden of disease from cervical cancer. Treatment should also be increased where coverage is low.

A financial road map to scaling up essential child health interventions in 75 countries.

OBJECTIVE: To estimate the additional resources required to scale up interventions to reduce child mortality and morbidity within the context of the fourth Millennium Development Goals aim to reduce mortality among children aged<5 years by two-thirds by 2015. METHODS: A costing model was developed to estimate the financial resources needed in 75 countries to scale up priority interventions that address the major causes of mortality among children aged < 5 years, including malnutrition, pneumonia, diarrhoea, malaria and key newborn causes of death such as sepsis. Calculations were made using bottom-up and ingredients-based approaches; this allowed financial costs to be estimated for each intervention, country and year. Costs reflect WHO guidelines on inputs and delivery strategies and encompass the delivery of interventions at community and facility levels. These costs also include programme-specific investments needed at national level and district level. FINDINGS: The scale-up scenario predicts that an additional US$ 52.4 billion will be required for the period 2006-2015. This represents an increase in total per-capita health expenditure in the 75 countries of US$ 0.47 in 2006; this is projected to increase to US$ 1.46 in 2015. Projected costs in 2015 are equivalent to increasing the average total health expenditure from all financial sources in the 75 countries by 8% and raising general government health expenditure by 26% over 2002 levels. (The latest data available at the time of the study were for 2002.) The scale-up scenario indicates that countries with weak health systems may experience difficulties mobilizing enough domestic public funds. CONCLUSIONS: While the results are approximate estimates, they show a substantial investment gap that low- and middle-income countries and their development partners need to bridge to reach the fourth Millennium Development Goal.

Cost effectiveness analysis of strategies for child health in developing countries.

OBJECTIVE: To determine the costs and effectiveness of selected child health interventions-namely, case management of pneumonia, oral rehydration therapy, supplementation or fortification of staple foods with vitamin A or zinc, provision of supplementary food with counselling on nutrition, and immunisation against measles. DESIGN: Cost effectiveness analysis. DATA SOURCES: Efficacy data came from published systematic reviews and before and after evaluations of programmes. For resource inputs, quantities came from literature and expert opinion, and prices from the World Health Organization Choosing Interventions that are Cost Effective (WHO-CHOICE) database, RESULTS: Cost effectiveness ratios clustered in three groups, with fortification with zinc or vitamin A as the most cost effective intervention, and provision of supplementary food and counselling on nutrition as the least cost effective. Between these were oral rehydration therapy, case management of pneumonia, vitamin A or zinc supplementation, and measles immunisation. CONCLUSIONS: On the grounds of cost effectiveness, micronutrients and measles immunisation should be provided routinely to all children, in addition to oral rehydration therapy and case management of pneumonia for those who are sick. The challenge of malnutrition is not well addressed by existing interventions.

Diffusion and utilization of magnetic resonance imaging in Asia.

OBJECTIVES: An assessment of the current status of magnetic resonance imaging (MRI) was undertaken to provide input for future government decisions on the introduction of new technologies in Asia. The objective of the study is to describe and explain the diffusion pattern of this costly technology in several Asian settings. METHODS: Data on the diffusion pattern of MRI for different Asian countries (the Republic of Korea, Malaysia, Indonesia, the Philippines and Thailand) and regions (the cities of Shanghai and Hong Kong in China and the state of Tamil Nadu in India) were obtained from national representatives of professional bodies by using standardized questionnaires for the year 1997-98. In addition, utilization data were collected at the hospital level in three countries before and after the economic crisis in the region. For four countries plus Hong Kong, background information on the legal framework for "big ticket" technologies was collected. RESULTS: Since the introduction of the first MRI in the region in 1987, the number of MRIs has gradually increased both in public and private facilities in Asia. In 1998 the average number of MRI machines installed varied from less than 0.5 machine per million population to more than 5 machines per million population. The maintenance and operating costs, and not the absence of regulation, account for the low number of MRIs in the Philippines and Malaysia. Overall, installed MRIs have low magnetic field strength, vary with respect to brand and type, and are mostly in the private sector and in the urban areas of the region. The diffusion pattern of MRIs in countries of the Asian region appears to follow two types of patterns of diffusion: one set of countries seems to be composed of mostly early adopters and another set of countries appears to be composed mostly of late adopters. CONCLUSIONS: Total number of MRIs per population in this region, though quite small compared to most OECD countries, reflects a higher share of the country's health-resource devoted to expensive high-technology devices. It is difficult to state the appropriate number of MRIs for each country; however, the study shows that there are observable problems in terms of efficiency, equity, and quality of MRI services. The research team proposes a few key recommendations to counteract these problems. Purchasing and regulatory bodies must be empowered with skill and knowledge of health technology assessment. Likewise, the fundamental problems resulting from inefficient and unfair health financing should not be overlooked, so that there is more equitable use of the technology.

Grading quality of evidence and strength of recommendations.

Users of clinical practice guidelines and other recommendations need to know how much confidence they can place in the recommendations. Systematic and explicit methods of making judgments can reduce errors and improve communication. We have developed a system for grading the quality of evidence and the strength of recommendations that can be applied across a wide range of interventions and contexts. In this article we present a summary of our approach from the perspective of a guideline user. Judgments about the strength of a recommendation require consideration of the balance between benefits and harms, the quality of the evidence, translation of the evidence into specific circumstances, and the certainty of the baseline risk. It is also important to consider costs (resource utilisation) before making a recommendation. Inconsistencies among systems for grading the quality of evidence and the strength of recommendations reduce their potential to facilitate critical appraisal and improve communication of these judgments. Our system for guiding these complex judgments balances the need for simplicity with the need for full and transparent consideration of all important issues.