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BACKGROUND: Although Ghana is lauded for its National Health Insurance Scheme (NHIS), concerns exist about the scheme's functioning and sustainability. An often-cited issue-contributing to the scheme's decreasing membership, long-standing financial deficit, and frequent out-of-pocket payments among members-is the large benefits package (BP). While, on paper, the BP covers over 95% of the conditions occurring in Ghana, its design was not informed by any budget analysis, nor any systematic prioritization of interventions. This paper aims to provide evidence-based input into ongoing discussions regarding a review of the NHIS benefits package. METHODS: An existing analytic framework is used to calculate net health benefit (NHB) for a range of interventions in order to assess their cost-effectiveness and enable the prioritization of 'best buys'. The framework is expanded upon by incorporating concerns for financial protection, and practical feasibility, as well as the political economy challenges of disinvesting in currently funded activities. Five different options for the benefits package, each based on policy discourse in Ghana's health sector, are presented and evaluated. RESULTS: Implementing all interventions for which data was available to 100% of the population in need was estimated to cost GHâµ4323 million (US$994 million), while the available NHIS budget was only GHâµ970 million (US$223 million). Options for the benefits package that focussed on cost-effectiveness and primary care provision achieved the best health outcomes, while options reflecting the status quo and allowing for co-payments included a higher number of healthcare interventions. Apart from the package option focussing on primary care, all packages were faced with physician shortages. CONCLUSIONS: Current funding to the NHIS is insufficient to provide the historical benefits package, which promises to cover over 95% of disease conditions occurring in Ghana, to the total population. Shifting the NHIS focus from intervention coverage to population coverage is likely to lead to better health outcomes. A primary care package may be most feasible in the short-term, though additional physicians should be trained to provide higher-level care that is highly cost-effective, such as emergency neonatal care.
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Setting out a health benefits package (HBP) of interventions to be prioritised for funding is an important step towards achieving universal health coverage in low and middle income countries. The 3rd version of the Disease Control Priorities (DCP3) database, and other similar databases, aim to establishing a single point of reference ("one stop shop") for cost effectiveness evidence to inform HBP design and other policy making. We reflect upon our experiences in using DCP3 for HBP design and offer suggestions for improving the future reporting of cost-effectiveness evidence. We appraise DCP3 based on generalisability, level of detail, and accessibility. We find that DCP and similar initiatives should be commended for the systematic assessment of a vast array of cost-effectiveness studies-the magnitude of such an endeavour is impressive in its own right. However, there are flaws. In future, providing disaggregated estimates of costs and effects, quantifying uncertainty, and systematically assessing the context in which estimates apply would make this evidence more useful for decision makers.
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OBJECTIVES: Social preference values of health states are a fundamental input for the preparation of studies in health economics. Several countries have undertaken studies to obtain these values. Our objective was to conduct a structured and systematic literature review of articles that calculates this set of representative values at the national level in low- and middle-income countries (LMICs). METHODS: In this systematic review, we searched the Embase, MEDLINE, Ovid, SciELO, and LILACS databases, among others, for studies published up to June 2022 that estimated nationally representative health states preferences values for LMICs. We summarized the information qualitatively and assessed the risk of bias in each article using the consensus-based standards for selecting health measurement instruments checklist tool. RESULTS: Of the 23 663 articles identified, 35 studies were eligible for inclusion. The studies were from 19 countries in Latin-American, Europe, Africa, and Asia. No studies were found for low-income countries. The most commonly applied generic instrument for measuring health-related quality of life was the 5-level version of EQ-5D and 3-level version of EQ-5D. Preference was given to face-to-face administration of these instruments. The sociodemographic variables with the most significant negative correlation versus utility were older adults, marital status (widowed or divorced), and low educational level and income. CONCLUSIONS: Worldwide, there have been few studies that have estimated, in a nationally representative manner, the social values of health states preferences in LMICs. We consider the local estimate of this set of societal values relevant for any society to improve decision making in allocating resources in health budgets.
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Países em Desenvolvimento , Qualidade de Vida , Humanos , Idoso , Renda , Europa (Continente) , ÁfricaRESUMO
OBJECTIVE: Empirical estimates of the impact of healthcare expenditure on health outcome measures may inform the cost-effectiveness threshold (CET) for guiding funding decisions. This study aims to systematically review studies that estimated this, summarize and compare the estimates by country income level. METHODS: We searched PubMed, Scopus, York Research database, and [anonymized] for Reviews and Dissemination database from inception to 1 August 2023. For inclusion, a study had to be an original article, estimating the impact of healthcare expenditure on health outcome measures at a country level, and presented estimates, in terms of cost per quality-adjusted life year (QALY) or disability-adjusted life year (DALY). RESULTS: We included 18 studies with 385 estimates. The median (range) estimates were PPP$ 11,224 (PPP$ 223 - PPP$ 288,816) per QALY gained and PPP$ 5,963 (PPP$ 71 - PPP$ 165,629) per DALY averted. As ratios of Gross Domestic Product per capita (GDPPC), these estimates were 0.376 (0.041-182.840) and 0.318 (0.004-37.315) times of GDPPC, respectively. CONCLUSIONS: The commonly used CET of GDPPC seems to be too high for all countries, but especially low-to-middle-income countries where the potential health losses from misallocation of the same money are greater. REGISTRATION: The review protocol was published and registered in PROSPERO (CRD42020147276).
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Atenção à Saúde , Gastos em Saúde , Humanos , Análise Custo-Benefício , Anos de Vida Ajustados por Qualidade de VidaRESUMO
Despite making remarkable strides in improving health outcomes, Malawi faces concerns about sustaining the progress achieved due to limited fiscal space and donor dependency. The imperative for efficient health spending becomes evident, necessitating strategic allocation of resources to areas with the greatest impact on mortality and morbidity. Health benefits packages hold promise in supporting efficient resource allocation. However, despite defining these packages over the last two decades, their development and implementation have posed significant challenges for Malawi. In response, the Malawian government, in collaboration with the Thanzi la Onse Programme, has developed a set of tools and frameworks, primarily based on cost-effectiveness analysis, to guide the design of health benefits packages likely to achieve national health objectives. This review provides an overview of these tools and frameworks, accompanied by other related analyses, aiming to better align health financing with health benefits package prioritization. The paper is organized around five key policy questions facing decision-makers: (i) What interventions should the health system deliver? (ii) How should resources be allocated geographically? (iii) How should investments in health system inputs be prioritized? (iv) How should equity considerations be incorporated into resource allocation decisions? and (v) How should evidence generation be prioritized to support resource allocation decisions (guiding research)? The tools and frameworks presented here are intended to be compatible for use in diverse and often complex healthcare systems across Africa, supporting the health resource allocation process as countries pursue Universal Health Coverage.
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BACKGROUND: Saudi Arabia's Vision 2030 aims to reform health care across the Kingdom, with health technology assessment being adopted as one tool promising to improve the efficiency with which resources are used. An understanding of the opportunity costs of reimbursement decisions is key to fulfilling this promise and can be used to inform a cost-effectiveness threshold. This paper is the first to provide a range of estimates of this using existing evidence extrapolated to the context of Saudi Arabia. METHODS AND MATERIALS: We use four approaches to estimate the marginal cost per unit of health produced by the healthcare system; drawing from existing evidence provided by a cross-country analysis, two alternative estimates from the UK context, and based on extrapolating a UK estimate using evidence on the income elasticity of the value of health. Consequences of estimation error are explored. RESULTS: Based on the four approaches, we find a range of SAR 42,046 per QALY gained (48% of GDP per capita) to SAR 215,120 per QALY gained (246% of GDP per capita). Calculated potential central estimates from the average of estimated health gains based on each source gives a range of SAR 50,000-75,000. The results are in line with estimates from the emerging literature from across the world. CONCLUSION: A cost-effectiveness threshold reflecting health opportunity costs can aid decision-making. Applying a cost-effectiveness threshold based on the range SAR 50,000 to 75,000 per QALY gained would ensure that resource allocation decisions in healthcare can in be informed in a way that accounts for health opportunity costs. LIMITATIONS: A limitation is that it is not based on a within-country study for Saudi Arabia, which represents a promising line of future work.
Healthcare in Saudi Arabia is undergoing wide-ranging reform through Saudi Arabia's Vision 2030. One aim of these reforms is to ensure that money spent on healthcare generates the most improvement in population health possible. To do this requires understanding the trade-offs that exist: funding one pharmaceutical drug means that same money is not available to fund another pharmaceutical drug. This is relevant whether the new drug would be funded from within the existing budget for healthcare or from an expansion of it. If the drugs apply to the same patient population and have the same price, the question is simply, "which one generates more health?" In reality, we need to compare pharmaceutical drugs for different diseases, patient populations, and at a range of potential prices to understand whether the drug in question would generate more health per riyal spent than what is currently funded by the healthcare system. This paper provides the first estimates of the amount of health, measured in terms of quality adjusted life years (QALYs), generated by the Saudi Arabian healthcare system. We find that the healthcare system generates health at a rate of one QALY produced for every 50,00075,000 riyals spent (5886% of GDP per capita). Using the range we estimate to inform cost-effectiveness threshold can aid decision-making.
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Atenção à Saúde , Custos de Cuidados de Saúde , Humanos , Análise Custo-Benefício , Anos de Vida Ajustados por Qualidade de Vida , Arábia SauditaRESUMO
This scoping review aims to identify and critically appraise published economic evaluations of self-help group (SHG) interventions in low- and middle-income countries (LMICs) that seek to improve health and potentially also non-health outcomes. Through a systematic search of MEDLINE ALL (Ovid), EMBASE Ovid, PsychINFO, EconLit (Ovid) and Global Index Medicus, we identified studies published between 2014 and 2020 that were based in LMICs, included at least a health outcome, estimated intervention costs and reported the methods used. We critically analysed whether the methods employed can meaningfully inform decisions by ministries of health and other sectors, including donors, regarding whether to fund such interventions, and prioritized the aspects of evaluations that support decision-making and cross-sectoral decision-making especially. Nine studies met our inclusion criteria. Randomized controlled trials were the most commonly used vehicle to collect data and to establish a causal effect across studies. While all studies clearly stated one or more perspectives justifying the costs and effects that are reported, few papers clearly laid out the decision context or the decision maker(s) informed by the study. The latter is required to inform which costs, effects and opportunity costs are relevant to the decision and should be included in the analysis. Costs were typically reported from the provider or health-care sector perspective although other perspectives were also employed. Four papers reported outcomes in terms of a generic measure of health. Contrary to expectation, no studies reported outcomes beyond health. Our findings suggest limitations in the extent to which published studies are able to inform decision makers around the value of implementing SHG interventions in their particular context. Funders can make better informed decisions when evidence is presented using a cross-sectoral framework.
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Economic evaluation of health-related projects requires principles and methods to address the various trade-offs that need to be made between costs and benefits, across sectors and social objectives, and over time. Existing guidelines for economic evaluation in low- and middle-income countries embed implicit assumptions about expected changes in the marginal cost per unit of health produced by the healthcare sector, the consumption value of health and the appropriate discount rates for health and consumption. Separating these evaluation parameters out requires estimates for each country over time, which have hitherto been unavailable. We present a conceptual economic evaluation framework that aims to clarify the distinct roles of these different evaluation parameters in evaluating a health-related project. Estimates for each are obtained for each country and in each time period, based on available empirical evidence. Where existing estimates are not available, for future values of the marginal cost per unit of health produced by the healthcare sector, new estimates are obtained following a practical method for obtaining projected values. The framework is applied to a simple, hypothetical, illustrative example, and the results from our preferred approach are compared against those obtained from other approaches informed by the assumptions implicit within existing guidelines. This exposes the consequences of applying such assumptions, which are not supported by available evidence, in terms of potentially sub-optimal decisions. In general, we find that applying existing guidelines as done in conventional practice likely underestimates the value of health-related projects on account of not allowing for expected growth in the marginal cost per unit of health produced by the healthcare sector.
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Países em Desenvolvimento , Renda , Análise Custo-Benefício , Serviços de Saúde , HumanosRESUMO
Despite being a fundamental tenet of economic analysis there is a lack of clarity regarding the relevance of opportunity costs to cost-effectiveness analysis for health technology assessment. We argue that this is due, in part, to the importance of the decision context in understanding the nature of opportunity costs. Taking the example of the National Institute of Health and Care Excellence (NICE) on behalf of the National Health Service (NHS) in England and Wales, we explore the implications of existing discrepancies between policy thresholds and emerging empirical evidence of health opportunity costs. In particular, we consider analysts communicating the results of cost-effectiveness analysis, and recommend that analysts provide analysis according to both the policy threshold and the latest empirical evidence until the discrepancies are better understood or resolved. A number of conceptually related, but distinct, issues are discussed and clarified.
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Medicina Estatal , Avaliação da Tecnologia Biomédica , Análise Custo-Benefício , Inglaterra , Custos de Cuidados de Saúde , HumanosRESUMO
BACKGROUND: The marginal productivity of a country's healthcare system refers to the health gains produced per unit change in the level of spending. In budget-constrained settings, this metric reflects the opportunity cost, in terms of health gains forgone, of committing additional or existing resources to alternative uses within the healthcare system. It can therefore assist in evidence-based decisions on whether different interventions represent good value for money. OBJECTIVE: The aim of this paper was to estimate the marginal productivity of the Indonesian healthcare system using subnational data, and to use this to inform health opportunity costs in the country. METHODS: We define a dynamic health production function to model the stream of effects of current and prior public health spending decisions on population under-five mortality. To estimate the model, we use data from the 33 Indonesian provinces for the 2004-2012 period. The estimated elasticity is then translated into gains in terms of cost per DALY (disability-adjusted life-year) averted. We use dynamic panel data methods to address potential endogeneity issues in the model. RESULTS: Our base-case estimates suggest that a 1% expansion in the level of health spending reduces under-five mortality by 0.38% (95% CI 0.00-0.76), which translates into a cost of averting one DALY of $235 (2019 US$). CONCLUSION: With Indonesia aiming for universal health coverage, our results support these efforts by highlighting the associated benefits resulting from increases in public health expenditure and have the potential to inform the decision-making process about a suitable locally relevant cost-effectiveness threshold.
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Atenção à Saúde , Gastos em Saúde , Humanos , Anos de Vida Ajustados por Qualidade de Vida , Indonésia , Análise Custo-BenefícioRESUMO
Many health technology assessment committees have an explicit or implicit reference value (often referred to as a 'threshold') below which new health technologies or interventions are considered value for money. The basis for these reference values is unclear but one argument is that it should be based on the health opportunity costs of funding decisions. Empirical estimates of the marginal cost per unit of health produced by a healthcare system have been proposed to capture the health opportunity costs of new funding decisions. Based on a systematic search, we identified eight studies that have sought to estimate a reference value through empirical estimation of the marginal cost per unit of health produced by a healthcare system for England, Spain, Australia, The Netherlands, Sweden, South Africa and China. We review these eight studies to provide an overview of the key methodological approaches taken to estimate the marginal cost per unit of health produced by the healthcare system with the aim to help inform future estimates for additional countries. The lead author for each of these papers was invited to contribute to the current paper to ensure all the key methodological issues encountered were appropriately captured. These included consideration of the key variables required and their measurement, accounting for endogeneity of spending to health outcomes, the inclusion of lagged spending, discounting and future costs, the use of analytical weights, level of disease aggregation, expected duration of health gains, and modelling approaches to estimating mortality and morbidity effects of health spending. Subsequent research estimates for additional countries should (1) carefully consider the specific context and data available, (2) clearly and transparently report the assumptions made and include stakeholder perspectives on their appropriateness and acceptability, and (3) assess the sensitivity of the preferred central estimate to these assumptions.
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Atenção à Saúde , Avaliação da Tecnologia Biomédica , Tecnologia Biomédica , China , Análise Custo-Benefício , Inglaterra , HumanosRESUMO
BACKGROUND: Current health economic analysis guidelines emphasize the importance of using nationally appropriate cost and valuation inputs. However, some countries lack national data, and some analyses focus on interventions with costs and benefits at regional or global scales. METHODS: Recognizing the need for better estimates of appropriate values for application at these levels than those used in the past, we characterize population-weighted dollar per disability-adjusted life year (DALY) averted by World Bank Income Level based on available national estimates of the marginal productivity of the healthcare system. RESULTS: The defaults suggested here reflect health opportunity costs across countries more consistent with existing evidence than those previously used or recommended. As countries change income levels and healthcare spending, and as additional or updated marginal productivity of healthcare expenditure estimates become available, we expect the defaults to change. CONCLUSION: The best option for informing decisions around resource allocation in health care such that they improve health outcomes overall remains the use of time-appropriate country-specific estimates of the marginal productivity of the healthcare system. Instead of single, time-invariant defaults, health economists should seek to develop valuation inputs that better account for health opportunity costs and do so over time.
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Atenção à Saúde/economia , Custos de Cuidados de Saúde/estatística & dados numéricos , Gastos em Saúde/estatística & dados numéricos , Avaliação de Resultados em Cuidados de Saúde/métodos , Análise Custo-Benefício , Humanos , Anos de Vida Ajustados por Qualidade de Vida , Alocação de Recursos/economiaRESUMO
Health benefits packages (HBPs) are increasingly used in many countries to guide spending priorities on the path towards universal health coverage. Their design is, however, informed by an uncertain evidence base but research funds available to address this are limited. This gives rise to the question of which piece of research relating to the cost-effectiveness of interventions would most contribute to improving resource allocation. We propose to incorporate research prioritisation as an integral part of HBP design. We have, therefore, developed a framework and a freely available companion stand-alone tool, to quantify in terms of net disability-adjusted life-years (DALYs) averted, the value of research for the interventions considered for inclusion in a package. Using the tool, the framework can be implemented using sensitivity analysis results typically reported in cost-effectiveness studies. To illustrate the framework, we applied the tool to the evidence base that informed the Malawi Health Sector Strategic Plan 2017-2022. Out of 21 interventions considered, 8 investment decisions were found to be uncertain and three showed strong potential for research to generate large health gains: 'male circumcision', 'community-management of acute malnutrition in children' and 'isoniazid preventive therapy in HIV +individuals', with a potential to avert up to 65 762, 36 438 and 20 132 net DALYs, respectively. Our work can help set research priorities in resource-constrained settings so that research funds are invested where they have the largest potential to impact on the population health generated via HBPs.
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Atenção à Saúde , Cobertura Universal do Seguro de Saúde , Criança , Análise Custo-Benefício , Humanos , Malaui , MasculinoRESUMO
PURPOSE: Evaluating whether a new health technology provides good value for money requires an assessment of its opportunity cost. If the opportunity cost of the new health technology exceeds the benefits, however measured, a net loss is produced. Value frameworks using economic evaluation methods have been developed to guide the assessment of the value of new technologies within health care in response to rising spending. However, few explicitly consider health opportunity costs and fewer still base health opportunity costs on empirical estimates. This may partly be due to the dearth of estimates available, with only a handful of countries having estimates based on within-country data. To fill this gap, this study provides estimates of cost per disability-adjusted life year (DALY) averted for 33 high-income countries and the remaining Organization for Economic Cooperation and Development (OECD) and BRIICS countries (Brazil, Russia, India, Indonesia, China and South Africa). METHODS: Cost per DALY averted for each country was based on estimated elasticities of the health effects of changes in expenditure on health outcomes from applying an existing published econometric model that uses cross-country data to an expanded dataset and other existing elasticities drawn from selected UK within-country studies to country-level data on health expenditure, demographic characteristics, and burden of ill health. To provide a comprehensive picture of the state of research around empirical estimates of health opportunity costs for these countries, results from this study are reported against previously published estimates of cost per quality-adjusted life year (QALY) gained for the same countries. FINDINGS: All but one of the ranges estimated fall below 3× the gross domestic product (GDP) per capita, the upper end of the widely applied range of 1-3× GDP per capita. The range of estimates based on applying an existing published econometric model that uses cross-country data to an expanded dataset are higher than when cost per DALY averted is calculated from other existing elasticities of the health effects of changes in expenditure drawn from selected UK within-country studies. They also tend to be higher than published estimates of cost per QALY gained. IMPLICATIONS: This study provides placeholder cost per DALY averted estimates that reflect health opportunity costs for 33 high-income countries and the remaining OECD and BRIICS countries. These estimates can be used to estimate the health opportunity costs of government health care expenditure until country-specific health opportunity cost are estimated using within-country data.
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Tomada de Decisões , Modelos Econométricos , Análise Custo-Benefício , Custos de Cuidados de Saúde , Gastos em Saúde , Humanos , Anos de Vida Ajustados por Qualidade de VidaRESUMO
Universal Health Coverage (UHC) has become a key goal of health policy in many developing countries. However, implementing UHC poses tough policy choices about: what treatments to provide (the depth of coverage); to what proportion of the population (the breadth of coverage); at what price to patients (the height of coverage). This paper uses a theoretical mathematical programming model to derive analytically the optimal balance between the range of services provided and the proportion of the population covered under UHC, using the general principles of cost-effectiveness analysis. In contrast to most CEA, the model allows for variations in both the costs of provision and the social benefits of treatments, depending on the deprivation level of the population. We illustrate empirically the optimal trade-off between the size of the benefits package and the proportion of the population securing access to each treatment for a hypothetical East African country, based on WHO data on the costs and benefits of treatments at different coverage levels. We begin with a scenario allowing coverage levels to vary, then apply differential equity weights to the benefits of coverage, and finally illustrate a scenario where interventions are either provided at 95% coverage or not at all (as is usually done in health benefits package design) for comparison. The results present the optimal trade-off between the social benefits of pursuing full population coverage, at the expense of expanding the benefits package for 'easier to reach' populations.
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Cobertura do Seguro/organização & administração , Modelos Teóricos , Cobertura Universal do Seguro de Saúde/economia , Algoritmos , Análise Custo-Benefício , Saúde Global , Política de Saúde , HumanosRESUMO
INTRODUCTION: Estimating the value of providing effective healthcare interventions in a country requires an assessment of whether the improvement in health outcomes they offer exceeds the improvement in health that would have been possible if the resources required had, instead, been made available for other healthcare activities in that country. This potential alternative use of the same resources represents the health opportunity cost of providing the intervention. Without such assessments, there is a danger that blanket recommendations made by international organisations will lead to the adoption of healthcare interventions that are not cost effective in some countries, even given existing donor mechanisms intended to support their affordability. METHODS: We assessed the net health impact to 46 Gavi-eligible countries of achieving one of the WHO's proposed 90-70-90 targets for cervical cancer elimination, which includes 90% coverage of human papillomavirus (HPV) vaccination among girls by 15 years of age, using published estimates of the expected additional benefits and costs in each country and estimates of the marginal productivity of each healthcare system. We calculated the maximum price each country could afford to pay for HPV vaccination to be cost effective by assessing the net health impact that would be expected to be generated at different potential prices. RESULTS: At Gavi negotiated prices, HPV vaccination offers net health benefits across most Gavi-eligible countries included in this study. However, if Gavi-eligible countries faced the average price faced by non-Gavi eligible countries, providing HPV vaccination would result in reduced overall population health in most countries. CONCLUSION: Estimates of the net health impact of providing a healthcare intervention can be used to assess the benefit (or lack of) to countries of adhering to global guidance, inform negotiations with donors, as well as pricing negotiations and the value of developing new healthcare interventions.
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Alphapapillomavirus , Infecções por Papillomavirus , Vacinas contra Papillomavirus , Países em Desenvolvimento , Feminino , Humanos , Infecções por Papillomavirus/epidemiologia , Infecções por Papillomavirus/prevenção & controle , VacinaçãoRESUMO
BACKGROUND: Health technology assessment has been increasingly used in China, having been legally mandated in 2019, to inform reimbursement decisions and price negotiations between the National Healthcare Security Administration and pharmaceutical companies around the price of new pharmaceuticals. The criteria currently used to judge cost effectiveness and inform pricing negotiations, 3 × GDP per capita, is based on the rule of thumb previously recommended by the World Health Organization rather than an estimate based on an empirical assessment of health opportunity costs. OBJECTIVE: The objective of this study was to inform a cost-effectiveness threshold for health technology assessment in China that accounts for health opportunity cost. METHODS: The elasticity of health outcomes with respect to health expenditure was estimated using variations across 30 provincial-level administrative divisions in 2017 controlling for a range of other factors and using an instrumental variable approach to account for endogeneity to assess robustness of results. The estimated elasticity was then used to calculate the cost per disability-adjusted life-year (DALY) averted by variations in Chinese health expenditure at the margin. RESULTS: The range estimated from this study, 27,923-52,247 (2017 RMB) (central estimate 37,446) per DALY averted or 47-88% of GDP per capita (central estimate 63%), shows that a cost per DALY averted cost-effectiveness threshold that reflects health opportunity costs is below 1 × GDP per capita. CONCLUSION: Our results suggest that the current cost-effectiveness threshold used in China is too high; continuing to use it risks decisions that reduce overall population health.
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Custos de Cuidados de Saúde , Avaliação da Tecnologia Biomédica , China , Análise Custo-Benefício , Humanos , Anos de Vida Ajustados por Qualidade de VidaRESUMO
Public payers around the world are increasingly using cost-effectiveness thresholds (CETs) to assess the value-for-money of an intervention and make coverage decisions. However, there is still much confusion about the meaning and uses of the CET, how it should be calculated, and what constitutes an adequate evidence base for its formulation. One widely referenced and used threshold in the last decade has been the 1-3 GDP per capita, which is often attributed to the Commission on Macroeconomics and WHO guidelines on Choosing Interventions that are Cost Effective (WHO-CHOICE). For many reasons, however, this threshold has been widely criticised; which has led experts across the world, including the WHO, to discourage its use. This has left a vacuum for policy-makers and technical staff at a time when countries are wanting to move towards Universal Health Coverage . This article seeks to address this gap by offering five practical options for decision-makers in low- and middle-income countries that can be used instead of the 1-3 GDP rule, to combine existing evidence with fair decision-rules or develop locally relevant CETs. It builds on existing literature as well as an engagement with a group of experts and decision-makers working in low, middle and high income countries.
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The primary focus of this paper is to offer guidance on the analysis of time streams of effects that a project may have so that they can be discounted appropriately. This requires a framework that identifies the common parameters that need to be assessed, whether conducting cost-effectiveness or benefit-cost analysis. The quantification and conversion of the time streams of different effects into their equivalent health, health care cost or consumption effects avoids embedding multiple arguments in discounting policies. This helps to identify where parameters are likely to differ in particular contexts, what type of evidence would be relevant, what is currently known and how this evidence might be strengthened. The current evidence available to support the assessment of the key parameters is discussed and possible estimates and default assumptions are suggested. Reporting the results in an extensive way is recommended. This makes the assessments required explicit so the impact of alternative assumptions can be explored and analysis updated as better estimates evolve. Some projects will have effects across different countries where some or all of these parameters will differ. Therefore, the net present value of a project will be the sum of the country specific net present values rather than the sum of effects across countries discounted at some common rate.
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The economic evaluation of healthcare interventions requires an assessment of whether the improvement in health outcomes they offer exceeds the improvement in health that would have been possible if the additional resources required had, instead, been made available for other healthcare activities. Therefore, some assessment of these health opportunity costs is required if the best use is to be made of the resources available for healthcare. This paper provides a framework for generating country-specific estimates of cost per disability-adjusted life year (DALY) averted 'thresholds' that reflect health opportunity costs. We apply estimated elasticities on mortality, survival, morbidity and a generic measure of health, DALYs, that take account of measures of a country's infrastructure and changes in donor funding to country-specific data on health expenditure, epidemiology and demographics to determine the likely DALYs averted from a 1% change in expenditure on health. The resulting range of cost per DALY averted 'threshold' estimates for each country that represent likely health opportunity costs tend to fall below the range previously suggested by WHO of 1-3× gross domestic product (GDP) per capita. The 1-3× GDP range and many other previous and existing recommendations about which interventions are cost-effective are not based on an empirical assessment of the likely health opportunity costs, and as a consequence, the health effects of changes in health expenditure have tended to be underestimated, and there is a risk that interventions regarded as cost-effective reduce rather than improve health outcomes overall.