Why cost-effectiveness thresholds for global health donors should differ from thresholds for Ministries of Health (and why it matters).

Healthcare cost-effectiveness analysis is increasingly used to inform priority-setting in low- and middle-income countries and by global health donors. As part of such analyses, cost-effectiveness thresholds are commonly used to determine what is, or is not, cost-effective. Recent years have seen a shift in best practice from a rule-of-thumb 1x or 3x per capita GDP threshold towards using thresholds that, in theory, reflect the opportunity cost of new investments within a given country. In this paper, we observe that international donors face both different resource constraints and opportunity costs compared to national decision-makers. Hence, their perspective on cost-effectiveness thresholds must be different. We discuss the potential implications of distinguishing between national and donor thresholds and outline broad options for how to approach setting a donor-perspective threshold. Further work is needed to clarify healthcare cost-effectiveness threshold theory in the context of international aid and to develop practical policy frameworks for implementation.

The Use of Cost-Effectiveness Thresholds for Evaluating Health Interventions in Low- and Middle-Income Countries From 2015 to 2020: A Review.

OBJECTIVES: Evidence-informed priority setting, in particular cost-effectiveness analysis (CEA), can help target resources better to achieve universal health coverage. Central to the application of CEA is the use of a cost-effectiveness threshold. We add to the literature by looking at what thresholds have been used in published CEA and the proportion of interventions found to be cost-effective, by type of threshold. METHODS: We identified CEA studies in low- and middle-income countries from the Global Health Cost-Effectiveness Analysis Registry that were published between January 1, 2015, and January 6, 2020. We extracted data on the country of focus, type of interventions under consideration, funder, threshold used, and recommendations. RESULTS: A total of 230 studies with a total 713 interventions were included in this review; 1 to 3× gross domestic product (GDP) per capita was the most common type of threshold used in judging cost-effectiveness (84.3%). Approximately a third of studies (34.2%) using 1 to 3× GDP per capita applied a threshold at 3× GDP per capita. We have found that no study used locally developed thresholds. We found that 79.3% of interventions received a recommendation as "cost-effective" and that 85.9% of studies had at least 1 intervention that was considered cost-effective. The use of 1 to 3× GDP per capita led to a higher proportion of study interventions being judged as cost-effective compared with other types of thresholds. CONCLUSIONS: Despite the wide concerns about the use of 1 to 3× GDP per capita, this threshold is still widely used in the literature. Using this threshold leads to more interventions being recommended as "cost-effective." This study further explore alternatives to the 1 to 3× GDP as a decision rule.

Recalibrating the notion of modelling for policymaking during pandemics.

COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and development partners. To understand the limitations of existing COVID-19 disease models (primarily from high income countries) and how they could be adequately support decision-making in LMICs, a desk review of modelling experience during the COVID-19 and past disease outbreaks, two online surveys, and regular online consultations were held among the collaborators. Three key recommendations from CMCC include: A 'fitness-for-purpose' flowchart, a tool that concurrently walks policymakers (or their advisors) and modellers through a model selection and development process. The flowchart is organised around the following: policy aims, modelling feasibility, model implementation, model reporting commitment. Holmdahl and Buckee (2020) A 'reporting standards trajectory', which includes three gradually increasing standard of reports, 'minimum', 'acceptable', and 'ideal', and seeks collaboration from funders, modellers, and decision-makers to enhance the quality of reports over time and accountability of researchers. Malla et al. (2018) A framework for "collaborative modelling for effective policy implementation and evaluation" which extends the definition of stakeholders to funders, ground-level implementers, public, and other researchers, and outlines how each can contribute to modelling. We advocate for standardisation of modelling processes and adoption of country-owned model through iterative stakeholder participation and discuss how they can enhance trust, accountability, and public ownership to decisions.

Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review.

BACKGROUND: How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes. METHODS: We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed. RESULTS: The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage. CONCLUSION: The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.

The journey to UHC: how well are vertical programmes integrated in the health benefits package? A scoping review.

BACKGROUND: Countries are recommended to progressively work towards universal health coverage (UHC), and to make explicit choices regarding the expansion of priority services. However, there is little guidance on how to manage the inclusion of vertical programmes, funded by external partners, in health benefits packages (HBP) in low and middle-income countries (LMICs). OBJECTIVE: We conducted a scoping review to map the inclusion of six vertical programmes (HIV, tuberculosis, malaria, maternal and child health, contraceptives, immunisation) in 26 LMICs. METHODS: We identified 26 LMICs with an HBP that was not aspirational (eg, with evidence of implementation or funding). For each HBP, we collected information on the corresponding UHC scheme, health financing at the time of establishment, revisions since inception and entitlements. For each vertical programme, we developed a list of tracer interventions based on the Disease Control Priorities 3 and the 100 Core Health Indicators List. We then used this list of tracer interventions to map the coverage of the six vertical programmes. RESULTS: The review shows that there is no common starting point for countries embarking into UHC. Some HBPs were almost three decades old. Whole package revisions are rare. The inclusion of vertical programme does not follow a given pattern based on health financing indicators or country's income group. Maternal child health services are the most often included and family planning the least. Six countries in our sample covered all vertical programmes, while one covered only one of six. CONCLUSIONS: This review has shown that there has been a long history of countries facing this question and we have provided the first mapping of inclusion of vertical programmes in UHC. The results of the mapping can inform decisions in countries embarking in UHC.

Measuring Health Outcomes in HIV: Time to Bring in the Patient Experience.

Introduction: Over the past decade, the global response to HIV has led to a reduction in the number of new infections, and a decrease in associated mortality. Yet, the number of people living with HIV (PLHIV) is high, with an estimated 38 million infected worldwide. As HIV shifts from being an acute terminal illness to a chronic condition, evaluating programmatic responses to HIV with sole reliance on biological markers (such as viral load or CD4 cell count) as proxies for patient health may no longer be suitable. HIV affects the lives of those infected in myriad ways which should be reflected in programme evaluations by measuring health-related quality of life, in addition to biomarkers. Discussion: In this commentary we argue that there is a pressing need to review how a "good" health outcome is defined and measured in light of care systems moving towards value-based frameworks that measure value in terms of the actual health outcomes achieved (rather than processes of care), global response shifting to providing long-term care for PLHIV in the community, and integrating HIV as part of universal health coverage plans. Efforts should be directed towards validating generic and disease specific patient-reported measures of PLHIV, to identify the most suitable tools. Such efforts will ensure that patient experience is appropriately captured, especially to be used in programme or economic evaluations. Conclusions: It is only by recognising and measuring the full range of health, mental and social outcomes related to the disease that the health status of PLHIV can be fully understood.

What next after GDP-based cost-effectiveness thresholds?

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.

How can we evaluate the cost-effectiveness of health system strengthening? A typology and illustrations.

Health interventions often depend on a complex system of human and capital infrastructure that is shared with other interventions, in the form of service delivery platforms, such as healthcare facilities, hospitals, or community services. Most forms of health system strengthening seek to improve the efficiency or effectiveness of such delivery platforms. This paper presents a typology of ways in which health system strengthening can improve the economic efficiency of health services. Three types of health system strengthening are identified and modelled: (1) investment in the efficiency of an existing shared platform that generates positive benefits across a range of existing interventions; (2) relaxing a capacity constraint of an existing shared platform that inhibits the optimization of existing interventions; (3) providing an entirely new shared platform that supports a number of existing or new interventions. Theoretical models are illustrated with examples, and illustrate the importance of considering the portfolio of interventions using a platform, and not just piecemeal individual analysis of those interventions. They show how it is possible to extend principles of conventional cost-effectiveness analysis to identify an optimal balance between investing in health system strengthening and expenditure on specific interventions. The models developed in this paper provide a conceptual framework for evaluating the cost-effectiveness of investments in strengthening healthcare systems and, more broadly, shed light on the role that platforms play in promoting the cost-effectiveness of different interventions.

Resource allocation processes at multilateral organizations working in global health.

International institutions provide well over US$10 billion in development assistance for health (DAH) annually and between 1990 and 2014, DAH disbursements totaled $458 billion but how do they decide who gets what, and for what purpose? In this article, we explore how allocation decisions were made by the nine convening agencies of the Equitable Access Initiative. We provide clear, plain language descriptions of the complete process from resource mobilization to allocation for the nine multilateral agencies with prominent agendas in global health. Then, through a comparative analysis we illuminate the choices and strategies employed in the nine international institutions. We find that resource allocation in all reviewed institutions follow a similar pattern, which we categorized in a framework of five steps: strategy definition, resource mobilization, eligibility of countries, support type and funds allocation. All the reviewed institutions generate resource allocation decisions through well-structured and fairly complex processes. Variations in those processes seem to reflect differences in institutional principles and goals. However, these processes have serious shortcomings. Technical problems include inadequate flexibility to account for or meet country needs. Although aid effectiveness and value for money are commonly referenced, we find that neither performance nor impact is a major criterion for allocating resources. We found very little formal consideration of the incentives generated by allocation choices. Political issues include non-transparent influence on allocation processes by donors and bureaucrats, and the common practice of earmarking funds to bypass the normal allocation process entirely. Ethical deficiencies include low accountability and transparency at international institutions, and limited participation by affected citizens or their representatives. We find that recipient countries have low influence on allocation processes themselves, although within these processes they have some influence in relatively narrow areas.