Introduction
To achieve Universal Health Coverage of their populations1 using a limited resource envelope, governments of low- and middle-income countries (LMIC) inevitably must make hard choices when selecting the healthcare interventions that their population has access to, free-of-charge, through publicly pooled funds.
Recent advances in methods to identify the set of interventions to be provided, that constitute what is known as a Health Benefits Package (HBP), recommend explicit consideration of the population net health effect (pNHE) associated with including in the package each intervention under consideration.2 3 This metric accounts for both the health expected to be generated by the intervention, and the losses in health associated with funding the intervention rather than addressing other healthcare priorities. The assessment of the pNHE of relevant interventions is informed by data coming from a range of sources. National surveys and bottleneck analyses are often used to assess population needs and interventions’ capacity to cover them, whereas estimates of per patient cost and health benefit typically come from published cost-effectiveness analyses.
Cost and health benefit estimates are, however, uncertain, due to limited data availability on key quantities such as drug and programme costs, clinical effectiveness and its long-term implications for patients’ quality of life and life expectancy.3 4 Approaches to quantifying uncertainty in the cost-effectiveness of interventions considered for inclusion in HBPs have been proposed and used, such as stochastic league tables whereby interventions are ranked by their probability of being cost-effective.5 These approaches, however, fall short of guiding policy makers as to how they should respond to uncertainty, that is whether this uncertainty matters to the resource allocation process and should be addressed by funding further research. As a result, research strategies may not be aligned with the evidential needs of HBPs. We, therefore, propose a framework to support the concomitant design of HBPs and research prioritisation, based on an assessment of where additional evidence would be most valuable in generating health gains.
Our framework builds on value of information (VOI) methods6 to quantify the pNHE of reducing uncertainty through further research. The contribution of our work is to tailor the application of VOI methods to the evidence base that typically informs HBPs, namely secondary cost-effectiveness data.
VOI methods or other methods similarly grounded in statistical decision theory, are often used to determine how much one may lose out by taking a decision with uncertain outcomes and therefore how much benefit there is to reducing uncertainty via research.6 7 Their application usually requires estimates of uncertainty around outcomes, or around the quantities that drive them, to produce probabilistic simulations of the values that outcomes could take.8 9 This data is, however, not readily available from published cost-effectiveness studies that overwhelmingly constitute the evidence base informing HBPs. The high burden of information inputs and technical knowledge associated with the application of statistical decision theory methods have impeded the use of VOI methods for aligning research funds allocation with evidential requirements.
We have, therefore, developed a freely available tool—the Value of Information for Health Benefits Package design (VOI-HBP) tool—that addresses these two hurdles and estimates the value of research using only the information that is typically reported in cost-effectiveness studies and without the need for undertaking supplementary statistical analysis. Our framework and companion VOI-HBP tool aim to provide a practical approach to informing deliberations about research priorities in LMIC countries so that the limited resources allocated to HBPs achieve greater gains in population health.
We apply the VOI-HBP tool to the evidence base that informed the HBP of Malawi’s Health Sector Strategic Plan (HSSP) 2017–202210. Malawi has used a HBP since the early 2000s to prioritise interventions for funding within its national health budget. In addition, clear ambitions have been set to secure funds for health research, with the government agreeing to commit 2% of its overall health budget to research activities and overseas development partners being required to commit 5% of their assistance funds.11 12 Malawi’s National Health Research agenda12 is developed through structured deliberations of a large panel of experts and stakeholders from the Ministry of Health, academic institutions, service providers and bilateral and multilateral donors. Alongside several criteria such as equity impacts and public acceptability of research, these deliberations are informed by qualitative assessments of evidence needs, where particular attention is given to evidence gaps on efficacy. Whether these identified evidence gaps translate to uncertainty in cost-effectiveness and could challenge the current allocation of limited resources is, however, not considered. In this context, the Ministry of Health13 acknowledges the need to strengthen these deliberations with quantitative estimates of where research could make the largest contributions to population health.