For many low- and middle-income countries, health benefits packages (HBPs) have become a key component for providing universal health coverage from a limited resource envelope. Simply put, HBPs define which healthcare interventions will be provided within a country’s health system. However, due to a range of uncertainties which exist within current evidence bases that inform the costs and benefits of healthcare interventions (e.g. limitations in data quality, quantity or relevance), selecting the interventions to prioritise within the package is challenging. Some interventions may indeed ultimately drain too much resources from the healthcare system with respect to the benefits they generate, or alternatively, the package may miss out on those interventions that would have provided greater value for the money invested.
In response to this challenge, Thanzi la Onse researchers, Laetitia Schmitt, Beth Woods, Jessica Ochalek, Paul Revill and Karl Claxton (Centre for Health Economics, University of York), have therefore developed a new framework and freely-available tool, to explicitly consider the decision-making implications of uncertainty in the currently available data and to assess the value of undertaking research. Its objective is to guide the allocation of limited research funds so that HBPs are better informed and ultimately, generate more population health.
This framework is implemented by the freely-available ‘Value of Information for Health Benefits Package design’ (VOI-HBP) tool, whose objective is to create a picture of uncertainty (and of the value of reducing it) around the decision to include or not healthcare interventions on the sole basis of the information on their costs and benefits reported in publicly available cost-effectiveness studies. This information may be presented visually, in the form of tornado plots, cost-benefit scatterplots and cost effectiveness ratio histograms, or using standard metrics of variation such as confidence intervals or standard errors.
Application of the tool to the evidence base available for the healthcare interventions that were considered for the HBP of Malawi for 2017-2022, identified three interventions to consider when establishing healthcare research priorities: ‘male circumcision’, ‘community-management of acute malnutrition in children’ and ‘isoniazid preventive therapy in HIV +individuals’. This case study shows how application of the framework can help align research strategies with HBPs’ evidential needs so that packages generate more health gains in the future.
In designing HBPs, decision-makers are often faced with difficult choices, particularly in situations where there are more interventions under consideration than can be accommodated within available, and often scarce, budgets. It is hoped that this framework and accompanying tool can provide useful methods to support resource allocation decision-making processes underpinning HBPs, assist decision-makers with prioritising interventions, and offer insight to help policy makers and international research funding organisations identify areas for further research.
Find out more using the links below:
Research Article: Concomitant health benefits package design and research prioritisation: development of a new approach and an application to Malawi | Laetitia Schmitt, Jessica Ochalek, Karl Claxton, Paul Revill, Dominic Nkhoma, Beth Woods | December 2021
Practical Tool: Uncertainty Analysis for supporting HBP design: VOI-HBP tool | Laetitia Schmitt, Beth Woods, Jessica Ochalek, Karl Claxton | December 2021
By: Laetitia Schmitt, Jessica Ochalek, Karl Claxton, Paul Revill, Beth Woods | January 2022
