In the field of global health, an all-too-common paradox is that technical solutions to major challenges– drugs, vaccines, devices and other interventions – often exist but are not widely delivered. Why do health technologies that have been proven to be cost-effective fail to be implemented in low- and middle-income countries? What can researchers do to help resolve this last-mile problem?
One reason for this gap is that for policy-makers, evidence of cost-effectiveness may be a necessary but not sufficient condition for adoption. Cost-effectiveness analysis demonstrates that a particular intervention offers value for money (in terms of incremental health gains per dollar), but casts no light on the equally critical practical question of whether it is likely to be affordable to the implementing agency (in terms of total dollar outlay). In low- and middle-income countries (LMICs), budget impact is an important criterion for funding new interventions, particularly for large public health investments such as new vaccines. Decision-makers need estimates of the real financial consequences of introducing a new intervention within a defined budget rather than relying on anticipated savings in economic costs alone.
Yet the literature shows that health economists publish far more cost-effectiveness analyses (CEAs) than budget impact analyses (BIAs). Publishing more high-quality BIAs is therefore a first step towards providing a more comprehensive, decision-relevant evidence base for policymakers. Secondly, as CEAs are more common than BIAs, particularly in LMICs, it would be helpful if existing CEAs could be adapted to provide budget impact information without requiring much additional data or analysis. Such pragmatic adaptations could be immediately useful to policy-makers seeking to fill the gap in stand-alone BIAs.
In a recently published study, an international team of collaborators developed a framework that incorporates the latest best-practice international recommendations into a BIA quality assessment checklist, which can be converted into a scoring system to critically assess the quality of a BIA. The BIA Checklist consisted of 15 items divided into four categories: background, interventions, analytic framework and results. For instance, in the background category we identified five features of the healthcare system that should be explicitly considered: financing available, budget for vaccines, the country’s decision to introduce the new vaccine, rotavirus disease burden and other relevant healthcare system factors such as availability of infrastructure. The recommended perspective is that of the decision maker or budget holder. Finally, the size of the eligible population must be described and data sources or approaches used to estimate population size explained. Strict scoring rules were followed to assigned a full (1), partial (0.5) or null (0) score for each item, based on how closely the article met the relevant recommendations. A modified BIA checklist and scoring system was developed for CEAs, to evaluate the extent to which a CEA can be used to provide sufficient information for a BIA.
To demonstrate the use-case for these tools, we examined the case of rotavirus vaccine, a vaccine that has the potential to address the leading cause of diarrheal disease, and a leading cause of mortality, among children in LMICs. Most of the estimated 215,000 deaths in children under 5 years of age from rotavirus gastroenteritis occur in LMICs. Since 2006, when rotavirus vaccination was introduced, it has been shown to be efficacious and cost-effective in multiple settings, and since 2009, WHO has recommended vaccination in all countries. However, take-up is far from universal where it is most needed with adoption currently in about 90 countries and estimated global coverage of 25%.
We applied the checklists and scoring systems to a systematic review of rotavirus vaccine economic evaluations conducted in LMICs and examined the extent to which existing evaluations provide sufficient evidence about budget impact to enable decision making. We found that even for this widely-known and critical technology, most published BIAs do not meet current best-practice recommendations, such as not discounting future costs, providing annual or budget relevant financial streams of costs, model validation, and sensitivity and scenario analyses among others. Existing CEAs moreover, generally did not provide sufficient budget-relevant information to be easily adapted for decision making purposes.
Evidence-based policymaking requires that policymakers address both the value of technology as well as its affordability. Our study shows that there is considerable scope for researchers to take steps that ensure that economic evaluation fully meets the needs of policymakers, and to ensure that lack of the right kind of evidence is not a bottleneck for critical health technologies.