In order to determine how best to dedicate resources to get the maximum impact in improving population health in the future, policymakers need accurate information about the cost effectiveness of different health interventions. To be most useful to policymakers, estimates for different interventions must be as comparable as possible.
The Cost Effectiveness research team aims to increase comparability by using consistent inputs, explicitly following a set of core assumptions, valuing the benefit of all interventions in a common way (in this case, disability-adjusted life years averted), and observing a common set of guidelines in analytic model development.
Key Activities
- Produce cost effectiveness assessments for health interventions and health service delivery platforms
IHME’s long-term aim is to produce a set of comparable cost effectiveness assessments for more than 300 health interventions and a multitude of health service delivery platforms across multiple regions of the world. Many of the existing cost effectiveness estimates available to policymakers use different assumptions about both costs and effectiveness that make it difficult to compare results across studies. By conducting assessments of these platforms as well, IHME will provide policymakers with the ability to understand the trade-offs when the same intervention is delivered through different channels. Ideally, this area of investigation will yield a computational tool that policymakers can use to compare the cost effectiveness of multiple interventions in their own countries. This work is a component of the Disease Control Priorities Network.
- Extend existing tools for choosing child health interventions to encompass broader determinants of child mortality and distal factors
Various tools such as the Lives Saved Tool (LiST) provide useful guidance on the potential impacts of technology scale-up based on meta-analyses of efficacy. A critical challenge for understanding trends in child mortality is to coherently relate the evidence on technology scale-up with the evidence on the relationship between other risks and social determinants, such as education, on child mortality. Some effects of distal socioeconomic, cultural, and demographic factors are mediated through access and uptake of technologies. The dramatic declines in child mortality in all developed countries that predate the advent of child survival technologies are testament to the fact that the recent decline in child mortality is not entirely related to technology scale-up. It is important for prioritizing resources for improving child mortality that the evidence on all the determinants of child mortality is put into one coherent framework. One way to integrate this evidence is to use data from the Demographic and Health Surveys. The research team is attempting to map the effect sizes between each step in the causal web for child mortality.
Impact
The Cost Effectiveness research team’s work will provide policymakers with tools and information on the most cost-effective interventions to improve health outcomes.
