Presentation (CTI)

OBJECTIVES: Early health economic modelling is a useful approach to inform intervention development and trial design. This project demonstrates a case study on how headroom analysis and value of information (VoI) could be used to inform intervention development and trial design for complex public health interventions.
METHODS: COPE-BP is a planned multicomponent public health intervention for hypertension management targeting low-income urban residents in Bangladesh and Pakistan. A decision-analytic Markov model was developed to estimate the lifetime value for money and health impact of a hypothetical COPE-BP intervention compared to usual care from the healthcare system perspective. Headroom analysis calculated the maximum amount of resource which could be spent on the COPE-BP intervention while remaining cost effective. VoI used the expected value of partial perfect information (EVPPI) of single parameter and grouped parameters to estimate the expected benefit of eliminating uncertainty and therefore informing priorities in data collection in the forthcoming trial, with VoI results scaled to reflect the total hypertensive prevalent population in both countries.
RESULTS: Headroom shows that the maximum cost-effective intervention cost per participant was US$12 (95% CI: -14, 37) in Bangladesh and US$9 (95% CI: -10, 27) in Pakistan. The VoI results show that the composite CVD risk function parameters are the key drivers of uncertainty. When evaluating the components of the composite CVD risk function independently, eliminating uncertainty for CHD risk generates the largest expected value of 7.40 million USD for Bangladesh, 9.77 million USD for Pakistan.
CONCLUSIONS: This case study demonstrates the value of early health economic modelling to inform public health intervention and trial design, and to maximise the value of health and research investments in resource-constrained global health settings.