This analysis uses actuarial principles to illustrate a framework for handling uncertainty in modelling the financial impact of recommending new treatments. In collaboration with the National Institute for Health and Care Excellence (NICE) in England, we explore some alternative methodological approaches that build on the incremental cost-effectiveness ratio (ICER), which offer valuable perspectives on mitigating financial uncertainty more explicitly in ultimate decision-making.
Using the evidence from recent hepatitis C manufacturer submissions to NICE, we replicate a state-dependent Markov model as a proof of concept to demonstrate the degree of financial uncertainty around the mean ICER. We also design risk sharing agreements focussing on parameters and model assumptions with the greatest potential budget impact to payers. Selected risk mitigation strategies prevalent in insurance settings, such as stop-loss schemes and risk corridors, are used to illustrate one-way and two-way risk sharing, ultimately reinforcing the need to monitor "real-world" experience against projections.