HT3 - Actuarial Approaches To Modelling and Mitigating Financial Uncertainty in Recommending New Drugs and Health Technologies

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Health technology assessments (HTAs) are fundamental in informing decisions on reimbursement, assessing whether premium drug pricing is commensurate with the expected incremental health benefits. In collaboration with the National Institute for Health and Care Excellence (NICE) in England, alternative methodological approaches to the appraisals of new drugs and technologies are explored, which offer valuable perspectives on handling financial uncertainty. Building on the evidence from recent hepatitis C manufacturer submissions to NICE, a state-dependent Markov model is replicated as a proof of concept to demonstrate the degree of financial uncertainty around recommending new drugs for routine commissioning. A theoretical framework is developed to illustrate how risk sharing agreements focussing on parameters and assumptions with the greatest potential budget impact can be implemented. Selected risk mitigation strategies prevalent in insurance settings such as stop-loss schemes and risk corridors support the design of one-way and two-way risk sharing agreements. These are tailored to meet the specificities of the model assumptions from the case study. Recognising the strong influence of the mean incremental cost-effectiveness ratio (ICER) in decision-making, but also the lack of a defined framework for appraising uncertainty around this ratio, reimbursement decisions based on the median ICER and a 75% percentile ICER are explored in the simulation. A measure of variability such as the coefficient of variation supplements the proposed approaches, which incorporate financial uncertainty more explicitly due to the allocation of probability distributions to cost and outcome metrics. Finally, the methodology reinforces the need to monitor actual experience against projections through retrospective reviews of historical medical data, to inform the value of the recoverable per the risk sharing terms. It further builds on actuarial principles and stochastic modelling for handling the financial yet uncertain impact of recommending new drugs and health technologies in a context of value-based care.