Decision makers often use value-based decision rules to determine whether technologies offer good value for money and should therefore be adopted, comparing cost-effectiveness analysis results with a threshold value. This assumes that decision makers are indifferent to interventions with the same expected value but different levels of underlying uncertainty. Such indifference is unlikely to hold in practice. We propose a risk-based price and accompanying decision rules to address this limitation.

We characterized risk using the per-patient expected value of perfect independent information (EVPII), a modification of a standard output from value of information analysis. The EVPII estimates the expected value of net benefit losses caused by uncertainty related to a technology, independent of the uncertainty related to alternative treatments. ‘Payer risk tolerance’ is then defined as the maximum per-patient risk of making wrong decisions that payers are willing to accept, expressed in monetary terms. The risk-based price is the price at which the EVPII is equal to the payer risk tolerance.

The risk-based pricing decision rules are as follows: (i) a technology is acceptable for adoption at the submitted price if the incremental net benefit of the technology is greater than or equal to zero and the EVPII is less than or equal to the payer risk tolerance; and (ii) the optimal technology has the greatest expected net benefit at the lowest of the sponsor submitted, value-based, or risk-based price at a given cost-effectiveness threshold value.

The risk-based price incorporates uncertainty and risk attitudes into decision-making. We demonstrate that both risk-averse and risk-neutral payers prefer the outcomes of risk-based pricing. Risk-based decision rules incentivize sponsors to develop evidence. Implementation of the risk-based price improves outcomes for patients by increasing health system net benefits under constrained resources, with better alignment to decision maker risk attitudes.