Demand for Precision Medicine: A Discrete-Choice Experiment and External Validation Study.

Background: A limited evidence base and lack of clear clinical guidelines challenge healthcare systems' adoption of precision medicine. The effect of these conditions on demand is not understood.

Objective: This research estimated the public's preferences and demand for precision medicine outcomes.

Methods: A discrete-choice experiment survey was conducted with an online sample of the US public who had recent healthcare experience. Statistical analysis was undertaken using an error components mixed logit model. The responsiveness of demand in the context of a changing evidence base was estimated through the price elasticity of demand. External validation was examined using real-world demand for the 21-gene recurrence score assay for breast cancer.

Results: In total, 1124 (of 1849) individuals completed the web-based survey. The most important outcomes were survival gains with statistical uncertainty, cost of testing, and medical expert agreement on changing care based on test results. The value ($US, year 2017 values) for a test where most (vs. few) experts agreed to changing treatment based on test results was $US1100 (95% confidence interval [CI] 916-1286). Respondents were willing to pay $US265 (95% CI 46-486) for a test that could result in greater certainty around life-expectancy gains. The predicted demand of the assay was 9% in 2005 and 66% in 2014, compared with real-world uptake of 7% and 71% (root-mean-square prediction error 0.11). Demand was sensitive to price (1% increase in price resulted in > 1% change in demand) when first introduced and insensitive to price (1% increase in price resulted in < 0.1% change in demand) as the evidence base became established.

Conclusions: Evidence of external validity was found. Demand was weak and responsive to price in the near term because of uncertainty and an immature evidence base. Clear communication of precision medicine outcomes and uncertainty is crucial in allowing healthcare to align with individual preferences.