Incorporating Real Option Value in Valuing Innovation: A Way Forward

Considerable progress has been made in defining and measuring the real option value (ROV) of medical technologies. However, questions remain on how to estimate (1) ROV outside of life-extending oncology interventions; (2) the impact of ROV on costs and cost effectiveness; and (3) potential interactions between ROV and other elements of value.

We developed a 'minimal modeling' approach for estimating the size of ROV that does not require constructing a full, formal cost-effectiveness model. We proposed a qualitative approach to assessing the level of uncertainty in the ROV estimate. We examined the potential impact of ROV on the incremental cost-effectiveness ratio as well as on the potential interactions between ROV and other elements of value. Lastly, we developed and presented a 15-item checklist for reporting ROV in value assessment.

The minimal modeling approach uses estimates on the efficacy of current treatment and potential future innovation, as well as success rate and length of new treatment development, and can be applied to all types of ROV across disease areas. ROV may interact with the conventional value, value of hope, productivity effects, and insurance value. The impact of ROV on cost effectiveness can be evaluated via threshold analysis.

The minimal modeling approach and the checklist developed in this paper simplifies and standardizes the estimation and reporting of ROV in value assessment. Systematically including and reporting ROV in value assessment will minimize bias and improve transparency, which will help improve the credibility of ROV research and acceptance by stakeholders.