A Framework for Prioritizing Research Investments in Precision Medicine

Area of Science:

• Health Economics
• Genomic Medicine
• Decision Science

Background:

• Precision medicine (PM) adoption is limited despite significant research investment.
• Foundational economic approaches are needed to guide PM's proper use and growth.

Purpose of the Study:

• To develop and present a novel framework for forecasting the expected value of precision medicine (PM).
• To incorporate patient, physician, and payer behaviors into economic models for PM diffusion.
• To provide decision-relevant metrics for evaluating PM implementation and investment.

Main Methods:

• Conceptualized new decision-relevant metrics based on the expected value of individualized care (EVIC) framework.
• Considered behavioral aspects of patients, physicians, and payers influencing PM adoption.
• Applied the framework to a retrospective evaluation of the OncotypeDx genomic test in breast cancer patients.

Main Results:

• Enriched metrics inform decisions on reimbursement, implementation programs, and research investments.
• Replicated prior OncotypeDx evaluations but highlighted limitations of unmet assumptions.
• Demonstrated that incorporating practical behaviors can significantly alter value estimates for PM.

Conclusions:

• The presented framework and methods offer decision-makers improved tools for assessing PM value.
• Recognizes the importance of adoption data for effective decision-making in PM.
• Highlights the need for further research in developing predictive models for PM technology diffusion.