Precision medicine is the future…at least that is what we have been told. But to treat patients based on genetic biomarkers, one first has to test for these biomarkers. What factors to payers consider when evaluating whether or not they should provide coverage for these genetic tests?
This is the exact question that Dhanda et al. (2020) aim to answer. After conducting in-depth interviews with six payers, the authors found six attributes of interest to payers:
- Type of information the test provides (i.e., screening vs. treatment prediction),
- Probability that the member will have an informative genetic marker,
- Expert agreement on whether the test result would lead to a change in treatment plan
- Expected quality-of-life gains,
- Expected survival gains
- Cost to the plan.
Once these attributes were determined, the authors used a discrete choice experiment approach to estimate which of these attributes mattered most. After surveying 150 individual payer respondents, they found:
Payers valued improvements in quality of life the most (marginal willingness to pay [mWTP] of $1,513-$6,076), followed by medical expert agreement on the treatment change (mWTP of $2,881-$3,489). Payers placed a relatively lower value for genetic tests with lower marker probability (mWTP of $2,776 for highest marker probability to $423 for lowest marker probability). Payers mWTP was lowest for resolving uncertainty in quality of life (mWTP of $1,513- $2,031) and life expectancy gains ($536-$1,537).
In short, not only does expert opinion matter, but the results of these genomic tests must impact treatment practices in a way that directly affects survival or quality of life. Payers seem to discount the value patients place just on knowing or the value of reduced uncertainty and also how quickly the tests can be turned around even though previous studies (e.g., Regier 2009) have found these factors important.