A newly proposed payment model aims to increase reimbursement for cancer diagnostics by incentivizing companies to produce more clinical utility data. However, to drive widespread adoption, companies may also need to look to risk-sharing deals with payers.
Molecular diagnostics and sequencing-based tests for cancer have been stuck in a negative loop.
Slow and inconsistent reimbursement practices coupled with a lack of data on health or economic benefits at launch often slows their uptake. This in turn hampers investment in new diagnostics, which are needed to guide treatment, reduce patient exposure to toxic or suboptimal therapies or identify patients at the greatest risk for adverse outcomes.
New payment models from various stakeholders are aiming to break that logjam.
One, from the American Society of Clinical Oncology (ASCO) and researchers at Duke University School of Medicine, proposes a framework that would tie different reimbursement levels to the amount and quality of clinical utility data generated for tumor biomarker tests.
Published in the Journal of Clinical Oncology in October, the model aims to help payers assess the value of new or existing diagnostics by categorizing the type of evidence that would support different levels of reimbursement. It could also serve as a road map for companies to understand the quality of evidence needed to gain greater reimbursement.