New thinking on clinical utility: Hard lessons for molecular diagnostics

摘要

Objectives To describe 5 basic requirements for planning, implementing, and proving clinical utility for diagnostic tests, drawing on recent reimbursement decisions. Study Design Review of recent reimbursement decisions by Palmetto GBA's MolDx program, and summary of lessons learned.Methods Qualitative review of publicly available coverage and reimbursement decisions, plus our industry experience.Results Lack of clinical utility data is the most commonly cited reason for why companies fail to receive favorable coverage and reimbursement decisions in this rapidly growing industry. We summarize 5 strategies to establish clinical utility and secure coverage with reimbursement: 1) understanding that outcomes are hard to capture, but that clinical behavior change is always proximate to outcomes change, 2) starting clinical utility studies early, 3) learning from successes and failures, 4) determining clinical utility with rigorous science, and 5) understanding that clinical utility studies may need to involve private payers and providers from the start.Conclusions Coverage and reimbursement are shifting from relatively low entry barriers to higher, evidence-based barriers that will require test developers to generate evidence of the net clinical benefits before widespread clinical use will occur. Concerted, early investment in rigorously designed clinical utility studies is necessary. The once-lucrative diagnostics testing market is at a crossroads, facing greater pressure to show value in an atmosphere of evolving regulatory priorities. Cost and patient value are in the forefront of every payer's mind as we move deeper into the era of healthcare reform and cost consciousness. Converging efforts-such as the recent McKesson Health Corporation and American Medical Association (AMA) partnership to create a registry of molecular diagnostic tests, and the new gapfilling procedures used by CMS to set reimbursement rates-have increased both the granularity and clarity demands of diagnostic coding, emphasizing the increasing need for precision in quantifying test value and justifying price. With these pressures come insight and a clear aspiration for companies and payers alike: Better, less risky, more principled strategies are necessary for companies to generate evidence of impact and determine clinical utility.