Payer Presentations Can Trigger Enforcement
from DarshanTalks Podcast Hosted by Darshan Kulkarni
Send us Fan Mail The boundary between scientific exchange and marketing in payer presentations is increasingly blurred, creating significant compliance and enforcement risks. While payers demand real-world evidence, comparative studies, and economic models beyond FDA-approved labeling, manufacturers must ensure all shared information is truthful, non-misleading, properly contextualized, and backed by competent and reliable scientific evidence. Key pitfalls include: Cherry-picking data without balanced limitations. Economic models presented without caveats or assumptions. Future indications framed as imminent rather than investigational. Crossing into promotion can trigger FDA, FTC, OIG, DOJ, and plaintiff scrutiny, with false claims liability a real risk. To mitigate exposure, companies should: Use clear disclaimers and transparent disclosures. Involve compliance early in deck preparation. Document rationale, recipients, and underlying assumptions. Maintain audit trails through tools like Ceres Tracking. The DOJ’s healthcare fraud task force has prioritized this area, making compliance essential not only to avoid regulatory letters but also subpoenas, litigation, and treble damages. Proper safeguards—including playbooks, legal review, and compliance monitoring—protect companies from costly enforcement actions. Bottom line: Scientific exchange with payers is permitted and necessary, but once it drifts into marketing, companies face severe legal and financial consequences. Support the show www.kulkarnilawfirm.com
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Send us Fan Mail The boundary between scientific exchange and marketing in payer presentations is increasingly blurred, creating significant compliance and enforcement risks. While payers demand real-world evidence, comparative studies, and economic models beyond FDA-approved labeling, manufacturers must ensure all shared information is truthful, non-misleading, properly contextualized, and backed by competent and reliable scientific evidence. Key pitfalls include: Cherry-picking data without...
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