Disruption in Healthcare: AI, Policy, and Practical Change With: Mika Newton
In this roundtable episode from Tensor Black, Dr. Doug Flora joins co-hosts Dr. Sanjay Juneja, Debra Patt, and Mika Newton to explore how artificial intelligence is disrupting U.S. healthcare policy, oncology practice, and digital health innovation. Dr. Flora, Executive Medical Director of Oncology Services at St. Elizabeth Healthcare and Editor-in-Chief of *AI in Precision Oncology*, offers candid insights on change management, clinical decision support, and value-based care. The panel also dissects major themes from the Health conference, Medicare’s AI-driven authorization model, and how AI tools like chart summarization can reshape patient access and clinical efficiency. This discussion, designed for healthcare executives and oncology leaders, highlights how AI is not only augmenting decisions but demanding new strategies for adoption, reimbursement, and scale.
Episode Contents:
Key Takeaways
- AI innovation must scale across systems to reduce healthcare costs.
- Fragmented policies undermine national digital health progress.
- Coordinated learning accelerates AI effectiveness in real-world care.
Transcript Summary
What’s the biggest barrier to implementing AI in clinical settings today?
The tools are here, but change management is the bigger challenge. Leadership must prepare teams and workflows for disruption.
How do policy shifts, like Medicare's AI-driven authorization model, affect care delivery?
These changes can streamline care but create fear and delay investment due to unclear reimbursement. Leadership and guidance are crucial.
What’s the role of clinical decision support tools in oncology?
They’re vital for extending reach, surfacing insights, and supporting evidence-based decisions. But AI should nudge, not dictate care.
Innovation vs. Regulation: Finding Balance
How should policy evolve to support responsible AI adoption?
Joint frameworks like the CHAI and Joint Commission report set ethical standards, governance, and transparency guidelines to guide future policy.
How can we scale AI innovation across healthcare systems?
We need infrastructure investment and unified data models. Fragmented policies create barriers. Scale requires coordinated learning and leadership.
What’s needed to bring AI into drug development?
AI is already transforming discovery, but development lags due to regulatory drag. Adaptive trials, NAMs, and digital twins offer hope.
More Topics
- AI in Patient Care
- AI in the Healthcare Industry
- AI and Medical Innovation
- Healthcare Ethics and Policy
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About the Series
Leading oncology AI thought leaders Drs. Sanjay Juneja, Debra Patt, and Doug Flora bring you conversations at the intersection of medicine, data, and innovation. Each episode explores both the big picture and the breaking news in artificial intelligence and healthcare—examining how today’s technology is reshaping the practice and business of oncology.
From industry disruptors to clinical pioneers, guests share insights that bridge the gap between algorithms and the art of patient care.
To learn more about the mission and upcoming initiatives, visit tensorblack.ai and subscribe to stay ahead of the curve.