AI and Reimbursement

• Aditi U. Joshi MD, MSc Global Digital Health Consultant, Bestselling Author, and Emergency Physician
• Matt Fisher Partner, Hancock, Daniel & Johnson, P.C.
• Charles Dunham Principal Shareholder, Greenberg Traurig, LLP

As AI continues to reshape clinical decision making and operational efficiency, one major question looms large: how do we pay for it—and who pays the price when something goes wrong?

In this THMT Unscripted podcast episode, we dive deep into the evolving landscape of AI reimbursement codes and explore how they differ from traditional digital medicine and remote monitoring programs. We'll unpack how health systems and digital health companies can set themselves up to use these codes effectively—and what happens when care, efficiency, or liability shifts from human to machine.

We’ll also explore the future of time based billing, the complexities of patient transparency, and what it really means when AI "saves time" but introduces new layers of risk. From direct pay models to health plans and employers, you'll hear perspectives that challenge how we think about value and trust in AI powered care.

Don't miss this conversation on the front lines of healthcare’s AI transformation.

Discussion Questions:

• How are AI reimbursement codes different from other digital medicine codes?
• How do companies and health systems set their programs up to use these codes?
• What should happen to time-based codes when AI reduces physician time?
• Who is liable when AI-assisted clinical decisions lead to harm?
• What information on AI performance should be presented to clinicians at point of care?
• What obligations exist when patients ask about AI use in their care?