The Digital Patient

215: Mount Sinai’s Drs. Gavin & Nadkarni: How to Turn Predictive AI into Clinical Action, Developing a “Scale-First” Operating Philosophy for Innovation, and Async Care to Improve Patient Access

Jan 22, 2026
Dr. Nicholas Gavin, Chief Clinical Innovation Officer at Mount Sinai, and Dr. Girish Nadkarni, Chairman of AI and Human Health, delve into transforming predictive AI into practical clinical actions. They discuss the importance of a clear 'why' for innovation adoption and the challenges of pilot projects, advocating for a scale-first approach. The duo also explores asynchronous care models that enhance patient access, alongside the need for robust AI governance and equitable deployment. Their insights on workflow redesign and human-AI collaboration promise to reshape digital healthcare.
Ask episode
AI Snips
Chapters
Books
Transcript
Episode notes
ANECDOTE

Demo Routed Patients To A Competitor

  • Nicholas Gavin recounts demoing a triage tool that accidentally routed patients to a competitor during a live demo.
  • The mistake exposed the need for rigorous QA across the software development life cycle.
INSIGHT

Predictions Need Actionable Steps

  • Predictions only matter when paired with actionable recommendations that fit clinician workflows or guidelines.
  • Girish Nadkarni notes AI should evolve to suggest next-best actions that balance patient and system outcomes.
INSIGHT

Differentiate Explainability, Interpretability, Transparency

  • Distinguish interpretability, explainability, and transparency when evaluating clinical AI.
  • Girish Nadkarni warns post-hoc explanations can be misleading and stresses interpretability and model nutrition labels.
Get the Snipd Podcast app to discover more snips from this episode
Get the app