In this episode, Hunter sits down with Dr. Yubin Park, healthcare AI pioneer and founder of Mimi Labs and Falcon Health, to explore the future of value-based care and how 30TB of public health data can unlock new opportunities.

Topics we cover:

• Why value-based care is like switching from "hourly contractors" to "project-based payments"
• How capitated payment models are evolving beyond traditional HMO approaches
• The reality check on LLMs in healthcare: why they're "smart, cheap interns" that need oversight
• Why healthcare data changes faster than people think (regulations, codes, payment rules)
• How AI can bridge the gap between fragmented government datasets and policy decisions
• Practical applications of public health data for both established companies and startups
• The surprising optimism case for America's "messy" healthcare system vs. monolithic approaches
• Van Gogh's philosophy applied to healthcare: why small details build great outcomes

Perfect for: Healthcare data leaders, value-based care professionals, health tech entrepreneurs, and anyone working with public health datasets or building AI solutions in healthcare.

Dr. Park shares his unique perspective as someone who's experienced healthcare systems in Korea, Japan, and the US, plus insights on building data teams, operationalizing public datasets, and why America's fragmented healthcare system might actually be a feature, not a bug.

Guest Bio: Dr. Yubin Park is a healthcare AI pioneer who built and sold multiple startups, served as Chief Data and Analytics Officer at Astrana Health, and now leads Mimi Labs and Falcon Health. He was recently named to Pearl Health's list of top 50 value-based care thinkers and teaches as an adjunct professor at Emory University.

In this episode, Hunter sits down with Payal Patnaik, former AI/ML Product Lead at One Medical, to cut through the AI hype and discuss what actually works when implementing LLM products in healthcare.

Topics we cover:

• Why most "AI strategies" fail and how to start with the right problems instead of shiny objects
• The three-pillar AI maturity model (Usage, UX, Platform) and where your organization fits
• How to build clinician buy-in for AI tools without triggering replacement fears
• Practical evaluation frameworks for ensuring LLM accuracy and safety
• The 15 essential questions every value-based care data team should answer
• Real lessons from launching 6 LLM services at One Medical within one year

Perfect for: Healthcare data leaders, product managers, executives exploring AI implementation, and anyone building tech solutions for clinical workflows.

Payal shares her journey from journalism and biomedical engineering to leading AI product development, plus insights on responsible AI use, the importance of breaking down complex reasoning tasks, and why LLMs are becoming the great equalizer in healthcare innovation.

Guest Bio: Payal Patnaik led AI/ML product management at One Medical (Amazon Health Services) and previously built data product organizations at Iora Health. She teaches "LLMs in Healthcare 101" and moonlights as a singer-songwriter in the Boston area.