Ep 54: The Business of Making Healthcare Data Trustworthy

Summary Healthcare is racing to be "AI ready." But most of the industry is still trying to turn billing exhaust into strategy. In this episode, Bradley Bostic sits down with Ryan Leurck, Co-Founder & Chief Analytics Officer at Kythera Labs, to cut through the noise and get blunt about what actually makes AI work in healthcare. Because the truth is simple—and uncomfortable: If your data can't be trusted by humans, it can't be trusted by AI. And in healthcare, much of our data was never designed for the questions we're now demanding it answer. Takeaways Why claims, EHR, and lab data weren't built for strategy—and how that limits AI. The risk of modern AI: "AI is not always right, but it always sounds sure." Why healthcare data is still optimized for coding and billing, not predictive insight. Kythera's mission to "reduce the uncertainty in the use of healthcare data." How leaders should think about "AI ready" without falling for hype. The reality of claims: a "big bag of receipts" that can mislead without expert context. Why data quality and missingness matter as much as the data you do have. A practical vision for AI inside provider orgs: agents that function like analysts/interns, not decision-makers.   Chapters 00:00 Introduction to AI in Healthcare 01:23 Ryan Leurck's Journey from Aerospace to Healthcare 03:22 The Current AI Landscape and Its Misconceptions 06:54 Kythera Labs: Reducing Uncertainty in Healthcare Data 11:13 Challenges of Healthcare Data and AI Integration 18:03 Opportunities for AI in Healthcare 22:52 Kythera's Target Audience and Solutions 27:41 The Role of AI in Operational Efficiency 31:18 Data Privacy and Accessibility in Healthcare 34:30 The Future of AI in Healthcare   Keywords AI, healthcare, data analytics, machine learning, healthcare technology, Kythera Labs, artificial intelligence, data quality, healthcare providers, operational efficiency