ENCORE! EP263: The Start-up Who Won Medicare's AI Contest, Beating Out IBM, Deloitte, and Mayo—A Conversation With Andrew Eye

In this Encore episode, Stacey Richter talks with Andrew Eye, CEO and founder of ClosedLoop.ai, about how his start-up beat out IBM, Deloitte, and Mayo to win Medicare's AI contest — and what predictive analytics and machine learning can actually do for population health, risk stratification, and reducing financial toxicity in health care.

WHAT YOU'LL LEARN

✅ What predictive analytics actually is, and where it delivers the most value in health care

✅ Why explainability is such a hot topic in health care AI specifically

✅ What "data shaming" gets wrong, and why incomplete data still has value

✅ Why top-performing Medicare Advantage plans already use advanced analytics and AI to risk-stratify their populations

✅ Why the diminishing returns of interoperability and more data don't have to stop you from getting started now

WHY THIS MATTERS

ClosedLoop.ai beat out over 300 rivals with a system that forecasts adverse health events and surfaces action steps for clinicians directly in the EHR. As excessive upcoding and gaming in Medicare Advantage continue to cost taxpayers a fortune, AI-driven risk adjustment and predictive analytics are moving from marketing pitch to real, deployable tools — and the health care system, as Andrew puts it, can't afford that level of inefficiency much longer.

=== LINKS ===

🔗 Show Notes with all mentioned links: Episode Page

🔗 Healthcare Industry Acronyms and Terms

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00:00 Introduction

04:34 What exactly predictive analytics is.

05:05 The use cases of predictive analytics value.

07:23 The oversimplification of how people think about risk.

09:03 "Did you have an impact or not?"

09:17 The public scorecard for predictive analytics.

13:59 "Explainability is a real hot topic in artificial intelligence, specifically in health care."

15:24 Data shaming—what's wrong with it, and why incomplete data are still important.

17:34 The possibilities that machine learning allows for in patient care in health care.

23:45 "Our health care system can't afford for that level of inefficiency."

24:57 "It's not a question of if; it's a question of when."

26:04 The diminishing returns of interoperability and more data for machine learning.

29:21 "You're running your business today, and whatever data you're using to run your business … you can use it to provide better patient care."

30:01 Andrew's advice: Get started now.