EP263: How Population Health Leaders Use Artificial Intelligence Right Now, With Andrew Eye From ClosedLoop

In this episode, Stacey Richter talks with Andrew Eye, CEO of ClosedLoop, about how population health leaders are actually using artificial intelligence right now.

WHAT YOU'LL LEARN

✅ How top-performing Medicare Advantage plans are already using AI to risk-stratify populations

✅ What predictive analytics actually means and where its real use cases lie

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

✅ What "data shaming" gets wrong, and why incomplete data can still be valuable

✅ Why the returns on more interoperability and more data for machine learning eventually diminish

WHY THIS MATTERS

Andrew Eye cuts through the AI hype to explain what's actually working in population health today: predictive models that flag which members are likely to become high-cost without intervention, built from real-world, messy health care data organizations already have. He pushes back on oversimplified thinking about risk and data completeness, and argues that most organizations don't need to wait for perfect interoperability to start using the data they already have to improve patient care. His advice is blunt: get started now, because the inefficiency the system can't afford isn't going away on its own.

=== LINKS ===

🔗 Show Notes with all mentioned links: Episode Page

🔗 Healthcare Industry Acronyms and Terms

✉️ Enjoy this podcast? Subscribe to the free weekly newsletter

🫙 Support the podcast with a small donation to the Tip Jar

📺 Subscribe to our YouTube channel

🎤 Listen on Apple Podcasts

🎤 Listen on Spotify

=== CONNECT WITH THE RHV TEAM ===

✭ LinkedIn ✭ Threads ✭ Bluesky ✭ X

00:00 Introduction.

01:50 Artificial intelligence in health care, and the different things that this means to the health care community.

02:06 Image analysis, also known as replacing doctors with robots.

02:25 Chatbots for health care.

02:43 Predictive analytics.

04:39 "What they really care about is, How can this impact our business? How can this improve patient lives?"

04:51 "For us, this is all just better math."

08:13 What exactly predictive analytics is.

08:40 The use cases of predictive analytics value.

11:33 The oversimplification of how people think about risk.

13:13 "Did you have an impact or not?"

13:27 The public scorecard for predictive analytics.

18:16 "Explainability is a real hot topic in artificial intelligence, specifically in health care."

19:46 Data shaming—what's wrong with it, and why incomplete data are still important.

21:53 The possibilities that machine learning allows for in patient care in health care.

28:08 "Our health care system can't afford for that level of inefficiency."

29:21 "It's not a question of if; it's a question of when."

30:37 The diminishing returns of interoperability and more data for machine learning.

33:54 "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."

34:34 Andrew's advice: Get started now.