Advancing Health Podcast

HCA’s AI-Driven Patient Safety Evolution, Part 1

Date: September 3, 2025
Host: Dr. Chris Durienzo (Chief Physician Executive, AHA)
Guest: Dr. Randy Fagan (Chief Quality Officer, HCA Healthcare)

Episode Overview

This episode explores HCA Healthcare's comprehensive approach to patient safety and quality, focusing on the integration of artificial intelligence (AI) as a transformative tool. Dr. Chris Durienzo interviews Dr. Randy Fagan about HCA’s efforts to learn from high-reliability organizations outside healthcare, the organization's holistic safety framework, and emerging AI-enabled solutions driving measurable improvements in patient outcomes. This is the first of a two-part series.

Key Discussion Points & Insights

1. Scope and Structure of HCA's Quality Efforts

[01:34–03:44]

• HCA Healthcare operates ~2,000 points of care, with nearly 200 hospitals across half the U.S. states, serving diverse communities from urban to rural settings.
• Dr. Fagan's role as Chief Quality Officer is newly created, unifying previously separate domains:
  • Patient safety
  • Medication compliance and management
  • Regulatory readiness/response
  • Clinical advisory services (service lines)
  • Quality research and claims insights
• Quality work at HCA is anchored around four pillars:
  1. Patient safety
  2. Regulatory compliance
  3. Clinical service line performance
  4. Claims, insights, and research (scanning the policy, legal, economic, and competitive horizon for clinical strategy development)

“It's a brand new role... to provide greater efficiency and hopefully a force multiplying effect in terms of the impact we can have broadly across the organization.”
—Dr. Randy Fagan [02:35]

2. A Broader View on Patient Safety

[04:17–05:55]

• Patient safety is foundational; it acts as a limiting factor (“governor on the engine”) for compliance, clinical outcomes, and liability.
• High-reliability sectors like railways, manufacturing, and military aviation surpass healthcare in safety metrics, often by factors of 10 to 1,000.
• Healthcare has unique challenges, but many safety lessons are transferable and can be scaled without changing core operating models.

“Safety becomes a ceiling that everything else kind of bumps itself up against. And you can't go any higher than your performance and safety.”
—Dr. Randy Fagan [04:41]

“There are scalable and industry agnostic lessons that we can and should learn from these high performers...”
—Dr. Randy Fagan [05:31]

3. Learning from Other Industries

[05:55–08:09]

• HCA formed a cross-disciplinary team (safety, HR, ethics, nursing, etc.) to benchmark with:
  • GE Manufacturing (Waukesha, WI)
  • DuPont Chemical (Wilmington, DE)
  • The 160th Airborne (military special operations)
  • Defense Health Agency
  • Virginia Mason (healthcare)
• Team conducted field trips and site visits to extract practical safety strategies adaptable to healthcare environments.

“We spent time with GE Manufacturing... visited DuPont Chemical... visited the 160th Airborne Division... tried to spend time physically with people who have created substantive levels of safety and performance and reliability...”
—Dr. Randy Fagan [06:58]

4. Introducing AI as a Patient Safety Accelerator

[08:09–10:09]

• AI is seen as a critical enabler, especially for “moving upstream” in patient safety:
  • Shifting focus from adverse outcomes (falls, mortality) to near-misses, behaviors, and environmental risks.
  • Hospitals are geared to track downstream outcomes; AI unlocks measurement of upstream indicators through pattern recognition.
• AI aggregates complex signals into actionable insights previously inaccessible to human observers.

“AI almost becomes not just an enabler, but... may even create an ability we wouldn't otherwise have... to embed some of these practices in our organization.”
—Dr. Randy Fagan [08:43]

“There is a lot of if-then pattern recognition in behaviors, in signals... that when aggregated by AI, serve as that upstream measure...”
—Dr. Randy Fagan [09:28]

5. AI in Action: Use Cases at HCA Healthcare

[10:54–13:59]

• Initial AI deployments focused on low-risk, non-clinical functions (e.g., workflow, staff scheduling) to reduce cognitive and administrative burden.
• HCA’s digital transformation arm (led by Dr. Michael Schlosser) develops and sponsors clinical AI solutions.
• Core principle:
  • AI augments but does not replace clinical decision-making.
  • AI democratizes knowledge, reduces variance in decision approaches and outcomes.
• Clinical use case:
  • Partnership with GE Healthcare to build AI-driven fetal heart rate tracing analysis.
  • AI identifies ambiguous cases ("the middle" of the bell curve), helping to distinguish which require intervention, thus supporting physician decision-making and protecting vulnerable populations.
  • The algorithm is being submitted to the FDA for approval.

“This is not going to tell a doctor what they should or shouldn't do... but AI is a vehicle for us to... democratize understanding... and if you reduce the variance in the knowledge base, you reduce the variance in decision making, and... outcomes.”
—Dr. Randy Fagan [12:06]

“We've been actually training an AI algorithm... to be able to recognize those ones that are in the middle and swing them to the left or the right and say, are these more likely to be something we don't need to worry about, or... do need to worry about?”
—Dr. Randy Fagan [12:52]

6. Transforming Data into Action

[13:59–14:59]

• AI enables continuous monitoring and pattern recognition at a scale no human workforce could match.
• Dr. Durienzo emphasizes AI’s role in transforming raw data into actionable information for both patients and workforce support.

“That is where AI is making a difference today—helping with pattern recognition, consuming and monitoring reams of data which... is staying as data and not being transformed into information.”
—Dr. Chris Durienzo [14:07]

7. Commitment to Shared Learning and Scale

[14:59–15:25]

• HCA aims to scale and share learnings broadly, so improvements in safety and outcomes benefit all communities.

“Those things that we learn to do not just once, but at scale are things that need to be shared broadly... Because at the end of the day, we're all caring for our communities and we need to do this together.”
—Dr. Randy Fagan [15:03]

Notable Quotes & Memorable Moments

• “You cannot go any higher than your performance and safety.”
  —Dr. Randy Fagan [04:44]

• “We could say we're different. I'm not sure how different we are.”
  —Dr. Randy Fagan [05:24]

• “AI augments, but does not replace, clinical decision-making.”
  —Dr. Randy Fagan [12:07]

• “Helping with pattern recognition and consuming and monitoring reams of data... that is where AI is making a difference today.”
  —Dr. Chris Durienzo [14:07]

Important Timestamps

| Timestamp | Segment | |------------|--------------------------------------------------------------| | 01:34 | Scope and structure of HCA’s safety & quality | | 04:17 | Patient safety as foundational; impact on other pillars | | 05:55 | Benchmarking with non-healthcare high safety organizations | | 08:09 | AI as a driver of upstream patient safety measurement | | 10:54 | AI use cases: workflow, staff scheduling, moving to clinical | | 12:30 | Clinical AI: fetal heart rate tracing example | | 14:59 | Commitment to sharing and scaling learnings |

Episode Summary

In this engaging and insightful episode, Dr. Randy Fagan shares HCA's multi-layered approach to quality and patient safety—rooted in both internal integration and outward learning from industries with elite safety records. AI emerges as a game-changing tool, not only for automating processes but for fundamentally changing how safety is measured and acted on. The conversation underscores the value of cross-industry collaboration, data-driven transformation, and the promise of AI to improve outcomes for both patients and frontline caregivers.

Listeners are left anticipating Part 2, which promises further exploration of outcomes and implementation.