Advancing Health – HCA’s AI-Driven Patient Safety Evolution, Part 2

Podcast: Advancing Health
Host: Dr. Chris Tirienzo (AHA Chief Physician Executive)
Guest: Dr. Randy Fagan (Chief Quality Officer, HCA Healthcare)
Date: September 8, 2025
Theme: HCA Healthcare’s comprehensive integration of AI to advance patient safety, with a focus on robust governance, frontline engagement, and actionable lessons for health systems.

Episode Overview

This episode delves into HCA Healthcare’s journey with AI-driven patient safety, offering a practical look at governance structures, variance reduction, the importance of frontline staff involvement, and real-world examples of AI-enabled decision support. Dr. Randy Fagan shares insights and concrete advice for hospital leaders navigating AI adoption.

Key Discussion Points & Insights

1. The Necessity of Robust AI Governance

(01:33 - 02:57)

• Comprehensive Stakeholder Involvement:
  Dr. Fagan describes HCA’s multi-disciplinary governance framework, integrating not just clinical leadership but operations, finance, marketing, supply chain, and more.

  “We've put into place a pretty robust governance structure that goes beyond just our clinical leaders... It's important as we look at use cases that we're looking at each use case through all lenses.” — Dr. Fagan [01:33]

• Objective Prioritization of Use Cases:
  Uses quantitative risk/opportunity scoring to identify high-impact AI use cases, with a primary objective to reduce variance in clinical and operational practice.

2. Variance Reduction: The Core Value of AI

(02:57 - 03:36)

• Impact Beyond Averaging Up:
  Fagan emphasizes that AI’s most promising contribution is reducing variability—by clinician experience, patient presentation, or geography—thereby delivering more consistent and safer care.
• Relatable Analogy:
  Dr. Tirienzo offers a “batting average vs. slugging percentage” analogy to distinguish between broad vs. targeted improvements.

  “Is this a batting average problem or is this a slugging percentage problem?... It really does branch into very different pathways.” — Dr. Tirienzo [02:57]

3. The Critical Role of Frontline Involvement

(03:36 - 04:45)

• Early Involvement for Relevance and Buy-in:
  Involving frontline staff from the onset ensures solutions address real needs and promotes adoption.

  “It is critical that we get the people closest to the work involved early in the process to help to shape that work.” — Dr. Fagan [03:36]

• Lessons from Early Failures:
  Dr. Tirienzo reflects on prior missteps, reinforcing this point:

  “We showed it to the people who are going to use it and they said, ‘What's this? We don't need this...’ That is a lesson that you learn exactly once in your career.” — Dr. Tirienzo [04:06]

4. Augmentation, not Automation: Preserving Human Judgment

(04:45 - 05:44)

• AI as a Decision Enhancer:
  Dr. Fagan clarifies that the intent is to augment, not replace, clinician judgment except where safe.

  “How do we enhance human decision making, not replace it, especially in the clinical space?” — Dr. Fagan [04:45]

5. Real-World Applications: Staffing & Documentation

(05:44 - 09:52)

• Staffing Optimization:
  AI helps standardize nurse staffing, freeing leaders to focus on patient care while optimizing team composition for both patient needs and nurse preferences.

  “…offloading that burden from them, it allows them to actually lead rather than spend hours of their day managing a schedule.” — Dr. Fagan [05:44] “This is exactly the kind of problem that AI is built to solve because AI finds patterns and helps develop the solution.” — Dr. Tirienzo [06:21]

• Skill Mix and Clinical Considerations:
  AI factors in disease states and nurse experience, aiming for balanced units rather than homogeneity (all new or all veteran nurses).

  “How do we create the right dynamic of skill sets and experiences to meet the needs of the patients?... There’s a clinical value in the work.” — Dr. Fagan [07:09]

• Ambient AI for Documentation:
  HCA pilots AI-driven documentation that reduces physician/admin workload and improves record completeness and continuity.

  “It can remove literally hours’ worth of work... Also, when you think about having a more accurate, complete medical record...it's just better for patients.” — Dr. Fagan [07:09]

• Benefit to Workforce Well-being:

  “This ambient technology is giving it [face-to-face patient time] back... improve the experience of our workforce... while we are in the midst of a workforce crisis that we will never be able to recruit our way out of.” — Dr. Tirienzo [09:52]

6. Key Lessons Learned for Health Systems

(11:08 - 12:27)

• Multi-disciplinary Teams:
  Include voices beyond clinical—finance, operations, etc.—to comprehensively address AI challenges.
• Start with a Safely-Tested, High-Impact Problem:
  Choose a problem where failed attempts carry low risk but successful solutions will have significant positive effects.
• Avoid “Solution Looking for a Problem”:
  Focus on identifying the core clinical or operational need before engaging vendors or purchasing solutions.

  “Don’t start with vendor selection. That becomes a solution looking for a problem, you need to first identify the problem you’re trying to solve and then identify the solution...” — Dr. Fagan [11:37]

Notable Quotes & Memorable Moments

• On Governance:
  “We've included those folks to be a part of the table because it's important as we look at use cases that we're looking at each use case through all lenses.” — Dr. Fagan [01:33]
• On Learning from the Front Line:
  “It validates the problem, it ensures the relevance and buy in.” — Dr. Fagan [03:36]
• On AI’s Role:
  “How do we enhance human decision making, not replace it, especially in the clinical space?” — Dr. Fagan [04:45]
• On the Future of Health Workforce:
  “You have picked the best possible time to go into medicine or nursing...because...our entire world got electronified.... this ambient technology is giving [face time] back.” — Dr. Tirienzo [09:52]
• On Implementation Wisdom:
  “If you fail, you’re going to fail safely in this. And…don’t start with vendor selection.” — Dr. Fagan [11:37]

Important Segment Timestamps

• [01:33] – Building AI governance across functional areas
• [02:57] – Reducing variance as a methodology for improvement
• [03:36] – Importance of engaging frontline staff early
• [04:45] – Augmenting, not replacing clinicians with AI
• [05:44] – Case study: AI in nurse staffing
• [07:09] – Clinical documentation and administrative burden reduction
• [09:52] – Workforce crisis and technology’s humanizing return
• [11:37] – Lessons learned: Team composition, focusing on problems first

Summary

This episode provides a playbook for scalable, AI-enabled patient safety initiatives. HCA’s experience underlines the necessity for inclusive governance, a variance-reduction mindset, early and deep engagement with frontline users, and disciplined implementation focused on tangible, tested problems. The practical wisdom offered is relevant for organizations of all sizes—in Chris Tirienzo’s words, “just as easily in a critical access hospital in Oregon as...a multi-state system like HCA.”