Podcast Summary

Becker’s Healthcare Podcast

Episode: Suki & McLeod Health’s Three-Phase Roadmap for Scalable AI and Scribe Adoption
Host: Lucas Voss (A)
Guest: Dr. Brian Frost, CMIO at McLeod Health (B)
Date: October 15, 2025

Overview

This episode features Dr. Brian Frost, Chief Medical Information Officer (CMIO) at McLeod Health, discussing the organization's comprehensive and bias-resistant three-phase roadmap for the scalable adoption of ambient AI scribes, specifically their journey with Suki. Dr. Frost outlines how their rural, non-academic system prioritized both quality and return on investment, the innovative vendor selection process, lessons learned, and measurable impacts on both physician well-being and organizational finances.

Main Discussion Points & Insights

1. Context & Challenges of AI Adoption in Rural Healthcare

• McLeod Health is a seven-hospital, rural, nonprofit system in South Carolina with careful financial stewardship.
• Dr. Frost stressed the importance of picking solutions that truly solve practical problems, given limited resources and no large innovation foundation ([00:29]).
• Strategic emphasis: AI scribes aim to address the “cognitive burden” and physician burnout, restoring the “joy of practicing medicine” ([01:41]).

2. Bias-Resistant, Multi-Phase Vendor Selection Process

• Dr. Frost’s approach drew on lessons from medical training about resisting vendor bias ([01:41], [02:51]).

• Phase 0: Six-month vetting of all major vendors using external reviews and internal demos, narrowing to four with strong scalability and viability ([02:58]).

• Phase 1: Real-world, unbiased testing using scripted clinical scenarios:

  • Created 15 detailed patient scripts featuring common medical cases and intentional complications to challenge AI scribe products ([02:58]–[04:20]).
  • Used actors (including C-suite leaders) as patients and assigned different specialties to test adaptability and robustness.
  • Vendors recorded live interactions and immediately delivered note outputs for evaluation by a triad: revenue cycle experts, physicians, and non-clinical staff ([05:10]).
  • Memorable moment: Dr. Frost expected his personal favorite vendor to win, but it placed last, highlighting the power of unbiased testing ([06:05]).
  • Quote:
    "I was pretty sure that I was not biased, but I was also pretty sure my organization was. ... Boy, was I wrong. It was very humbling." – Dr. Brian Frost [02:58]

• Phase 2:

  • The two top vendors were invited back; they presented workflow solutions to a broad cross-section of McLeod physicians ([07:05]).
  • Simultaneous deep tech review by informatics/IT security, with a vision for future scalability beyond documentation (e.g., clinical decision support).

• Phase 3:

  • Rather than a final “bake-off” between the last two vendors, overwhelming physician preference led to direct adoption of Suki ([08:08]).
  • Emphasized goal was not direct financial gain, but burden reduction and improved job satisfaction. Any monetary gains were viewed as a bonus ([08:50]).
  • Quote:
    "We were very clear with the doctors, we don't want to make money. If we break even, great." – Dr. Brian Frost [09:05]

3. Implementation, Pricing Model, and Impact

• Initial Pilot Limitation: Initially offered only to the most “efficient” physicians (top 70th percentile), fearing underutilization of fixed-price licenses – later called a “dumb decision” ([10:20]).
• Pivot to Encounter-Based Pricing:
  • Negotiated a per-encounter cap model, reducing wasted license fees and allowing system-wide access.
  • Discovered adoption willingness is unpredictable; some unexpected users became strong adopters ([11:10]).
  • Quote:
    "You really can't predict who will adopt and not. ... Now I don't have to worry about that." – Dr. Brian Frost [11:15]
• Aligning Interests:
  • The per-encounter fee aligned vendor and health system interests: if it isn’t used, it isn’t paid.
  • Eliminated administrative headaches in license “swap” management.
• ROI and Financial Results:
  • Encounter-based model yielded measurable financial impact:
    • Noted a shift to higher-value billing (more level 4 vs. level 3 CPT codes) and an 8–10% volume uptick.
    • Resulted in net positive ROI:
      • "We're currently right now making $2,636 per provider per month, net every month." – Dr. Brian Frost [12:40]

4. Physician and Organizational Outcomes

• User Empowerment:
  • Physicians gained significant “pajama time” (off-hours charting) back, reallocated to patient care or personal time ([09:10]).
  • Avoided pressuring doctors to “see more patients”; aimed at quality over quantity.
• Unexpected Stakeholder Happiness:
  • Both medical staff and CFO were pleased; the approach benefited clinical well-being and financial health ([10:50]).

5. Vision for Ambient AI in Healthcare

• Dr. Frost is optimistic about the future, seeing current AI scribe platforms as the foundation for broader functions:
  • Real-time clinical decision support
  • Efficient chart review and specialty-specific summaries
  • Enhanced revenue cycle operations
  • Quote:
    "They are the thing that is now in the room with the patient and the doctor … a platform to deliver a lot more than just ambient documentation." – Dr. Brian Frost [13:41]

Notable Quotes & Timestamps

• On Vendor Bias:
  "I was pretty sure I was not biased, but boy, was I wrong."
  – Dr. Brian Frost [02:58]

• On Initial Assumptions:
  "The vendor that I thought the organization should go with, finished last place."
  – Dr. Brian Frost [06:05]

• On Pilot Learnings & Access:
  "Now I don't have to worry about who gets a license or not."
  – Dr. Brian Frost [11:15]

• On Financial Outcome:
  "We're currently right now making $2,636 per provider per month, net every month."
  – Dr. Brian Frost [12:40]

• On Future Impact of Ambient AI:
  "They are the thing that is now in the room with the patient and the doctor and ... a platform to deliver a lot more than just ambient documentation."
  – Dr. Brian Frost [13:41]

Timestamps for Key Segments

• McLeod Health & Initial Context – [00:29]
• Why AI Scribes? – [01:41]
• Bias-Resistant Selection Overview – [02:58]
• Details of Phase 1, the “Scripted Test” – [02:58]–[06:20]
• Learnings from Testing/Physician Input – [06:20]–[08:08]
• Implementation, Pricing Model, and Adoption – [08:08]–[12:40]
• ROI and Final Reflections – [12:40]–[14:20]
• Outlook on Ambient AI – [13:41]

Final Thoughts

Dr. Frost’s rigorously unbiased, evidence-driven approach—and willingness to learn from the results—demonstrated practical strategies for successful, scalable AI adoption in resource-limited health systems. By focusing on physician well-being, thoughtful vendor alignment, and creative pricing, McLeod Health achieved both improved clinical satisfaction and tangible financial returns. Looking forward, Dr. Frost envisions ambient AI as a foundational platform with the potential to fundamentally enhance care delivery, workflow efficiency, and patient outcomes.