AI is already influencing clinical decision-making, but what happens when those decisions occur outside the systems hospitals can monitor?

In this AMDIS Roundtable, Gregg Malkary is joined by Dr. John Lee, Dr. Paul Sutton, and Dr. Stephon Proctor to examine the growing use of consumer AI tools like ChatGPT, Claude, and Gemini at the point of care. As physicians increasingly turn to these tools for clinical questions, documentation, differential diagnoses, and workflow support, health systems are facing a new challenge: understanding how AI is shaping care when those interactions never appear in the medical record.

The discussion explores where clinicians find value in consumer AI, the risks of shadow AI, and why governance can't focus solely on restricting access. Instead, the panel examines how health systems can build trusted, enterprise-ready AI tools that fit naturally into clinical workflows while protecting patient privacy, preserving clinical judgment, and supporting better care.

Whether you're a CMIO, informatics leader, physician executive, or healthcare technology strategist, this conversation offers practical insight into one of the most important—and least visible—AI challenges facing healthcare today.

• Why physicians are turning to consumer AI tools during clinical care
• The operational and governance risks of shadow AI
• Privacy concerns when protected health information enters public AI platforms
• Where enterprise AI solutions still fall short of clinician needs
• Balancing clinician autonomy with organizational oversight
• How AI may reshape documentation, decision support, and clinical workflows
• Why transparency—not prohibition—will be essential for responsible AI adoption

00:00 | Shadow AI Is Already at the Point of Care
03:12 | How Physicians Are Using Consumer AI Behind the Scenes
07:08 | Why ChatGPT Feels Different Than Traditional Medical References
11:18 | OpenEvidence, MedPearl, and AI at the Bedside
15:46 | Real-World Uses for AI in Emergency Medicine
21:04 | Why Chart Summarization May Be AI's Biggest Win
24:07 | Inside Epic's New Agent Factory
28:42 | The Promise—and Risk—of Agentic AI
34:18 | Why Data Governance Must Come Before AI
38:11 | Ambient AI, Chart Summaries, and the Lowest-Hanging Fruit
40:58 | Hallucinations, Clinical Judgment, and the Human in the Loop
43:02 | Are We De-Skilling the Next Generation of Physicians?
45:34 | How Do We Replace Shadow AI with Trusted Enterprise Tools?
47:49 | Final Advice for Healthcare Informatics Leaders

Guests: Dr. John Lee, Dr. Paul Sutton, and Dr. Stephon Proctor
Host: Gregg Malkary - Lighthouse Healthtech
Sponsored by: Simplifi Medical
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

AI can identify a patient at risk. But what happens when the nurse receiving the alert is already caring for another patient?

As hospitals continue adopting AI-powered clinical decision support tools, nursing leaders face a practical challenge: identifying risk is only part of the equation. Acting on it requires people, workflows, communication, and clinical judgment.

In this episode of Beyond the Blueprint, Gregg Malkary is joined by Daniel Gracie, Carolyn S. Harmon, and Troy Seagondollar to explore how AI-driven alerts intersect with the realities of nursing practice. The conversation examines alert fatigue, cognitive overload, accountability, workflow design, and the limits of technology when resources and staffing remain constrained.

The discussion also explores why AI should support -- not replace -- clinical judgment, how poorly designed workflows can undermine even the most advanced tools, and what healthcare organizations should consider before introducing new AI-driven alerts into patient care environments.

Whether you're a nursing leader, informatics professional, healthcare executive, or technology innovator, this conversation offers a grounded look at what it takes to translate AI insights into meaningful action at the bedside.

• AI can identify risk, but it can't create capacity
• Clinical decision support is not clinical decision making
• Alert fatigue remains a significant patient safety challenge
• The right alert at the wrong time may not change care
• Experience still matters when prioritizing patient needs
• Technology can't fix broken workflows
• Escalation pathways matter as much as the alert itself
• Frontline nurses should help design AI-enabled workflows
• Better data leads to better clinical decision support
• AI should augment clinical judgment, not replace it

00:00 | AI Alerts Are Decision Support Tools, Not Decision Makers
04:29 | When a Nurse Can't Respond to an Alert Right Away
06:09 | Why the Same Alert Means Different Things to Different Nurses
07:40 | Alert Fatigue, Cognitive Load, and Patient Safety
11:15 | What Happens When a Nurse Leaves One Patient to Respond to Another
14:12 | "Treat the Patient, Not the Alert"
16:04 | Do We Need Air Traffic Control for Clinical Alerts?
16:26 | Why AI Can't Fix Poor Workflow Design
18:25 | AI as Decision Support, Not Decision Making
20:30 | Lessons from Telemetry Monitoring and Alarm Fatigue
21:57 | Who Is Accountable When an Alert Is Missed?
23:07 | Why Technology Can't Fix Broken Processes
24:12 | The Cost of Automating Bad Workflows
28:16 | Can AI Be Personalized for Different Clinical Environments?
29:51 | Why Data Quality Determines AI Performance
30:32 | Translating AI Research into Clinical Practice
32:23 | What Nursing Leaders Should Do Before Implementing New AI Tools

Guests: Daniel Gracie, Carolyn S. Harmon, Troy Seagondollar
Host: Gregg Malkary - Lighthouse Healthtech
Sponsored by: Simplifi Medical
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

Healthcare leaders often talk about culture, engagement, and retention. But what if many workforce challenges aren't simply staffing problems at all?

In this episode of Beyond the Blueprint, host Kris Baird and co-host Keith Washington welcome nurse leader and workforce strategist Elizabeth Jeanes for a conversation about the connection between leadership, culture, and workforce design.

Drawing on years of experience in nursing leadership and organizational development, Elizabeth explores why culture isn't built through mission statements or posters on a wall—it's built through consistent leadership behaviors, accountability, and the daily decisions leaders make about what they tolerate and what they reinforce.

Together, they discuss leadership burnout, generational differences in the workforce, the importance of purpose-driven leadership, and the difficult reality of managing toxic high performers. The conversation also examines how healthcare organizations can create environments where caregivers feel valued, connected, and supported—and why those efforts ultimately impact both retention and patient care.

Whether you're a nurse leader, executive, frontline manager, or healthcare innovator, this episode offers practical insights into building cultures where both caregivers and patients can thrive.

• Culture is shaped by leadership behaviors, not mission statements.
• Organizations often achieve the results their systems are designed to produce.
• Leadership development is essential for workforce stability and retention.
• Toxic high performers can cause significant damage to team culture.
• Gen Z caregivers place a high value on culture, belonging, and trust.
• Strong leaders help teams stay connected to purpose and meaning.
• Leadership burnout is an often-overlooked challenge in healthcare.
• Psychological safety requires active leadership and accountability.
• Technology should help caregivers spend more time with patients, not less.
• Positive culture change often begins with influential frontline team members.

00:00 | Toxic Superstars and What Leaders Tolerate

03:30 | Culture by Design vs. Culture by Default

04:35 | Why Leadership Behaviors Shape Organizational Culture

06:09 | Promoting Great Clinicians Doesn't Automatically Create Great Leaders

09:52 | Helping Leaders and Teams Reconnect to Purpose

11:25 | The Hidden Cost of Leadership Burnout

13:16 | Why Gen Z Views Leadership and Workplace Culture Differently

17:13 | Building Psychological Safety in Healthcare Teams

18:05 | The Difficult Decision: Keeping or Losing a Toxic High Performer

22:17 | Bringing Purpose Into Everyday Leadership

25:05 | Seeing Patients as People, Not Room Numbers

26:16 | How Technology Can Help Nurses Return to the Bedside

28:53 | What Every Generation Wants from Leaders

30:06 | Finding the Culture Champions Already Inside Your Organization

Guest: Elizabeth Jeanes - Jeanes Strategic Consulting

Host: Kristin Baird - Baird Group
Co-host: Keith Washington - Companions in Courage Foundation
Sponsored by: Simplifi Medical
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

What if healthcare's staffing crisis isn't really about staffing at all?

In this episode, Elizabeth Jeanes, founder of Jeanes Strategic Consulting and a healthcare leader with more than 20 years of experience in nursing, leadership development, and organizational strategy, challenges one of healthcare's biggest assumptions: that workforce shortages are purely a numbers problem.

Instead, Elizabeth makes the case for rethinking workforce design from the ground up, starting with preceptors, frontline influencers, and the leadership systems that shape culture from day one. Her take? The people are already in your building. We're just not developing them.

Beyond the Blueprint Host Keith Washington and Elizabeth unpack generational intelligence, why quad pay won't fix a broken culture, how preceptor programs should be leadership development, not skills training, and what it actually takes to earn the loyalty of a workforce that's done handing it over for free.

Whether you're building teams, leading culture change, or rethinking workforce strategy, this episode offers a fresh blueprint for the future of healthcare leadership.

• Healthcare's staffing crisis may be less about shortages and more about workforce design.
• Preceptors and frontline influencers have outsized impact on culture, retention, and new hire success.
• Leadership is an action, not a title, and organizations should develop informal leaders early.
• Generational intelligence helps leaders better understand what motivates today's workforce and why loyalty looks different now.
• Younger workers value mental health, work-life balance, and professional growth as much as compensation.
• Strong onboarding and evidence-based training programs can improve retention and reduce costly turnover.
• The future of workforce strategy is not just hiring talent, but building pathways to grow the talent you already have.

00:00 Intro
02:26 Why Preceptors Are the Most Overlooked Leaders in Healthcare
04:10 Culture First: Building Leadership from the Ground Up
09:09 Workforce Pipelines Beyond Nursing
12:05 "We Don't Have a Staffing Shortage. We Have a Design Problem."
14:24 The ROI of Retention and Evidence-Based Training
17:13 Generational Intelligence and the New Rules of Loyalty
21:29 Why Younger Workers Prioritize Mental Health Over Money
23:20 Mapping Your Workforce by Generation
28:28 Transferable Skills vs. Technical Skills
30:25 Inside Elizabeth's Leadership Framework and New Book
35:16 Gen Z, Technology, and the Future of Learning
37:15 Can VR Improve Leadership Development?
38:31 Preparing Gen Alpha for the Workforce
40:27 Final Thoughts & Where to Connect with Elizabeth

Guest: Elizabeth Jeanes
Host: Keith Washington - Companions in Courage Foundation
Sponsored by: Simplifi Medical
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

In this episode, we explore how AI is reshaping physician training — and what medical educators must do now to keep pace. Dr. May Lin (Touro University), Dr. Saroj Misra (A.T. Still University), Dr. Renu Agnihotri (A.T. Still University), and Dr. Shivam Vedak (Stanford University) share what's working and what isn't when it comes to preparing residents and medical students to use AI responsibly. From faculty development and inconsistent guidance across clinical sites, to automation bias and the pressure to see more patients faster, the panel examines the hard tradeoffs facing medical education today — and why building critical thinking alongside AI fluency is the only path forward.

• Faculty development is critical — attendings must understand AI tools before they can effectively guide trainees.
• Consistent AI policies across clinical training sites help reduce mixed messages for residents and students.
• AI should be thought of as augmented intelligence, not a shortcut or replacement for clinical reasoning.
• Trainees who understand how AI models work are better equipped to recognize when they fail.
• Automation bias is a real risk — trainees may accept incorrect AI outputs without sufficient scrutiny.
• Core clinical reasoning skills must be developed independently of AI, especially in early training.
• Hospital productivity pressures can undermine the thorough, deliberate habits that good training requires.
• Patients using AI without clinical background face similar — and potentially greater — risks than trainees.
• The EHR era offers a cautionary tale: physicians must engage early to shape how AI tools are built and deployed.
• Building a healthy relationship with AI from the start of medical education sets the foundation for safer clinical practice.

• 00:00 Intro
• 02:29 Are We Training Doctors for the World They're Entering?
• 04:05 Meet the Guests
• 05:08 Aligning Faculty and Trainees on AI Use
• 08:36 Moving Beyond the "AI as Cheating" Mindset
• 10:20 Which AI Tools Show the Most Clinical Promise?
• 13:05 Building the Right Relationship with AI from Day One
• 15:27 Why Upskilling the Whole Generation Matters
• 18:58 Teaching How AI Models Work — and Fail
• 20:01 The Faculty Development Challenge
• 20:39 How Do You Know a Trainee Truly Understands?
• 25:32 Balancing Thoroughness with Hospital Productivity Pressure
• 27:15 AI Should Improve Care Quality, Not Just Speed
• 29:32 When Patients Use AI Without Clinical Reasoning
• 31:15 Dr. Misra's Challenge: Should Any Task Be Off-Limits for AI?
• 33:18 Renu: The Cognitive Exoskeleton and Productive Struggle
• 34:33 May: A Ban on Banning AI
• 36:52 Shivam: Protect the Process of Clinical Reasoning
• 37:50 Final Thoughts & Closing

Guests: Dr. May Lin, Dr. Saroj Misra, Dr. Renu Agnihotri, Dr. Shivam Vedak
Host: Gregg Malkary - Lighthouse Healthtech
Cohost: Keith Washington - Companions in Courage Foundation
Sponsored by: Simplifi Medical
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

In this AMDIS Roundtable, Dr. Eve Cunningham (Cadence), Dr. Howard Landa (Adventist Health), and Dr. Deepti Pandita (UCI Health) explore what it really means to build an AI-ready EHR. Moving beyond features and vendor roadmaps, they examine how data governance, workflow design, and clinical validation shape the physician's day — from inbox overload to exam-room disconnect. Together, they discuss shadow AI, cognitive burden, and the hard tradeoffs between optimizing legacy workflows and redesigning care. Their message is clear: the next generation EHR isn't about adding more technology — it's about restoring clinical cognition and rebuilding trust in how care gets delivered.

• Bad data leads to bad AI — governance must come first.
• AI is math, not magic — noisy and inconsistent data amplify risk.
• Clinical validation is as important as data hygiene for meaningful AI use.
• The EHR disrupts connection when clinicians must focus on screens instead of patients.
• Ambient documentation restores presence but does not yet create a true intelligent clinical partner.
• Most AI tools solve isolated tasks, not the full end-to-end care workflow.
• Health systems need internal prompt and AI literacy — clinicians are not trained engineers.
• Third-party innovation fills gaps, but long contracts slow adaptation.
• Shadow AI often signals unmet needs, not noncompliance.
• Governance should enable safe experimentation rather than block innovation.
• Clinicians remain accountable for AI-driven decisions under current regulations.
• Patients are rapidly adopting AI tools, often without reliable guardrails.
• AI's highest near-term value is reducing cognitive and administrative burden.
• True progress requires redesigning workflows, not endlessly optimizing legacy processes.
• Leadership prioritization, not technology limits, often slows transformation.
• The next generation EHR must restore clinical cognition and trust.

00:00 | The Key to a Successful EHR: Restoring Clinical Cognition
02:36 | When the EHR Slows Care Instead of Supporting It
01:08 | Why This Isn't About Features or Vendor Roadmaps
02:36 | When the EHR Slows Care Instead of Supporting It
03:46 | AI Is Math, Not Magic
04:05 | Data Governance as the Prerequisite for AI
05:23 | Governance + Clinical Validation = Actionable Intelligence
06:44 | The Keyboard Breaks the Sacred Patient Encounter
08:25 | Ambient Tools and the Return of Joy in Medicine
09:19 | The "Intelligence-Ready" EHR Vision
11:10 | Why Clinicians Aren't Prompt Engineers
12:39 | Is Epic Cosmos Ready for Prime Time?
14:01 | Contextual, Specialty-Specific Views at the Point of Care
15:08 | Third-Party Innovation vs EHR Vendor Lag
16:49 | When to Replace vs Layer New AI Tools
18:09 | Shadow AI as a Signal of Unmet Need
19:08 | Enabling Safe Experimentation Through Governance
20:55 | If AI Makes a Mistake, Who Is Liable?
23:35 | Where AI Should Help First: The Patient Journey
25:19 | Patients Are Already Using AI for Medical Advice
27:33 | Cognitive Scaffolding: Removing Clinical Noise
28:31 | Intelligent Synthesis vs Data Mining
29:13 | The Peer Challenge: How Do We Move 2–3x Faster?
30:02 | Leadership Indecision Slows Transformation
30:47 | Stop Optimizing Legacy Workflows
31:46 | Final Message: Technology Isn't the Barrier Anymore

Guests: Dr. Eve Cunningham, Dr. Howard Landa, Dr. Deepti Pandita
Host: Gregg Malkary - Lighthouse Healthtech
Cohost: Keith Washington - Companions in Courage Foundation
Sponsored by: Simplifi Medical & Storage Systems Unlimited
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

In this AMDIS collaboration, Dr. Mark Pierce (former Parkview Health), Dr. Howard Landa (Adventist Health), and Dr. John Lee (HIT Peak Advisors) examine why data governance is ultimately a patient-care issue, not just an IT function. Drawing on real bedside decisions, EHR transitions, and conflicting metrics, they show how unclear definitions and hidden data create hesitation, workarounds, and loss of clinician trust. Together, they discuss the leadership commitment and investment required to improve data quality, and why clean data is the prerequisite for safe and meaningful AI in healthcare.

• Unclear data definitions slow care — clinicians pause, double-check, or guess at the bedside.
• Data governance is a patient-safety function, not an IT committee exercise.
• Most data problems are silent — staff create workarounds instead of reporting issues.
• Different departments define the same metric differently, eroding organizational trust.
• Leadership wants fast ROI, but governance requires long-term investment and persistence.
• AI magnifies bad data — clean inputs matter more than advanced algorithms.
• Use AI first to clean and structure data before deploying clinical AI tools.
• Start governance with visible problems (e.g., length-of-stay definitions, data sharing).
• Tie governance efforts to active initiatives to gain momentum and participation.
• Organizations rarely advertise good governance — you see it in outcomes, not org charts.
• Clinician trust is fragile; one bad data-driven decision can last for years.
• Accessible, synthesized data enables faster decisions and real improvement cycles.

00:00 | Why Data Governance Gets Ignored
02:01 | Data Governance as a Patient-Safety Issue
04:25 | When Data Helps — and When It Slows Care
06:29 | Too Much Information, Not Enough Clarity
09:14 | The "Raiders of the Lost Ark" Data Warehouse Problem
11:04 | Why Leaders Delay Governance Work
13:06 | The Real Investment Required
14:28 | The PD-Not-PDSA Cycle in Healthcare
15:16 | AI Fails Without Clean Data
16:55 | What Breaks When Definitions Differ
18:05 | Bad Data at the Bedside: A Stroke Decision
20:19 | How Trust in Data Is Lost
23:13 | Silent Workarounds Across Hospitals
25:18 | Where Organizations Should Start
27:15 | Making Data Actionable for Clinicians
29:26 | Governance as Organizational DNA
31:24 | Aligning AI Governance With Data Governance
32:13 | Use AI to Clean Data First
34:15 | Bias, Training Data, and Clinical Risk
36:29 | Final Message: When Rules Are Unclear, Care Suffers

Guests: Dr. Mark Pierce, Dr. Howard Landa, Dr. John Lee
Host: Gregg Malkary - Lighthouse Healthtech
Cohost: Keith Washington - Companions in Courage Foundation
Sponsored by: Simplifi Medical & Storage Systems Unlimited
Audio/Video: Tim Jones - Health Nuts Media
Marketing: Josh Troop - Troop-Creative
Learn More at: www.beyond-blueprint.com

In this episode, we're joined by two leaders from Sutter Health who are scaling ambient listening across their enterprise: Dr. Veena (Goel) Jones, Chief Medical Informatics Officer, and Stephanie Driscoll, Vice President of Digital Implementation.

In 2025 alone, Sutter onboarded more than 3,100 clinicians to ambient listening—moving well beyond pilot programs to true system-wide adoption. Together, they share what it takes to make that scale possible, from EHR integration and workflow redesign to governance, training, and change management.

• Ambient listening only scales when the EHR foundation is ready. Workflow standardization and template cleanup made enterprise adoption possible.
• In 2025, Sutter onboarded more than 3,100 clinicians—moving ambient listening beyond pilot and into system-wide infrastructure.
• AI adoption is operational, not just technical. Governance, enrollment processes, and structured onboarding determined success.
• Clinicians pulled the technology. Ambient listening spread because it reduced cognitive burden—not because it was mandated.
• Full Epic integration eliminated friction and accelerated both ambulatory and inpatient adoption.
• Ambient listening is a gateway. Documentation is just the beginning—queued orders and future AI workflows depend on foundational readiness.

00:00 | Enterprise Change Management and Ambient Listening
01:30 | Welcome to Beyond the Blueprint
02:30 | Why Ambient Listening Is More Than Hype
03:25 | Meet the Leaders: Sutter Health's AI Scale Strategy
05:00 | Early Physician Reactions: "This Changed My Life"
06:05 | From Pilot to Enterprise Enrollment
07:40 | Standardizing Epic to Prepare for AI
09:20 | Governance, Safety, and Clinical Oversight
11:00 | Integrating Ambient Listening Directly into Epic
13:30 | The Role of the Digital Academy in Scaling Adoption
15:45 | Reducing Cognitive Burden at the Bedside
18:00 | Scaling Across Ambulatory and Inpatient Settings
20:30 | Structured Intake and Monthly Onboarding Waves
23:00 | Protecting Coding Integrity and Revenue Cycle
27:15 | Beyond Documentation: Orders and Workflow Automation
29:00 | Measuring Impact: Charting Time and Pajama Time
31:45 | Why Clinicians Pulled the Technology
34:00 | Preparing the EHR Foundation for Future AI
36:30 | What It Really Takes to Move Beyond the Pilot
38:50 | Closing Thoughts: Ambient Listening as Infrastructure