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

Guests: 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