What products are available from Global MedOps Command?

Global MedOps Command offers a signature AI in Emergency Medicine course through Kajabi, simulation training platforms, books and resources, and the Free EM AI Survival Guide for clinicians who want a practical starting point.

Do I need AI or technical experience to use these resources?

No. The educational materials are built for clinicians and operational learners who want practical frameworks, not software-engineering training or prior AI expertise.

Who creates and teaches the material?

All material is created and taught by Chester Chet Shermer, MD, FACEP, a board-certified emergency physician with more than 25 years of experience in emergency medicine, operational leadership, and simulation-based teaching.

Is the AI training grounded in evidence and real clinical practice?

Yes. The AI training is built around safe implementation, clinical judgment, evidence-aware decision-making, and real-world emergency medicine workflow rather than speculation or hype.

How do learners enroll or get started?

Learners can start with the Free EM AI Survival Guide, move into the full Kajabi-hosted course, explore the simulation lab, or browse books and resources based on their immediate training goals.

Can I still catch up on AI as an experienced emergency physician?

Absolutely. Physicians who learn to evaluate, supervise, and apply AI thoughtfully can still catch up, protect clinical judgment, and lead adoption instead of reacting to it late.

Operations

Building Better Clinical Workflows

Global MedOps Command•March 2026•3 min read

Why this matters

A practical framework for improving efficiency, communication, and reliability in time-sensitive clinical settings.

Recommended next step

Pair this article with the free guide or course store if you want a more structured framework you can apply at the bedside or in leadership conversations.

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What this article covers

Workflow improvement in medicine should begin with the realities of the clinical environment rather than with abstract process mapsThis often means redesigning documentation support, communication pathways, and information retrieval so that critical thinking time is protectedGlobal MedOps Command approaches workflow improvement as a practical operational discipline tied to education, simulation, and responsible use of technology

Author and clinical perspective

Chester "Chet" Shermer, MD, FACEP

Founder, Global MedOps Command

Dr. Chet Shermer leads Global MedOps Command to help emergency physicians, EMS teams, and operational medical leaders strengthen clinical judgment, adopt AI responsibly, and train for high-stakes decisions.

Workflow improvement in medicine should begin with the realities of the clinical environment rather than with abstract process maps. The most useful changes are the ones that remove friction where clinicians actually experience it.

This often means redesigning documentation support, communication pathways, and information retrieval so that critical thinking time is protected. Better workflows do not replace judgment; they create more room for it.

Global MedOps Command approaches workflow improvement as a practical operational discipline tied to education, simulation, and responsible use of technology.

Do not stop at awareness

Turn this article into a concrete next step while the issue is still fresh.

Move from reading into a practical next step if this issue already affects your workflow, department, or training decisions.

See the AI course details Explore EM-Sim

Author and expertise

Chester "Chet" Shermer, MD, FACEP

Founder, Global MedOps Command

Through courses, simulation platforms, books, and practical resources, he translates frontline emergency medicine, transport, and military leadership experience into tools clinicians can use immediately.

This article is published through Global MedOps Command to help emergency clinicians evaluate AI, workflow, and operational decisions with a physician-led perspective.

View the full author hub

Clinical application depth

Evidence-aware AI adoption still depends on clinician judgment, local validation, and operational context.

Even when a topic looks persuasive on first read, the practical work begins when physicians translate it into local policy, escalation thresholds, training expectations, and failure-mode review. That is where credibility is gained or lost.

What to pressure-test next

Separate vendor language from bedside reality by asking how the tool performs in the highest-friction emergency workflows.

Clarify where physician override is mandatory so convenience never outruns clinical accountability.

Tie adoption decisions to measurable workflow, safety, and trust outcomes instead of broad promises about efficiency.

Questions for the next leadership discussion

What part of this issue is a true clinical problem versus a documentation, staffing, or governance problem?

Which patient-safety or liability risks increase if the team trusts the tool too early or too broadly?

What would a responsible pilot look like before this topic touches department-wide workflow?

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Build the next step from this article

Strengthen topical depth, related reading, and the right conversion path.

Keep readers inside the same topic cluster with related articles, then channel them toward the guide, course, books, simulation, or contact path that best matches the problem this article surfaced.

Course

Move from insight into a repeatable framework

Use the flagship course when you want a structured way to evaluate AI tools, pressure-test claims, and protect clinical judgment.

See the AI course details

Simulation

Practice the decision path under pressure

Use EM-Sim when you want scenario-based repetition that turns article-level insight into physician-facing emergency-medicine reps.

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Guide

Take the quickest next step

Use the free survival guide when you want the shortest path from this article into a practical emergency-medicine AI overview.

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Building Better Clinical Workflows

Chester "Chet" Shermer, MD, FACEP

Turn this article into a concrete next step while the issue is still fresh.

Chester "Chet" Shermer, MD, FACEP

Evidence-aware AI adoption still depends on clinician judgment, local validation, and operational context.

Strengthen topical depth, related reading, and the right conversion path.

Move from insight into a repeatable framework

Practice the decision path under pressure

Take the quickest next step

Building AI Fluency as a Professional Survival Skill

AI and Patient Handoffs: The Documentation Gap

AI Bias in Pain Management Is an ED Problem

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