Artificial Intelligence in Anesthesia Practice
AI is already in your OR. Learn to use it — and question it — like an expert.
A clinically grounded course built by a practicing CRNA. Understand the tools entering anesthesia practice, judge what their outputs actually mean, and protect yourself and your patients when an algorithm is in the loop.
A single day of locum income you'd lose to an outdated practice runs $1,500–2,500. One AI-related documentation gap, if it ever became a claim, can cost more than your entire career's worth of CE combined. Set against that, the cost of staying current is small.
CRNAs and SRNAs who keep hearing about AI in anesthesia and want a clear, practical, clinician-first understanding — not hype, not code. No technical background required.
What you'll be able to do
Concrete, bedside-ready capabilities — not abstract objectives.
Explain in plain clinical terms what an AI/ML tool's output actually represents — and what it doesn't.
Interpret a predictive hemodynamic alert and decide when to act on it and when to override it.
Recognize automation bias and alarm fatigue, and apply practical habits that keep the clinician in the loop.
Document AI-assisted decisions appropriately and understand where medicolegal exposure actually sits.
Critically evaluate an AI tool's performance, validation, and bias claims before trusting them at the bedside.
Use generative AI safely in your workflow without risking PHI or clinical accuracy.
Evaluate emerging anesthesia AI tools and separate near-term reality from hype.
Distinguish an FDA-regulated medical device from non-device clinical decision support and general-wellness software, and apply the 2026 FDA CDS guidance.
Describe how closed-loop and automated drug-delivery systems work in anesthesia, and recognize their failure modes and supervision requirements.
Use point-of-care imaging, ultrasound, and airway AI tools appropriately — understanding their assistive role and their limits.
Identify algorithmic bias at the patient level and address informed consent and disclosure for AI-assisted care.
Integrate the course's principles into a safe, practical plan for adopting AI in your own anesthesia practice.
Module-by-module breakdown
12 modules · 24 lessons · a short assessment after each module.
Your instructor
Anastasia is a practicing nurse anesthetist who also builds clinical software. That combination is rare — she works in the OR and with the code, so she can translate what these AI tools actually do into language clinicians use, without the vendor spin.