Artificial Intelligence in Anesthesia Practice
AI is already in your OR. Learn to use it — and question it — like an expert.
A clinically grounded, AANA Class A–accredited 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.
The AANA's own independent-practice CE runs about $1,247 for 20 credits. A single day of locum income you'd lose to an outdated practice runs $1,500–2,500.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, costs more than your career's worth of CE combined.
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.
Critically evaluate an AI tool's performance and validation claims before trusting them at the bedside.
Distinguish an FDA-regulated medical device from non-device clinical decision support and general-wellness software.
Document AI-assisted decisions appropriately and understand your medicolegal exposure.
Use generative AI safely in your workflow without risking PHI or clinical accuracy.
Module-by-module breakdown
7 modules · 13 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 writes the code, so she can translate what these AI tools actually do into language clinicians use, without the vendor spin. [Add 1–2 lines: years in practice, settings, and any app/development specifics you'd like to share.]
Frequently asked
Credit hours & pricing shown are placeholders pending final accreditation.