Artificial Intelligence in Anesthesia: Current Applications and Near-Future Innovations in Perioperative Practice

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Availability

On-Demand

Expires on Aug 31, 2029

Cost

Member: $70.00

Non-Member: $100.00

Resident Member: $70.00

Credit Offered

2 MAC Ed Credits

Explore how artificial intelligence is being used across perioperative care, including risk prediction, monitoring, imaging, documentation, and emerging anesthesia technologies. This course helps CRNAs and RRNAs evaluate AI tools critically, recognize their limitations, and apply them as clinical support while maintaining professional judgment, oversight, and accountability.

Learning Objective(s):

Identify current and emerging applications of AI in anesthesiology and perioperative medicine.
Recognize appropriate and inappropriate use cases for generative AI tools in clinical and educational settings.
Integrate AI-derived insights into perioperative decision-making while maintaining clinical accountability.
Utilize structured frameworks to evaluate the safety and appropriateness of AI-enabled clinical tools.
Analyze real-world perioperative case scenarios involving AI-supported risk prediction or decision support.
Examine institutional, regulatory, and ethical factors influencing AI implementation in healthcare systems.
Assess medicolegal and professional responsibility considerations associated with AI-assisted care.
Differentiate between AI-generated recommendations and clinician-derived decision-making in perioperative scenarios.
Describe key AI technologies (machine learning, deep learning, predictive analytics) relevant to anesthesiology practice.
Identify current clinical applications of AI across the perioperative continuum, including risk prediction, physiologic monitoring, and clinical decision support.
Explain the principles and potential benefits of closed-loop anesthesia systems and automated drug delivery technologies.
Evaluate emerging AI tools for airway assessment, ultrasound-guided procedures, and postoperative complication prediction.
Discuss ethical, regulatory, and implementation challenges associated with integrating AI into anesthesia practice.
Assess the future role of anesthesia providers in a healthcare environment increasingly augmented by intelligent systems

This program has been prior approved by the American Association of Nurse Anesthesiology for 2.00 MAC Ed CE credits; Code Number 1047203; Expiration Date 8/31/2029.

Jennifer Majumdar, PhD, MSN, CRNA

Accreditation Information:
The American Association of Nurse Anesthesiology is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's Commission on Accreditation.

AANA is an approved provider by the California Board of Registered Nursing, CEP #10862.

Disclosure Statement:
Any relevant relationship between an ineligible company and an individual with the ability to influence clinical content will be identified by the Nurse Planner within the activity. Any relevant relationship between an ineligible company and an individual with the ability to influence clinical content has been mitigated.

Post-Test Attempt Notice:
A minimum passing score of 80% is required to pass this course. You have TWO opportunities to achieve a passing score. If you fail to achieve a passing score of 80%, you will not receive CE credit for this course.

Content Disclaimer:
The views, information, or opinions expressed within the videos and audio are solely those of the individuals involved and do not necessarily represent those of the American Association of Nurse Anesthesiology.

Course content has been prepared by the presenter/developer, and each viewer agrees that the presenter/developer is solely responsible for the content and the accuracy thereof. The viewer agrees that the American Association of Nurse Anesthesiology has no responsibility or liability for the accuracy or completeness of the content.

Refund Policy:
Continuing education activities are nonrefundable.