What if the anesthesia workstation could see trouble coming and stop it before it starts? We explore how anesthesia moves from reactive to predictive by blending AI, medical-grade wearables, and closed loop systems with a strong safety culture. The story of Alex—a 75-year-old who developed postoperative delirium and fell—anchors the stakes and shows how early signals, if recognized and acted on, can change a life.

We break down practical uses of machine learning in the perioperative space: forecasting hypotension minutes ahead, integrating multimodal physiologic data for real-time decision support, and taming alarm fatigue with smarter, context-aware alerts. From operating room monitors to infusion pumps, interoperability turns scattered data into timely action.

Automation takes the next step with closed loop control. Imagine EEG-guided dosing that keeps hypnosis within target ranges, fluid and vasopressor titration that stabilizes hemodynamics, and a supervisory controller that coordinates these loops so clinicians can focus on communication, situational awareness, and patient advocacy. Through it all, safety culture remains the foundation: psychological safety, shared learning, and consistent prioritization of safety over short-term operational pressures. Technology should amplify the human connection, not replace it.

You’ll leave with a clear view of what to pilot now—AI decision support in high-yield scenarios, targeted wearable programs for high-risk pathways, and structured training that embeds safety into daily practice. If this vision sparks ideas or questions, reach out and join the conversation. Subscribe, share with a colleague who cares about perioperative safety, and leave a review to help more clinicians find the show.

For show notes & transcript, visit our episode page at apsf.org: https://www.apsf.org/podcast/293-reimagining-anesthesia-with-ai-wearables-and-safety-culture/

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