

SCCMPod-552: AI in Critical Care and Education
Oct 4, 2025
Kaitlin M. Alexander is a clinical associate professor specializing in integrating AI into critical care education, while Ankit Sakhuja directs AI and informatics at the Institute for Critical Care Medicine. They discuss the transformative potential of AI in critical care education and practice. Kaitlin shares innovative ways AI enhances experiential learning and simulates patient cases. Ankit highlights AI's capability to analyze vast ICU data for better decision-making, addressing data overload, and ensuring ethical usage. They stress the importance of teaching responsible AI application in clinical settings.
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Data Overload Drives AI Adoption
- ICU clinicians face overwhelming data, often thousands of data points per patient per day.
- Ankit Sakhuja argues AI can harness this scale to surface actionable insights and reduce cognitive load.
AI Flagged Nutrition Consults
- At Mount Sinai, an AI model runs continuously to flag patients needing nutritionist evaluation.
- Ankit Sakhuja reports this improved delivery of nutritional therapy for hospitalized patients.
Use Live Case Prompts For AI Learning
- Use AI in small-group case prompts during teaching and have learners critique the outputs live.
- Kaitlin M. Alexander says this reveals learning gaps and teaches students to evaluate AI outputs responsibly.