

SCCMPod-552: AI in Critical Care and Education
12 snips Oct 4, 2025
Kaitlin M. Alexander, a clinical associate professor specializing in AI in pharmacy education, and Ankit Sakhuja, director of AI at an Institute for Critical Care Medicine, share insights on integrating AI in critical care. They discuss how AI can enhance education through interactive simulations and improve clinical decision-making by analyzing vast data. The duo addresses challenges like patient data privacy and algorithm transparency, while exploring the future of personalized medicine and the importance of teaching responsible AI usage to healthcare professionals.
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Data Overload Makes AI Necessary
- ICU clinicians face an overwhelming data volume, often ~20,000 data points per clinician per day.
- AI can help harness and summarize that data to support smarter, scalable decision-making.
AI Identifies Nutrition Consult Needs
- At Mount Sinai an AI model flags patients who would benefit from a nutrition consult automatically.
- That tool improved detection of nutrition needs and helped ensure patients received appropriate nutritional therapy.
Use AI For Guided Case Discussions
- Use AI during small-group topic discussions by prompting cases and then critiquing outputs with learners.
- This reveals knowledge gaps and teaches students to evaluate AI-generated clinical answers critically.