Reducing Mortality Through the Use of AI-Guided RRT Proactive Rounding

Facilitator(s): Natalie Correll-Yoder, MN,RN,CCRN,CCNS

Contact Hours 1.00
CERP A 1.00
Denver Conference
Date Tuesday 5/21/2024
Time 7:30 AM - 8:30 AM MT

Venue Colorado Convention Center

Room Mile High BR 1D
Available On Demand
From Saturday 6/15/2024
To Thursday 10/31/2024

Session Summary

Traditional rapid response teams (RRT) depend on notification by another person/system to identify the patient to be seen emergently. This reactive process can result in the RRT being alerted too late to rescue the patient. Moving to a proactive rounding model, RRTs are able to intervene early to prevent patient deterioration or cardiac arrest. Use of a predictive analytics program alerts the RRT to changes in the patient’s condition in real time to facilitate proactive intervention to reduce mortality.


  • Describe traditional rapid response team models with both reactive and proactive rounding processes.
  • Compare and contrast existing early warning systems to identify patients at risk of deterioration.
  • Evaluate existing artificial intelligence algorithms using predictive analytics to identify patients at risk of deterioration.
Topics Technology, Patient Safety
Role Staff

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Successful Completion

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Provider approved by the California Board of Registered Nursing, Provider number CEP 1036, for 1.00 contact hours.

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