S1, E39 - Sarah Rossetti, RN, PhD: Nursing Informatics & the CONCERN Early Warning System

About this episode

The episode features Sarah Rossetti discussing the CONCERN early warning system for predicting patient deterioration through nursing documentation behavior.

On National Nurses Day, Practical AI in Healthcare welcomes its first nurse: Sarah Rossetti, RN, PhD, of Columbia University. Her CONCERN early warning system takes an unusual approach to predicting patient deterioration. Instead of modeling a patient's vital signs and labs, it models the nurse's documentation behavior, since the frequency and timing of charting reflect clinical concern long before the numbers move. In a 74-unit randomized trial of more than 60,000 patients, published in Nature Medicine, CONCERN was associated with a 35.6% reduction in instantaneous mortality risk. Rossetti and the hosts unpack the method, the counterintuitive rise in ICU transfers, equity safeguards, and what ambient AI means for the signal. https://practicalaiinhealthcare.com/episodes/#S1E39 More on Sarah Rossetti's work: https://www.dbmi.columbia.edu/profile/sarah-collins-rossetti/

People in this episode

Hosts: Steven Labkoff, MD, Leon Rozenblit, JD, PhD

Guest: Sarah Rossetti, RN, PhD

Topics covered

• nursing informatics
• patient deterioration
• early warning systems
• clinical documentation
• AI in healthcare

Keywords

• CONCERN
• early warning system
• patient safety
• nursing
• AI
• mortality risk
• ICU transfers
• healthcare equity

Mentioned in this episode

Organizations: Columbia University

Books & works: Nature Medicine

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