Other Titles

International Nurse Researcher Hall of Fame Recipient Presentation

Other Titles

Special Session/Plenary Session

Abstract

Human-centered AI offers a powerful opportunity to advance nursing practice and improve patient outcomes. The CONCERN Early Warning Score (EWS) is a nurse-driven AI-based predictive model that uses patterns of nursing surveillance for early prediction of deterioration outcomes. In a multi-site randomized controlled trial, use of CONCERN EWS was associated with a 35.6% reduction in mortality risk, 7.5% reduction in sepsis risk, shorter length of stay, more timely escalation, and cost savings.

Notes

References:

Rossetti, S. C., Dykes, P. C., Knaplund, C., Cho, S., Withall, J., Lowenthal, G., Albers, D., Lee, R. Y., Jia, H., Bakken, S., Kang, M.-J., Chang, F. Y., Zhou, L., Bates, D. W., Daramola, T., Liu, F., Schwartz-Dillard, J., Tran, M., Bokhari, S. M. A., Thate, J., & Cato, K. D. (2025). Real-time surveillance system for patient deterioration: A pragmatic cluster-randomized controlled trial. Nature Medicine. https://doi.org/10.1038/s41591-024-02933-0. Published online: April 2, 2025. PMID: 40175738. PMC12818231

Lee, R.Y., Cato, K.D., Dykes, P.C., Lowenthal, G., Cho, S., Jia, H., Daramola, T., Tuteja, S., Rossetti, S.C., Earlier ICU Transfer after CONCERN early warning system score escalation reduced sepsis-related mortality: results from a multi-site pragmatic cluster randomized controlled trial. AMIA 2025 Annual Symposium. Atlanta.

Author Details

Hall of Fame Inductee: Sarah Collins Rossetti, PhD, BSN, RN, FAMIA, FACMI, FAAN, FIAHSI - Associate Professor, Biomedical INformatics and Nursing, Columbia University

Sigma Membership

Alpha Zeta

Lead Author Affiliation

Columbia University, New York, New York, USA

Type

Presentation

Format Type

Text-based Document

Study Design/Type

Randomized Controlled Trial

Research Approach

Quantitative Research

Keywords:

Clinical Decision Support Systems, Artificial Intelligence, Decision Making in Clinical Medicine, Electronic Health Records, Nursing Informatics

Conference Name

37th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Toronto, Ontario, Canada

Conference Year

2026

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Review Type

Invited Presentation

Acquisition

Proxy-submission

Date of Issue

2026-09-17

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Nurse-Driven, Human-Centered AI: The CONCERN Early Warning System

Toronto, Ontario, Canada

Human-centered AI offers a powerful opportunity to advance nursing practice and improve patient outcomes. The CONCERN Early Warning Score (EWS) is a nurse-driven AI-based predictive model that uses patterns of nursing surveillance for early prediction of deterioration outcomes. In a multi-site randomized controlled trial, use of CONCERN EWS was associated with a 35.6% reduction in mortality risk, 7.5% reduction in sepsis risk, shorter length of stay, more timely escalation, and cost savings.