The CONCERN Implementation Toolkit: Standardizing, Scaling, and Spreading an AI-Based Clinical Decision Support System

Poster Number: P46
Presentation Time: 05:00 PM - 06:30 PM

Abstract Keywords: Clinical Decision Support, Nursing Informatics, Informatics Implementation, User-centered Design Methods
Primary Track: Applications
Programmatic Theme: Clinical Informatics

CONCERN is an AI-based early warning system that uses nursing data to predict patient deterioration. CONCERN has been implemented and studied at two clinical sites, with planned implementations at three additional locations. The CONCERN Implementation Toolkit (CIT) is a collection of resources that provide guidance, support and structure needed for successfully scaling and spreading CONCERN.

Speaker(s):
Jennifer Withall, PhD
Columbia University Department of Biomedical Informatics

Author(s):
Kenrick Cato, PhD, RN, CPHIMS, FAAN - University of Pennsylvania/ Children's Hospital of Philadelphia; PATRICIA C DYKES, PhD, MA, RN - Brigham and Women's Hospital; Sandy Cho, MPH IN-BC - Newton-Wellesley Hospital; Catherine Ivory, PhD, NI-BC, NEA-BC, FAAN - Vanderbilt University Medical Center; Po-Yin Yen, PhD, RN, FAMIA, FAAN - Washington University in St. Louis; Rachel Lee, PhD, RN - Columbia University; Brian Douthit, PhD, RN, NI-BC - Department of Biomedical Informatics, Vanderbilt University; Temiloluwa Daramola; Graham Lowenthal, BA - Brigham and Women's Hospital; David Albers, PhD - University of Colorado, Department of Biomedical Informatics; Syed Mohtashim Abbas Bokhari; Sarah Rossetti, RN, PhD - Columbia University Department of Biomedical Informatics;