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Exploring the Implementation Experience and Use of CONCERN Early Warning System in a Rural Community Hospital: A
Youngjin Lee1,2,3, Min-Jeoung Kang1,2, Veysel K Baris1,2
1Brigham and Women's Hospital, Boston, MA.
Abstract:
The Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that analyzes nursing documentation patterns to detect early signs of patient deterioration, with proven effectiveness in reducing the risk of in-hospital mortality and length of stay. This study extends the evaluation of CONCERN EWS beyond acute care settings to a rural community hospital, assessing user experience, system utilization, and accuracy in identifying patient deterioration. The study examined accuracy in a rural setting using a mixed-methods approach-qualitative interviews, quantitative data analysis, and clinical record reviews. Findingssuggestthat CONCERNEWS enhancesearly recognition of clinical deterioration andisusable in the context of busy acute care nursing workflows. These results support its adaptability to facilitate strengthening nursing surveillance, clinical decision-making, and patient safety in rural healthcare settings as well.
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