Multisite Pragmatic Cluster-Randomized Controlled Trial of the CONCERN Early Warning System.

ABSTRACT:

Importance

Late predictions of hospitalized patient deterioration, resulting from early warning systems (EWS) with limited data sources and/or a care team's lack of shared situational awareness, contribute to delays in clinical interventions. The COmmunicating Narrative Concerns Entered by RNs (CONCERN) Early Warning System (EWS) uses real-time nursing surveillance documentation patterns in its machine learning algorithm to identify patients' deterioration risk up to 42 hours earlier than other EWSs.

Objective

To test our a priori hypothesis that patients with care teams informed by the CONCERN EWS intervention have a lower mortality rate and shorter length of stay (LOS) than the patients with teams not informed by CONCERN EWS.

Design

One-year multisite, pragmatic con

SUBMITTER: Rossetti SC 

PROVIDER: S-EPMC11177900 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature