Objectives: To assess recent advances in interfacility critical care transport.
Data Sources: PubMed English language publications plus chapters and professional organization publications.
Study Selection: Manuscripts including practice manuals and standard (1990-2021) focused on interfacility transport of critically ill patients.
Background: In-hospital deterioration among ward patients is associated with substantially increased adverse outcome rates. In 2013 Kaiser Permanente Northern California (KPNC) developed and implemented a predictive analytics-driven program, Advance Alert Monitor (AAM), to improve early detection and intervention for in-hospital deterioration. The AAM predictive model is designed to give clinicians 12 hours of lead time before clinical deterioration, permitting early detection and a patient goals-concordant response to prevent worsening.
View Article and Find Full Text PDFPurpose/aims: Development and implementation of a predictive analytic scoring system in a system of 21 hospitals required 24-hour surveillance to ensure alerts were responded and acted upon. Identification of gaps in patient care created an opportunity to innovate and develop a team to integrate both workflows.
Description Of Project/program: A Virtual Nurse team of master's degree-prepared nurses with backgrounds in intensive care and management led by a clinical nurse specialist work remotely from their homes.