BACKGROUND: Real-time @entity922 ( @entity922 ) integrated with anesthesia information management systems (AIMS) can generate point of care reminders to improve quality of care. OBJECTIVE: To develop, implement and evaluate a real-time @entity922 system for anesthetic management of pediatric @entity131 ( @entity131 ) @entity1 undergoing urgent neurosurgery. METHODS: We iteratively developed a @entity922 system for pediatric @entity131 @entity1 undergoing urgent neurosurgery. The system automatically detects eligible cases and evidence-based key performance indicators (KPIs). Unwanted clinical events trigger and display real-time messages on the AIMS computer screen. Main outcomes were feasibility of detecting eligible cases and KPIs, and user acceptance. RESULTS: The @entity922 system was triggered in 22 out of 28 (79%) @entity1 . The sensitivity of detecting continuously sampled KPIs reached 93.8%. For intermittently sampled KPIs, sensitivity and specificity reached 90.9% and 100%, respectively. 88% of providers reported that @entity922 helped with @entity131 anesthesia care. CONCLUSIONS: @entity922 implementation is feasible and acceptable with a high rate of case capture and appropriate generation of alert and guidance messages for @entity131 anesthesia care.

Development and Feasibility of a Real-Time Clinical Decision Support System for XXXX Anesthesia Care.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity131 :: ('MESH:D001930', 'Disease') :: ['TBI', 'traumatic brain injury'] @entity922 :: ('MESH:D013568', 'Disease') :: ['CDS', 'clinical decision support']
@entity131 :: (MESH:D001930,Disease) :: ['Traumatic Brain Injury']
