Nurse-driven neurological decline recognition and documentation protocols: a quality improvement project and scoping review of electroencephalography education and implementation

Abstract

Neurological deterioration encompasses a spectrum of acute clinical changes that occur in hospitalized patients and are associated with increased morbidity and mortality, particularly when recognition and escalation of care are delayed. Continuous electroencephalography (EEG) enables detection of neurological decline; however, its effectiveness depends on timely bedside recognition, event-marker activation, and structured clinical documentation. This quality improvement initiative was implemented at a rural tertiary referral hospital serving frontier populations where baseline assessment identified variability in nursing recognition of neurological decline, inconsistent EEG event-marker activation, and nonstandardized documentation practices that limited electroclinical correlation and interdisciplinary communication. Guided by the Institute for Healthcare Improvement Model for Improvement and reported in accordance with SQUIRE 2.0 guidelines, a six-week intervention implemented structured EEG-focused nursing education, a standardized neurological response algorithm, and a guided documentation template integrated into routine workflow. Matched pre- and post-intervention surveys (n = 45) demonstrated significant improvements in nursing knowledge and confidence. Mean scores on the 10-item EEG knowledge assessment increased from 73% correct at baseline to 99% correct post-intervention, representing a 26-percentage-point improvement in EEG workflow and seizure-recognition knowledge among participating nurses. Confidence in EEG event-marker activation improved from 2.84 to 4.64 (p < .001). Documentation confidence also increased, and interdisciplinary satisfaction reached 95% positive endorsement. Embedding structured neurological response tools into routine nursing workflows improved recognition, communication, and documentation of neurological events during EEG monitoring. This scalable nurse-driven model offers rural hospitals a practical strategy to improve the reliability of EEG-related processes of care.