Abstracts

Rationale:
Electrographic status epilepticus and high seizure burden have been associated with worse neurologic outcomes.  Early treatment of electrographic seizures (ES) has been associated with a lower seizure burden.  Live uninterrupted monitoring of the continuous EEG by an experienced reader is impractical and leads to lag in the identification of seizures which delays treatment.  Quantitative Electroencephalography (qEEG) is a sensitive tool for seizure detection and has the potential to improve seizure identification and subsequently time to treatment which in turn may improve outcomes.  This quality improvement project focuses on teaching child neurology residents to effectively identify ES using qEEG.
Method:
Child neurology residents of varying levels of training completed a pre-training survey that included examples of common background patterns, artifacts, and seizures using proprietary qEEG software (Persyst).  After completion of the pre-training survey, residents viewed a 25-minute online education module focused on principles of qEEG and pattern recognition.  Residents who completed the video module received a printed reference card which included example images and descriptions of common qEEG trends.  A post-training survey was administered at two intervals (within 1-4 months after initial training and approximately 9 months later) to assess the accuracy with trend identification.  Resident comfort level with identification of seizures was also assessed using a 5-point Likert scale (1=very uncomfortable and 5=very comfortable) on the pre-training and post-training surveys.
Results:
Sixty-nine percent (9/13) of child neurology residents completed the pre-training survey, 46% (6/13) completed the initial post-training survey and the follow-up post-training survey.  For the 6 residents who completed all three surveys, the average overall scores were higher on both the immediate post-training survey and the follow-up post-training survey by 20% and 17%, respectively.  Overall average scores were 74% on the pre-training survey, 94% on the initial post-training survey, and 91% on the follow-up post-training survey.  Residents also reported an increase in comfort with identifying seizures on qEEG (average scores: pre-training 3.2, initial post-training 3.8, follow-up post-training 3.82).     
Conclusion:
A standardized instructional module is effective in teaching quantitative EEG and improves seizure pattern recognition for child neurology residents.  Other educational resources, like reference cards, can also facilitate acquisition and retention of knowledge.  Future direction includes ongoing training for child neurology residents and EEG technicians.
Funding:
:None