AUTHOR=Valaparla Vijaya Lakshmi , Sharma Tripti , Almomani Mohammad , Hafeez Muhammad , Komal Fnu , Masel Todd , Silveira Diosely C. , Li Xiangping 

TITLE=Optimization of continuous EEG monitoring in the inpatient setting- a quality improvement study

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1643069

DOI=10.3389/fneur.2025.1643069

ISSN=1664-2295

ABSTRACT=BackgroundContinuous EEG (cEEG) is widely used in the inpatient setting to detect non convulsive seizures and status epilepticus. Prolonged EEG monitoring can increase healthcare cost burden and patient discomfort. Optimizing cEEG by safely reducing the duration of EEG monitoring can be done using a validated scoring system. 2HELPS2B score predicts seizure risk in the next 24 h based on first hour of EEG monitoring and provides recommendation on the total duration of EEG monitoring. We aimed to safely reduce the duration of cEEG monitoring in low-risk patients (2HELPS2B score </=2) and optimize resource utilization.MethodsThis study was performed as a quality improvement interventional study from January till April 2025 in the inpatient setting across three campuses of the University of Texas Medical Branch at Galveston, Texas. A 2-step smart phrase was created on the Epic electronic medical record (EMR) for 2HELPS2B score. This was made live on Epic on January 1, 2025. Epileptologists were educated through departmental grand rounds and timely reminders to incorporate the score by including the smart phrase in the first segment of the cEEG reports.Results and conclusionThe mean monthly duration of cEEG in low-risk group patients reduced by 22.5% in post intervention group. None of the patients in the low-risk group had seizures. Effective implementation of 2HELPS2B scoring system in clinical practice can safely reduce the duration of EEG monitoring in the low-risk group. This will optimize EEG resource utilization and reduce healthcare costs.