Lack of Continuous Video EEG Surveillance Results in Delayed Event Reporting

Although real-time event detection during video EEG recording is required to ensure patients' safety, it is limited by the technologists' availability. We sought to explore the efficiency of real-time event detection by the EEG technologists in a single tertiary academic center. We retrospectively reviewed events from continuous inpatient video EEGs (cEEGs) and epilepsy monitoring unit (EMU) recordings in January 2017, when real-time surveillance was only available during the night shift, and June 2017, when a dedicated neurodiagnostic EEG technologist was available for real-time monitoring during all shifts. The events were categorized into those detected immediately (eyes-on), later in the same shift (delayed) or identified on the subsequent shift (missed). Chi-square and Fisher's exact tests were used for statistical comparisons. In January 2017, there were 25 patients (117 days of monitoring) in the EMU and 54 inpatients (146 days of monitoring) on cEEG with 92 total events, (39% seizures). In June 2017, there were 30 patients (133 days of monitoring) in the EMU and 47 additional inpatients (80 days of monitoring) on cEEG with 110 total events, (39% seizures). The number of events identified in real time was low and did not significantly differ among shifts regardless of the availability of the monitoring technologist. Most events were identified at the time of subsequent EEG scanning by the EEG technologist. Partial staffing for continuous video EEG surveillance is insufficient to identify events in real time. EEG technologists are able to identify events during regular EEG scanning.