Improving Seizure Frequency Documentation and Classification.

Background and Objectives: Accurate and reliable seizure data are essential for evaluating treatment strategies and tracking the quality of care in epilepsy clinics. This quality improvement project aimed to increase seizure documentation (i.e., documentation of seizure frequency from 80% to 100%, date of last seizure from 35% to 50%, and International League Against Epilepsy (ILAE) seizure classification from 35% to at least 50%) over 6 months. Methods: We surveyed 7 epileptologists to determine their perceived seizure frequency, ILAE classification, and date of last seizure documentation habits. Baseline data were collected weekly from September to December 2021. Subsequently, we implemented a newly created flowsheet in our Electronic Health Record (EHR) based on the Epilepsy Learning Healthcare System (ELHS) Case Report Forms to increase seizure documentation in a standardized way. Two epileptologists tested this flowsheet tool in their epilepsy clinics between February 2022 and July 2022. Data were collected weekly and compared with documentation from other epileptologists within the same group. Results: Epileptologists at our center believed they documented seizure frequency for 84%-87% of clinic visits, which aligned with baseline data collection, showing they recorded seizure frequency for 83% of clinic visits. Epileptologists believed they documented ILAE classification for 47%-52% of clinic visits, and baseline data showed this was documented in 33% of clinic visits. They also reported documenting the date of the last seizure for 52%-63% of clinic visits, but this occurred in only 35% of clinic visits. After implementing the new flowsheet, documentation increased to nearly 100% for all fields being completed by the providers who tested the flowsheet. Discussion: We demonstrated that by implementing an easy-to-use standardized EHR documentation tool, our documentation of critical metrics, as defined by the ELHS, improved dramatically. This shows that simple and practical interventions can substantially improve clinically meaningful documentation.

Standardization of seizure response times and data collection in an epilepsy monitoring unit.

OBJECTIVE: We sought to improve seizure response times in the epilepsy monitoring unit, improve the accuracy and reliability of seizure response time data collection, and develop a standardized and automated approach for seizure response data collection in the EMU. METHODS: We used Quality Improvement (QI) methodology to understand the EMU workflow involved in responding to seizures (a process map); to create a theory of change that stated the desired aim, potential drivers/barriers and interventions (i.e., key driver diagram) and perform iterative interventions to address some of the drivers plan-do-study-act (PDSA) cycles. We performed three PDSA cycles with a focus on improving the seizure alert system in our EMU. Adjustments were made to the methodology as it became clear that this was a systems issue, and our project would need to focus on improving the system rather than iteratively improving a functioning (stable) system. RESULTS: Over a 6-month period, 252 seizure response times were recorded and analyzed. We performed 3 interventions. The first was initiating twice monthly meetings with nursing and EEG techs to discuss the project and provide feedback on response times. The second was the implementation of a new Hill-Rom seizure alert system to reduce alert times and automate data tracking. The third was implementing a new alert deactivation system to reduce variability in the data. Following these 3 interventions, variation, and data collection methods were improved while also maintaining improvements in seizure response times. SIGNIFICANCE: We identified and implemented an alert system in our EMU which led to more efficient and accurate data collection while maintaining improved response times that resulted from the first intervention. This lays the groundwork for future QI initiatives and has created a framework for standardizing seizure response time recording and data collection that can be replicated at other centers with similar infrastructure, personnel and workflows.

RNS modifications to eliminate stimulation-triggered signs or symptoms (STS): Case series and practical guide.

Responsive neurostimulation (RNS) for intractable epilepsy involves placement of electrodes onto or into the brain that detect seizure activity and then deliver a current to abort a seizure before it spreads. Successful RNS treatment can deliver hundreds of stimulations per day, which are generally unnoticeable to patients. Uncommonly, RNS electrodes may result in stimulation of brain regions or peripheral structures that causes uncomfortable sensory or motor effects, a phenomenon we refer to as stimulation-triggered signs or symptoms (STS). Occurrence of STS may limit the ability to use RNS to full capacity to reduce seizures. In this case series, we describe STS in six out of 58 (10.3%) RNS patients at our institution. To eliminate or minimize STS, we developed a protocol for modification of RNS parameters. Modifying RNS stimulation was associated with reduced STS in all six patients, five had adjustment of stimulation settings, one of lead position. Five out of six patients were able to undergo further optimization of RNS for improved seizure control after reduction of symptoms. One patient had recurrent STS that prevented further increase of RNS stimulation current. This study may help other medical teams in identifying and reducing STS in patients with epilepsy receiving RNS devices.