To leverage an electronic health system reporting tool to examine how patient and visit volumes, antiseizure medication (ASM) prescriptions, and neuromodulation use evolved within a single tertiary care ambulatory epilepsy center.

For any given epilepsy center, we expect the volume and complexity of patients with epilepsy (PWE) served to evolve through migration, changes in referral patterns, and/or pediatric-to-adult transitions of care. With an ever-increasing volume of data available, generating knowledge that providers can utilize to improve outcomes has become challenging. Traditional manual chart review is labor-intensive and prone to error, and we currently lack automated methods to longitudinally track clinical characteristics of PWE.

This was a retrospective analysis utilizing data from EPIC Reporting Workbench tools for patients seen at the faculty group practice at a single NAEC Level IV Epilepsy Center in Texas, USA, between 1/1/2013 and 12/31/2023 by a set of 14 providers. We generated: a list of (i) visit dates, (ii) all individual prescriptions and dates, and (iii) current procedural terminology (CPT) entries for neuromodulation devices (e.g., responsive neurostimulation, deep brain stimulation). For every patient, a single annual complexity score (CS) was calculated proportional to the frequency of visits and the number of medications used to treat seizures.

Our analysis revealed a doubling of total patients served annually, an increase in ASM polytherapy rates, and subtle shifts in ASM prescribing patterns. High CS were observed in patients treated with neuromodulation or prescribed rescue or liquid ASMs. Average annual CS gradually increased over the study period, and many patients displayed wide CS fluctuations over time.

This study provides a simple approach to longitudinally monitor the volume and complexity of patients within a high level epilepsy center’s clinic, providing opportunities to equitably assign personnel and resources and identify candidates for epilepsy surgery and/or remote patient monitoring.