Professor of Psychiatry and of Neurology Case Western Reserve University School of Medicine
Rationale: Epilepsy self-management (ESM) is the summative set of behaviors that people with epilepsy (PWE) use to optimize their overall health. There remains a significant paucity of information on ESM including longer-term effects on health, differential patterns of ESM competency in diverse populations, and best ways to assess outcomes. This report describes the evolution of the Managing Epilepsy Well Network Database (MEW DB), an integrated dataset, intended to advance knowledge on ESM and inform the next wave of epilepsy care research. Methods: To ensure representative governance, and a strategy aligned with the overall goals of the MEW Network, sites contributing data provide up to two representatives to serve on a Steering Committee (SC). The SC establishes consensus on analyses to be conducted, how and where they will be reported, and how publication authorship should be fairly credited. Documents articulating these procedures include a set of Frequently Asked Questions (FAQs), an authorship agreement, and a standardized analysis request template. The data management structure facilitates harmonization and integration of new/ additional data. The MEW DB utilizes a hierarchical organization structure, with three tiers of data generally increasing in ascending complexity or collection burden. A recent revision of Tier 1-3 variables combined evaluation of existing variables in archival and ongoing studies and developing consensus on a crucial common data set for ESM studies. Results: Tier 1 data includes socio-economic variables including sex, age, race/ethnicity, education, employment and income, and clinical and health data such as age of epilepsy diagnosis, types of seizures, frequency of seizures, quality of life, psychiatric diagnosis or substance use. Tier 2 and 3 variables include more specific clinical, health and psychosocial variables related to ESM including seizure severity, epilepsy self-efficacy, depression, stress and anxiety, sleep quality, and cognitive functioning. Tier 3 variables include pharmacologic treatments (e.g., antiepileptic drugs (AEDs), psychotropic drugs) and patient-reported measures of stigma, social support and impact of epilepsy. The MEW DB sample includes 1,563 adult PWE, mean age 39.9 (SD 13.4 years), 64.9% women, 77% non-Hispanic white, 12.8% African-American and 22.2% Hispanic. The average age of epilepsy diagnosis is 21.3 years (SD 14.9) and individuals are prescribed a mean of 1.8 (SD 0.86) AEDs. Psychiatric comorbidity is extensive and includes 54% with depression and 30.1% with anxiety in this sample. Conclusions: Analysis of MEW DB variables, conceptualized within a socio-ecological framework relevant to ESM, may help to better understand the trajectories and determinants of outcome among PWE. Large samples that take advantage of existing research collaborations and archival datasets have potential to advance care and provide guidance on how ESM might be best incorporated within a comprehensive package of care for PWE. Funding: Please list any funding that was received in support of this abstract.: This work was funded by the CDC SIP 19-003, 6 U48DP006389-01-01, and the findings and conclusions in this abstract do not represent the official position of the CDC.