Abstracts

Rationale:
Epilepsy is a significant public health issue affecting nearly 3.4 million Americans, or 1.2% of the US population. An estimated one-third of people with epilepsy (PWE) in the US are covered by Medicaid, a joint federal and state partnership that provides health coverage for people with low income. In the state of Arizona, roughly 2 million people—more than 25% of the overall population—are enrolled in the state’s Medicaid program. This is a crucial population for research—and one for which data has historically been overlooked for the epilepsy community.  In most cases, epilepsy is a treatable condition with timely initiation of antiseizure drugs (ASDs). However, despite the availability of many cost-effective ASDs in the US, initiation after epilepsy diagnosis is often significantly delayed. Recent evidence underscores this treatment gap: one-third of newly diagnosed epilepsy patients in the US remain untreated up to 3 years after diagnosis (Kalilani et al., 2019). Other studies estimate that these treatment gaps range from 7% to over 50% of all PWE (Meyer et al., 2010). This delay increases the risk of adverse medical events, emergency department (ED) visits, and hospital admissions. Though there is limited research to explain the delay in ASD initiation, it is likely that a confluence of social and structural determinants of health (SDH) play a role in this treatment gap. Given the known importance of social factors on health outcomes, the limited research surrounding SDH and epilepsy treatment represents a significant gap in knowledge for the epilepsy community.
Method:
Our study encompasses a targeted literature review of epilepsy treatment gaps and the impact of SDH on health outcomes, gathering of SDH data at a census tract-level for the entire state of Arizona, development of a predictive statistical model, building of an interactive Geographic Information System (GIS) Map, and statistical analyses using Arizona Medicaid claims records.
Results:
Our targeted literature review reveals that epilepsy treatment gaps vary tremendously both between and within countries. Identifying the root causes of these treatment gaps remains especially elusive; however, existing literature supports the assertion that SDH are fundamental drivers of health and disease. Among Arizona’s Medicaid population, our predictive statistical model relates the outcome and treatment gap for a PWE to their social determinants at a census tract-level. Census tract-level SDH measures and treatment gap correlations are visualized through the GIS Map, contextualized by patient-level data that includes care setting, continuity of care, and hospital/outpatient/ED utilization during treatment gaps.
Conclusion:
This work provides the first substantial quantitative research looking at the correlation between SDH and epilepsy outcomes at a community level. The insights generated about epilepsy treatment gaps may influence strategies for improving health outcomes in the epilepsy population in Arizona and beyond.
Funding:
:This project is funded by UCB, Inc.