Social Determinants of Genetic Testing Utilization Among Pediatric Epilepsy Patients
Abstract number :
3.135
Submission category :
13. Health Services (Delivery of Care, Access to Care, Health Care Models)
Year :
2024
Submission ID :
438
Source :
www.aesnet.org
Presentation date :
12/9/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Katherine Xiong, MD – Stanford University
Prathyusha Teeyagura, BS – Stanford University School of Medicine
William Gallentine, DO – Stanford University
Rationale: Genetic testing for patients with unexplained epilepsy is increasingly common, with the 2022 National Society of Genetic Counselors and the American Epilepsy Society practice guidelines recommending genetic testing be offered to all individuals with unexplained epilepsy. Factors including insurance coverage, cost, and access to genetic specialists likely impact patient access. Patients from historically marginalized groups’ access may be disproportionately affected, but to date, limited investigations to social, clinical and systems levels determinants have been conducted. We aimed to characterize the genetic testing practices at Lucile Packard Children’s Hospital – Stanford (LPCH – S) and to determine if specific social, clinical or systems-levels determinants are predictive of genetic testing service access.
Methods: This is a retrospective cohort study of patients evaluated in the pediatric epilepsy clinic at LPCH-S between 2020-2023 with a diagnosis of epilepsy and an indication for genetic testing, including neonatal/infantile onset seizures, epileptic encephalopathy, intractable epilepsy, or other neurodevelopmental disorder or autism, without prior genetic evaluation. Demographic variables including age, race, gender, primary language, insurance provider, rural/urban status [through Rural Urban Commuting Area (RUCA) measure], and genetic testing type were recorded. Primary outcomes of 1) the rate of genetic testing ordering and 2) the rate of testing completion (defined as test collection and resulting within 180 days of order placement) were extracted. Time to testing completion was also evaluated. Logistic regression and correlation analysis was used to examine statistically significant (p < 0.05) differences.
Health Services (Delivery of Care, Access to Care, Health Care Models)