Geospatial Analysis of Predictor Factors in Early Intervention Autism Screenings in Alabama

Screening for autism is an important first step to accessing early intervention services (Scarpa, et. al 2013). Identifying what demographic populations are more likely to pass or fail screeners can provide more information on barriers to diagnoses and services. This study focused on demographic factors that are usually included when studying socioeconomic status. Access to healthcare services in Alabama has been found to be more difficult in rural areas (Croft, et. al 2016), however, autism has not been specifically studied in the state of Alabama. Data was collected for demographic factors (gender, race, county, age of screening and insurance type) in an ongoing MCHAT-R screening study for autism in partnership with the Alabama Early Intervention System. Data was analyzed using descriptive and predictive analyses. Medicaid and ALL Kids insurance holders were 2.5 times more like to have a failed MCHAT-R score. Race, gender, age of screening, and county type (rural/urban) were not predictors of a failed MCHAT-R. Findings on gender and race contrast the historical bias that exists in autism screenings. Rural and urban classifications were a limitation in this study, where county level data was collected instead of a more accurate descriptor of rurality at the zip code level. Medicaid being predictive of a failed screening reflects the need for better mental health services in the state, where currently every county is classified as a Mental Health Profession Shortage Area. This information is useful for policy makers in Alabama to understand areas in need of better funding for accessible autism services.