PROJECT SUMMARY Autism Spectrum Disorder (ASD) affects up to 1 in 44 children in the United States, and its prevalence has increased over the past 10 years. Though early access to autism care improves outcomes, children of color and children from low-income families access care later and have unmet care needs. Though there is a broad understanding that contextual factors on the neighborhood, community, and state levels impact autism health care disparities, these factors are largely unexplored. In this proposed research, we will compile the most comprehensive and largest autism service use dataset ever, combining Medicaid claims from 16 states with community-level data from the Child Opportunity Index, as well as state education and health care policy data. We will use this powerful new data set to uncover modifiable determinants of child autism services use disparities. Analyses will focus on age of diagnosis as well as medication and behavioral therapy use. Then we will use findings to bring research to action, by engaging a consensus panel of community and research experts to suggest data-driven, feasible interventions based on study findings. We will also use our research to expand the diversity of the autism disparities research field, by sponsoring scholars who are under- represented in medicine and/or who have health disparities research interests, to use the resulting dataset to pursue additional data analyses. At the end of this project, we expect to have evidence-informed findings regarding which children access which services, which contextual factors affect services access, and which interventions can be deployed to address autism health inequities.

PROJECT NARRATIVE Autism Spectrum Disorder affects 1 and 44 children, and racial/ethnic disparities profoundly impact access to care. Though most research has focused on child and family factors, other contextual factors such as neighborhood, state health policy, and educational system determinants are likely drivers of structural disparities in care. In this research we propose to identify cross-sector, modifiable determinants of autism diagnostic and treatment disparities by combining Medicaid data with information on neighborhoods, state policy, and state educational data, and we will use a stakeholder-engaged consensus panel to turn data into actionable interventions.