Microsoft Excel® is a popular graphing tool used by behavior analysts to visually display data. However, this program is not always friendly to the graphing conventions used by behavior analysts. For example, adding phase change lines has typically been a cumbersome process involving the insertion of line objects that do not move when new data is added to a graph. The purpose of this article is to describe a novel way to add phase change lines that move when new data is added and when graphs are resized.

This study examined variation in geographic access to Board Certified Behavior Analysts for children with autism spectrum disorder. Between March and May 2019, we integrated public data from the U.S. Department of Education’s Civil Rights Data Collection, Behavior Analyst Certification Board’s certificant registry, and U.S. Census. The study sample included all U.S. counties and county equivalents in 48 states and D.C. ( N = 3108). Using geographic information systems software, we assigned Board Certified Behavior Analysts to counties based on their residence, allocated children via school districts to counties, and generated per capita autism spectrum disorder/Board Certified Behavior Analyst ratios. We calculated the Getis-Ord G* statistics for each county and each ratio and compared counties in high-ratio clusters with counties in low-ratio clusters by socioeconomic variables. More than half of all counties had no Board Certified Behavior Analysts. Counties in the highest accessibility category had ⩽17.1 children with autism spectrum disorder per Board Certified Behavior Analyst ( n = 770), while counties in the lowest accessibility category had ⩾137.1 children with autism spectrum disorder per Board Certified Behavior Analyst ( n = 12). In all, 55 of the 129 counties with the highest autism spectrum disorder prevalence had no Board Certified Behavior Analysts. Higher accessibility counties were wealthier and had smaller uninsured populations. To improve geographic access, we must identify factors driving unequal distribution that can inform provider recruitment and retention efforts in underserved areas. Lay abstract This study looked at whether access to Board Certified Behavior Analysts for children with autism spectrum disorder is different between U.S. counties. The study included all U.S. counties and county equivalents in 48 states and D.C. ( N = 3108). Between March and May 2019, we combined data from the U.S. Department of Education’s Civil Rights Data Collection, Behavior Analyst Certification Board’s certificant registry, and U.S. Census. We assigned Board Certified Behavior Analysts to counties based on their address, matched children in school districts to counties, and determined how many children with autism spectrum disorder there were in a county compared with how many Board Certified Behavior Analysts there were in a county. The results show uneven numbers of Board Certified Behavior Analysts between U.S. counties. More than half of all counties had no Board Certified Behavior Analysts. National maps illustrate clusters of high and low accessibility to Board Certified Behavior Analysts. To improve access to Board Certified Behavior Analysts in underserved areas, we must identify what contributes to the differences in access.

To examine the relationship between geographic access to Board Certified Behavior Analysts (BCBAs) among children with autism spectrum disorder (ASD) and county sociodemographic factors and state policy, we integrated publicly available data from the U.S. Department of Education’s Civil Rights Data Collection, Behavior Analyst Certification Board’s certificant registry, and U.S. Census. The study sample included U.S. counties and county equivalents (e.g., parishes, independent cities) in 49 states and D.C. (N = 3040). Using GIS software, we assigned BCBAs to counties based on their residence, allocated children via school districts to counties, and generated per-capita children with ASD/BCBA ratios. We distributed counties into five categories based on these ratios: no BCBAs (reference), ≥ 31, 21–30, 11–20, > 0–10. We used a generalized logit model to conduct analyses. Highly affluent and urban counties had the highest access to BCBAs with odds ratio estimates for affluence ranging from 2.26 to 5.26. County-level poverty was positively associated with access, yet this relationship was moderated by urbanicity. Race-ethnicity and healthcare insurance coverage were negatively related to access. Other variables were not significant. Targeting non-urban and less affluent counties for provider recruitment and maintenance could most improve access to BCBAs. In addition to strategies specific to BCBAs for improving geographic access, traditional strategies used for other healthcare providers could be useful.

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