The impact of a delay to early intensive behavioral intervention on educational outcomes for a cohort of medicaid-enrolled children with autism

Abstract

Introduction. Early Intensive Behavioral Interventions (EIBI) is an applied behavior analysis approach that can be effective for remediating autism spectrum disorder (ASD) symptoms for some individuals (Reichow, 2012). From a population perspective, timely access to early intervention services is assumed to be important for facilitating long term positive educational outcomes. Stakeholders report, however, long waitlists for services. The range of effects of EIBI service delay on educational outcomes for children with ASD is unknown. The purpose of the study was to examine how EIBI service delays relate to later educational and placement outcomes for Medicaid-enrolled children diagnosed with ASD. Three research questions guided the analyses conducted in this study: 1) what is the main effect of delay to EIBI on educational outcomes, 2) what is the main effect of average hours of EIBI per week on educational outcomes and 3) does the average delay to start EIBI differ by county or region within Minnesota? Method. The study utilized cross-systems administrative data to create a cohort of 3 to 5 year olds who received a diagnosis of ASD between 2008 and 2010. This cohort was matched with Minnesota Department of Education (MDE) records from the 2010-2014 academic year (94.5% match rate). Delay to EIBI services in months was calculated by subtracting the date of ASD diagnosis (ICD-9 CM 299.0) from the first billing date associated with an EIBI service provider. Educational outcomes evaluated included primary educational ASD diagnosis, instructional placement, Minnesota Comprehensive Assessment-III (MCA) scores and special education service hours. Descriptive analyses, Generalized Estimating Equations regressions models (GEE), and Geographic Information Systems (GIS) were used to evaluate data from 667 children with ASD (82% Male, 72% White). Results. The average delay to EIBI was 8.99 months (SD=10.63 mos). At follow-up, 94% of the cohort qualified for special education with 70% of them receiving an ASD diagnosis in school. About 40% of the children received a general education placement. The GEE models calculated showed that the main effect of delay to EIBI was significant and the odds of receiving a general education placement and participating in the MCA- tests was decreased if the child experienced a longer delay to start EIBI. Additionally, the odds of receiving a primary educational diagnosis of ASD increased for every increase in delay. The results further suggest that the main effect of average hours of EIBI per week was significantly associated with ASD diagnosis in school, MCA participation, and special education service hours. Finally, children who resided in the metro area (M=9.89 mos, SD=11.24 mos) had a larger average delay to EIBI compared to children who resided in the non-metro area (M=7.00 mos, SD=8.78 mos). Discussion. With increases in diagnoses of ASD over the past decade, it is imperative that children and families have early access to high quality services. Children who were diagnosed younger and experienced a shorter delay had better educational outcomes overall. This study is limited in that the reason a delay may have occurred is unknown and the educational outcomes are limited. In sum, there are waitlists and delays to services which may be detrimental to children’s educational outcomes. Future research should investigate if a telehealth delivery model (i.e., video-conferencing) could supplement the gap in services early on and the cost-effectiveness of timely service.