Early accurate identification and treatment of young children with Autism Spectrum Disorder (ASD) represents a pressing public health and clinical care challenge. Given mounting evidence that early, accurate diagnosis of ASD is possible and that very young children who receive intervention can demonstrate substantial gains in functioning, current American Academy of Pediatrics practice guidelines endorse formal ASD screening at 18 and 24 months of age. Ideally, this recommended screening would translate into early diagnosis and treatment for most children. Unfortunately, large numbers of children are still not screened for ASD; waits for specialized diagnostic assessment can be very long; and the average age of diagnosis in the US remains between 4 to 5 years of age. Furthermore, groups from traditionally underserved communities are even more likely to be diagnosed at later ages. Delays in accurate diagnosis contribute to high levels of family stress and limit access to ASD behavioral intervention services, which are increasingly recognized as very important to children?s functioning. Continuing work initiated in our Phase I project, the current project rigorously tests ?Autoscreen??a digital tool for rapid screening, diagnostic triage, referral, and treatment engagement of young children within community pediatric settings, with an embedded focus on reaching underserved populations. This tool fuses advanced computational strategies with expert knowledge and tools for ASD screening/assessment in order to realize a commercial tool that not only provides support for enhanced, reimbursable screening across diverse communities, but also establishes a clear decision pathway for early, accurate diagnostic triage and meaningful engagement in early treatment. In Phase II, we will rigorously evaluate the validity and broader clinical utility of Autoscreen. If successful, this innovative product could identify and link children with ASD to meaningful interventions at younger ages. We believe that a substantial potential market for such a system exists, given that commonly used developmental screening instruments identify roughly 8% of children as showing developmental risks in first years of life. In this capacity, our tool will ultimately be designed as a practical, feasible, and reimbursable health-screening module for wide-scale use in community pediatric settings.
Early accurate identification and treatment of young children with Autism Spectrum Disorder (ASD) represents a pressing public health and clinical care challenge. Continuing our Phase I work, the current project rigorously tests ?Autoscreen??a digital tool for rapid screening, diagnostic triage, referral, and treatment engagement of young children with ASD concerns within community pediatric settings. Autoscreen fuses advanced computational strategies with expert knowledge and tools for ASD screening. It offers community providers an accessible, commercially viable digital platform for enhanced, reimbursable screening across settings. It then gives providers decision pathways for early, accurate diagnostic triage, which could speed treatment initiation and improve outcomes.
