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Lead investigators:
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Sarabeth Broder-Fingert, Apurv Soni 

The status quo:
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Early autism diagnosis and treatment are associated with many long-term benefits for children and their families. Traditional approaches to autism diagnosis require time-intensive evaluations and multiple visits with a specialist. Unfortunately, the waitlist time for these appointments is often years-long; the cost may not be covered by insurance; and caregivers must be able to take multiple days off from work. Postponed checkups and other disruptions due to the COVID-19 pandemic have further exacerbated diagnostic delays.

What we study:
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A novel AI-powered diagnostic approach provides primary care physicians with the opportunity to remove barriers to accessing autism care. CanvasDx (developed by Cognoa, Inc.) is an FDA-authorized Software as Medical Device (SaMD) that aids physicians in diagnosing autism. To produce a diagnostic evaluation, CanvasDx requires three sources of input: a caregiver questionnaire (5 minutes to complete), two caregiver videos (up to 5 minutes each), and a healthcare provider questionnaire (10 minutes to complete). In the FIND-ASD (Feasibility of Integrating Novel Diagnostics for Autism Spectrum Disorders) study, we will assess the feasibility and acceptability of CanvasDx in pediatric outpatient practices in the UMass Memorial Health System.

How we innovate:
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FIND-ASD aims to administer CanvasDx to 100 children in the UMass Memorial Health System who are awaiting specialist evaluation. Key study measures will include:

Caregiver assessment. 

The length of time from study invitation to completion of caregiver assessment

Study engagement. 

Evaluation of sociodemographic factors associated with study engagement

Physician input completion rate.  

The rate of completion of the physician input required by CanvasDx

Join this study

If you are interested in learning more and participating in this study, please contact our study team.


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FIND-ASD: Reducing waitlist times for autism diagnosis