Document Type
Article
Publication Date
10-21-2025
Abstract
Background: Pediatric specialist shortages and rapidly rising autism prevalence rates have compelled primary care clinicians to consider playing a greater role in the autism diagnostic process. The ECHO Autism: Early Diagnosis Program (EDx) prepares clinicians to screen, evaluate, differentiate, diagnose, and provide longitudinal care for children with autism in primary care settings. Canvas Dx is a prescription-only Software as a Medical Device designed to support clinical diagnosis or rule out of autism, including in primary care settings. It is authorized by the Food and Drug Administration for use, in conjunction with clinical judgment, in 18‐ to 72-month-olds with indicators of developmental delay.
Objective: This study aims to assess the feasibility and impact of integrating the device into the ECHO Autism: EDx workflow. Time from the first clinical question of developmental delay to autism diagnosis is the primary endpoint. Secondary endpoints explore clinician and caregiver experience of device use.
Methods: Children aged 18 to 72 months with concern for developmental delay indicated by either a caregiver or health professionals were eligible to participate in this prospective observational study. Experienced ECHO Autism: EDx clinicians were recruited to evaluate the inclusion of the device as part of their diagnostic evaluations. Outcome data were collected via a combination of electronic questionnaires, standard clinical care record reviews, and analysis of device outputs. Institutional review board approval was provided by the University of Missouri-Columbia (project number 2075722).
Results: Eighty children and 7 clinicians completed the study. On average, time from clinical concern at study enrollment to final autism diagnosis was 39.22 days, compared to 180‐ to 264-day waits at adjacent specialist referral centers. The vast majority (93%, 50/54) of caregivers reported being satisfied with the ECHO Autism: EDx plus device evaluation their child received and endorsed that they would recommend it to others and that they felt comfortable using the device. The device produced determinate autism predictions or rule-outs for 52.5% of participants, and in all cases, these were consistent with the final clinical determination. Participating clinicians reported that device use was feasible and reduced several challenges associated with their previous diagnostic process; however, they noted it did not obviate the need for additional structured observation in every case.
Conclusions: The ECHO Autism: EDx plus device workflow offers considerable time savings compared to specialty center referral and was strongly endorsed by caregiver participants. Embedding the device into the ECHO Autism: EDx workflow was feasible and helped streamline several workflow efficiencies. Clinicians still utilized their training and application and interpretation of Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria when formulating the diagnosis for indeterminate cases.
Recommended Citation
Sohl K, Linstead E, Heinz K, Lledo EE, Brewer Curran A, Mahurin M, Nanclares-Nogués V, Salomon C, Seal M, Taraman S. Integration of an Artificial Intelligence–Based Autism Diagnostic Device into the ECHO Autism Primary Care Workflow: Prospective Observational Study. JMIR Form Res 2025;9:e80733. https://doi.org/10.2196/80733
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The authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
This article was originally published in JMIR Formative Research, volume 9, in 2025. https://doi.org/10.2196/80733