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Accepted for/Published in: JMIR Formative Research

Date Submitted: Apr 26, 2026
Date Accepted: Oct 8, 2026

The final, peer-reviewed published version of this preprint can be found here:

Integration of an FDA-Authorized Digital Autism Diagnostic Tool Into an Outpatient Developmental Pediatrics Workflow: Preliminary Quality Improvement Study

Resnik JB, Lane RT, Turnacioglu SO

Integration of an FDA-Authorized Digital Autism Diagnostic Tool Into an Outpatient Developmental Pediatrics Workflow: Preliminary Quality Improvement Study

JMIR Form Res 2026;10:e98697

DOI: 10.2196/98697

Integration of an FDA-Authorized Digital Autism Diagnostic Tool Into an Outpatient Developmental Pediatrics Workflow: A Preliminary Quality Improvement Study

  • Jenna B. Resnik; 
  • Rebecca T. Lane; 
  • Sinan O. Turnacioglu

ABSTRACT

Background:

Long wait times and specialist shortages delay autism spectrum disorder (ASD) diagnosis, often beyond the period when early intervention is most effective. Digital diagnostic tools may help improve diagnostic efficiency in outpatient settings.

Objective:

To evaluate the accuracy and clinical utility of a digital autism diagnostic application (Canvas Dx) when incorporated into an outpatient developmental pediatrics workflow.

Methods:

This quality improvement project assessed use of an FDA-authorized digital autism diagnostic application in an outpatient developmental pediatrics clinic. Children aged 18–72 months with caregiver or provider concern for developmental delay completed the assessment as part of routine clinical care. Diagnostic outputs were compared with specialist clinical diagnoses. Clinician and caregiver feedback was collected to assess usability and perceived efficiency.

Results:

A total of 28 children were included (mean age 52.2 months, SD 12.8; 25% female), with an autism prevalence of 67.9% (19/28) based on specialist diagnosis. The device generated a determinate result for 22 participants (78.6%). Among participants with determinate device results, sensitivity was 94.1% (95% CI 73.0–99.0) and specificity was 80.0% (95% CI 37.6–96.4%). Positive predictive value was 94.1% (95% CI 73.0–99.0), and negative predictive value was 80.0% (95% CI 37.6–96.4%), indicating strong agreement with specialist diagnostic determinations. Test accuracy and determinate result rates did not differ significantly by sex or race/ethnicity. Clinicians reported improved efficiency and insights during evaluation visits, and caregivers reported high satisfaction with the assessment process. Use of the tool supported timely diagnostic decision-making within routine outpatient workflows.

Conclusions:

Incorporation of a digital autism diagnostic application into outpatient developmental pediatrics practice appears feasible and may improve diagnostic efficiency while maintaining diagnostic accuracy.


 Citation

Please cite as:

Resnik JB, Lane RT, Turnacioglu SO

Integration of an FDA-Authorized Digital Autism Diagnostic Tool Into an Outpatient Developmental Pediatrics Workflow: Preliminary Quality Improvement Study

JMIR Form Res 2026;10:e98697

DOI: 10.2196/98697

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