Autism Diagnostic E-Consults After PCP Training: A Practice-integrated Model to Expand Diagnostic Capacity

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Abstract
Objective: To evaluate the feasibility and clinical performance of an autism diagnostic e-consult model that embeds asynchronous psychologist review within primary care workflows to support diagnostic decision-making and triage by primary care providers (PCPs). Methods: Eight autism-trained PCPs across 4 clinics recorded brief diagnostic visits for children referred for autism evaluations. They submitted videos plus structured e-consult orders through a secure platform. Psychologists reviewed cases asynchronously and returned structured electronic health record (EHR) documentation indicating whether PCP impressions were supported and whether specialist follow-up was warranted. Diagnostic outcomes, triage decisions, child and visit characteristics, and observational scores were summarized using descriptive statistics, Wilcoxon rank sum tests, and χ 2 tests. Results: Across 81 e-consults over 21 months, children had a median age of 2.3 years; the median interval from initial concern to completed e-consult was 73 days, and all reviews were completed within 7 days. Follow-up testing was recommended for 31%. Concordance between PCP global impressions and psychologist review was high, with 74% of diagnosed children rated “obviously consistent with autism” by their PCP. Children diagnosed with autism had higher ASD-PEDS scores on both psychologist and PCP ratings than those not diagnosed. Children referred for specialist follow-up had lower ASD-PEDS scores, and were more likely to have PCP-endorsed medical/social complexity and phrase speech. Conclusion: Pairing PCP training with EHR-integrated e-consults may offer a pragmatic pathway compatible with emerging billing and implementation models for autism assessment in primary care. In this sample, the process was associated with high concordance between PCP and psychologist determinations and appeared to route more complex cases to appropriate specialist follow-up.
Funding Information
  • National Institutes of Health (U54 HD08321)
  • National Center for Advancing Translational Sciences (5UL1TR002243-03)

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