Specialty training key to making accurate ASD diagnoses in primary care

Specialty training appears to improve the ability of community-based primary care clinicians to make accurate diagnoses of autism spectrum disorder (ASD) in most cases, as reported in a study.

For the study, researchers examined the usefulness of the Early Autism Evaluation (EAE) Hub system, a statewide network that provides specialized training and collaborative support to community-based primary care providers in the diagnosis of young children at risk of ASD.

A total of 126 children between 14 and 48 months of age were referred by EAE Hub clinicians for inclusion in the study. These children underwent blinded follow-up expert assessment that covered developmental level, adaptive behaviour, and ASD symptom severity. Agreement on categorical ASD diagnosis between EAE Hub clinician (index diagnosis) and ASD expert (reference standard) was the primary endpoint.

The mean age of the population was 2.6 years, with 77 percent being boys and 66 percent being non-Latinx White. There were 103 children (82 percent) who consistently received ASD diagnoses at the index and reference evaluations.

The sensitivity for diagnosing ASD at the index evaluation was 81.5 percent. The corresponding specificity was 82.4 percent, positive predictive value was 92.6 percent, and negative predictive value was 62.2 percent. Accuracy did not differ by EAE Hub clinician or site.

True positive and false negative (FN) ASD diagnoses significantly differed across measures of development, with true positive cases showing greater impairment (p<0.001 for all).

Diagnostic disagreements were predominately FN cases, in which EAE Hub clinicians had difficulty distinguishing between ASD and global developmental delay. Children with FN diagnoses were more likely to have a differential diagnostic and phenotypic profile.

The findings underscore the need for developing future population health solutions that address ASD diagnostic delays.