Evidence-based use of scalable biomarkers to increase diagnostic efficiency and decrease the lifetime costs of autism.

Challenges associated with the current screening and diagnostic process for autism spectrum disorder (ASD) in the US cause a significant delay in the initiation of evidence-based interventions at an early age when treatments are most effective. The present study shows how implementing a second-order diagnostic measure to high risk cases initially flagged positive from screening tools can further inform clinical judgment and substantially improve early identification. We use two example measures for the purposes of this demonstration; a saliva test and eye-tracking technology, both scalable and easy-to-implement biomarkers recently introduced in ASD research. Results of the current cost-savings analysis indicate that lifetime societal cost savings in special education, medical and residential care are estimated to be nearly $580,000 per ASD child, with annual cost savings in education exceeding $13.3 billion, and annual cost savings in medical and residential care exceeding $23.8 billion (of these, nearly $11.2 billion are attributable to Medicaid). These savings total more than $37 billion/year in societal savings in the US. Initiating appropriate interventions faster and reducing the number of unnecessary diagnostic evaluations can decrease the lifetime costs of ASD to society. We demonstrate the value of implementing a scalable highly accurate diagnostic in terms of cost savings to the US. LAY SUMMARY: This paper demonstrates how biomarkers with high accuracy for detecting autism spectrum disorder (ASD) could be used to increase the efficiency of early diagnosis. Results also show that, if more children with ASD are identified early and referred for early intervention services, the system would realize substantial costs savings across the lifespan.