Building Capacity for Community Pediatric Autism Diagnosis: A Systemic Review of Physician Training Programs

OBJECTIVES

Training primary care providers to provide diagnostic assessments for autism spectrum disorder (ASD) decreases wait times and improves diagnostic access. Outcomes related to the quality of these assessments and the impacts on system capacity have not been systematically examined. This systematic review identifies and summarizes published studies that included ASD diagnostic training for primary care providers (PCPs) and aims to guide future training and evaluation methods.

METHODS

Systematic searches of electronic databases, reference lists, and journals identified 6 studies that met 3 inclusion criteria: training for PCPs, community setting, and training outcome(s) reported. These studies were critically reviewed to characterize (1) study design, (2) training model, and (3) outcomes.

RESULTS

All studies were either pre-post design or nonrandomized trials with a relatively small number of participants. There was considerable heterogeneity among studies regarding the training provided and the program evaluation process. The most evaluated outcomes were access to autism diagnosis and accuracy of diagnosis.

CONCLUSION

Training PCPs to make ASD diagnoses can yield high diagnostic agreement with specialty teams' assessments and reduce diagnostic wait times. Current data are limited by small sample size, poor to fair quality study methodology, and heterogenous study designs and outcome evaluations. Evidence is insufficient to draw conclusions about the overall effects of training PCPs for ASD diagnostic assessments. Since further research is still needed, this review highlights which outcomes are relevant to consider when evaluating the quality of ASD assessments across the continuum of approaches.

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.