# Can novel telemedicine tools reduce disparities related to early identification of autism > **NIH NIH R21** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2020 · $237,000 ## Abstract PROJECT SUMMARY Although there is evidence that Autism Spectrum Disorder (ASD) can be accurately identified during the second year of life, many children in the United States are not diagnosed with ASD until after age four years. This is especially true for children from traditionally underserved communities, such as children from racial and ethnic minority groups, children whose parents report low levels of educational attainment, and children from rural geographies, whom providers might not even screen for autism concerns when they cannot subsequently link children to appropriate diagnostic services. This creates disparities in diagnostic identification and care that may have harmful, long term consequences for children, families, and service systems. Diagnostic visits offered by expert clinicians generally take place in tertiary care centers that present barriers to access of travel, time, and resources. These barriers may be extremely amenable to the use of telemedicine methods and practices. No explicit tools for conducting early telemedicine based consultations are currently available. This project introduces two novel telemedicine tools, the TELE-STAT and TELE-ASD-PEDS, for assessing autism risk in young children within their medical homes. These tools have explicitly selected as (a) the TELE-STAT represents a specific tool previously successfully utilized in-vivo within rapid triage and teleconsultation settings and to (b) the TELE-ASD-PEDS represents clinically-informed application of a computationally sophisticated analysis of observations tools used in comprehensive settings to diagnosis ASD. Under the supervision of an expert remote clinician, these tools can be used to coach parents and naïve pediatric providers via distance in how to elicit the behavioral features marked as most indicative of autism risk. We will test the accuracy of expert clinician telemedicine diagnosis utilizing these tools as part of evaluation. This work will be conducted in two stages. First, we will explore tool implementation, feasibility, acceptability, and preliminary accuracy in an already identified sample of young children with or without specific ASD concerns. Based on this pilot we will refined and adapt final versions of each. We will then implement and compare the tools across two groups of clinically referred children. We will do this in a simulated telemedicine diagnostic setting that will be immediately followed by a gold standard, in-person diagnostic evaluation with a different set of blinded clinicians. These tools have been designed to be low cost, to be compliant with privacy rules, and to meet the pragmatic and financial needs of many community provider networks. If successful, our telemedicine tools could provide methodologies that rapidly link children to ASD experts within practice locations where they are currently receiving care, in partnership with their existing providers. In turn, these children, who without such assessment may wai... ## Key facts - **NIH application ID:** 9841449 - **Project number:** 5R21MH118539-02 - **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER - **Principal Investigator:** Zachary E Warren - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $237,000 - **Award type:** 5 - **Project period:** 2018-12-20 → 2021-11-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9841449 ## Citation > US National Institutes of Health, RePORTER application 9841449, Can novel telemedicine tools reduce disparities related to early identification of autism (5R21MH118539-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9841449. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*