Zachary Warren

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.

Objective: This study focused on in-home use of a tele-assessment tool for autism diagnosis in young children, the TELE-ASD-PEDS (TAP). Psychometric properties, caregiver experiences, and perceptions of feasibility were examined among families likely to experience barriers to in-person evaluation. Methods: One hundred eighty-two children between 18 and 42 months of age were recruited because of positive screening, primary care concerns, or early intervention referral. All participants completed initial tele-assessment including the TAP. Approximately 2 weeks later, a second visit was conducted: 92 were randomized to a repeat TAP administration by telehealth and 90 were randomized to an in-person evaluation. Caregivers completed surveys regarding challenges with technology and satisfaction with telehealth assessment. Results: Overall, 77% of the sample was diagnosed with autism spectrum disorder (n = 140). There were few diagnostic disagreements (n = 10, 6%) between initial and second evaluations, with disagreements equally distributed between second visit type. Diagnostic outcomes (autism vs no autism) agreed between telehealth and in-person evaluation for 94% of cases, kappa = 0.82. Outcomes agreed between 2 telehealth visits for 94% of cases, kappa = 0.84. Test-retest reliability of total TAP scores across 2 administrations was strong, intraclass correlation coefficient = 0.85. Very few caregivers reported challenges with technology during telehealth appointments (<6%); 92% reported that there was nothing they would change about the telehealth visit. Examiners also reported high satisfaction with telehealth assessments. Conclusion: In-home use of the TAP is valid, reliable, feasible, and acceptable to caregivers. Findings support the continued use of telehealth assessment for autism in toddlers, which can reduce disparities in access to timely diagnostic services.

The wait for ASD evaluation dramatically increases with age, with wait times of a year or more common as children reach preschool. Even when appointments become available, families from traditionally underserved groups struggle to access care. Addressing care disparities requires designing identification tools and processes specifically for and with individuals most at-risk for health inequities. This work describes the development of a novel telemedicine-based ASD assessment tool, the TELE-ASD-PEDS-Preschool (TAP-Preschool). We applied machine learning models to a clinical data set of preschoolers with ASD and other developmental concerns (n = 914) to generate behavioral targets that best distinguish ASD and non-ASD features. We conducted focus groups with clinicians, early interventionists, and parents of children with ASD from traditionally underrepresented racial/ethnic and linguistic groups. Focus group themes and machine learning analyses were used to generate a play-based instrument with assessment tasks and scoring procedures based on the child’s language (i.e., TAP-P Verbal, TAP-P Non-verbal). TAP-P procedures were piloted with 30 families. Use of the instrument in isolation (i.e., without history or collateral information) yielded accurate diagnostic classification in 63% of cases. Children with existing ASD diagnoses received higher TAP-P scores, relative to children with other developmental concerns. Clinician diagnostic accuracy and certainty were higher when confirming existing ASD diagnoses (80% agreement) than when ruling out ASD in children with other developmental concerns (30% agreement). Utilizing an equity approach to understand the functionality and impact of tele-assessment for preschool children has potential to transform the ASD evaluation process and improve care access.

Background: Expedient access to early intervention (EI) systems has been identified as a priority for children with developmental delays, identified disabilities, and other special health care needs. Despite the mandated availability of EI, it remains challenging for families to navigate referral processes and establish appropriate services. Such challenges disproportionately affect families from traditionally underserved communities. Mobile health apps can improve clinical outcomes, increase accessibility to health services, and promote adherence to health-related interventions. Though promising, the implementation of apps within routine care is in its infancy, with limited research examining the components of what makes an effective app or how to reach families most impacted by inequities in health care delivery. Objective: In study 1, we conducted focus groups to access a broad range of perspectives on the process of navigating the EI system, with the dual goals of identifying ways in which a patient-facing app might facilitate this process and identifying barriers to use with traditionally underrepresented and underserved groups. In study 2, focus group findings informed the development of a patient-facing app, which was subsequently tested with a pilot sample of 5 families. Methods: In study 1, the focus groups included 29 participants from 4 shareholder groups. Targeted sampling was used to recruit participants from traditionally underrepresented groups. Focus group questions sought information about barriers families experience as they navigate the EI system, ideal features of a patient-facing app designed to track family engagement with the EI system, and potential barriers. Focus group procedures were informed by the Consolidated Framework for Implementation Research framework. In study 2, a pilot app was developed. The app was tested with a sample of 5 families of young children involved in the EI system. Families provided information on app functionality and usability. Results: Qualitative analysis revealed a desire for increased communication and information about the process of accessing EI services, potential utility of an app for communication purposes, and clear recommendations for app features. Insights from focus groups were used to inform the development of the Family on Track app and related implementation supports. App features included survey customization, timing and delivery of prompts, and questions related to barriers and service satisfaction. Implementation supports include a visual guide for app installation, resources related to common family questions, and availability of study personnel to guide families through installation and provide ongoing support. Field testing provided preliminary information about app usability, including identifying future directions. Conclusions: The results of this study could support the development of a new way for the EI system to communicate and connect with families, provide families with a means to communicate satisfaction and frustration, and access the supports they need to be active participants in their child’s care.

BACKGROUND Expedient access to early intervention (EI) systems has been identified as a priority for children with developmental delays, identified disabilities, and other special health care needs. Despite the mandated availability of EI, it remains challenging for families to navigate referral processes and establish appropriate services. Such challenges disproportionately affect families from traditionally underserved communities. Mobile health apps can improve clinical outcomes, increase accessibility to health services, and promote adherence to health-related interventions. Though promising, the implementation of apps within routine care is in its infancy, with limited research examining the components of what makes an effective app or how to reach families most impacted by inequities in health care delivery. OBJECTIVE In study 1, we conducted focus groups to access a broad range of perspectives on the process of navigating the EI system, with the dual goals of identifying ways in which a patient-facing app might facilitate this process and identifying barriers to use with traditionally underrepresented and underserved groups. In study 2, focus group findings informed the development of a patient-facing app, which was subsequently tested with a pilot sample of 5 families. METHODS In study 1, the focus groups included 29 participants from 4 shareholder groups. Targeted sampling was used to recruit participants from traditionally underrepresented groups. Focus group questions sought information about barriers families experience as they navigate the EI system, ideal features of a patient-facing app designed to track family engagement with the EI system, and potential barriers. Focus group procedures were informed by the Consolidated Framework for Implementation Research framework. In study 2, a pilot app was developed. The app was tested with a sample of 5 families of young children involved in the EI system. Families provided information on app functionality and usability. RESULTS Qualitative analysis revealed a desire for increased communication and information about the process of accessing EI services, potential utility of an app for communication purposes, and clear recommendations for app features. Insights from focus groups were used to inform the development of the Family on Track app and related implementation supports. App features included survey customization, timing and delivery of prompts, and questions related to barriers and service satisfaction. Implementation supports include a visual guide for app installation, resources related to common family questions, and availability of study personnel to guide families through installation and provide ongoing support. Field testing provided preliminary information about app usability, including identifying future directions. CONCLUSIONS The results of this study could support the development of a new way for the EI system to communicate and connect with families, provide families with a means to communicate satisfaction and frustration, and access the supports they need to be active participants in their child’s care.

The COVID‐19 pandemic has posed unique challenges for families and caregivers, as well as for autism‐focused clinicians, who are faced with providing a thorough and accurate evaluation of children's specific needs and diagnoses in the absence of in‐person assessment tools. The shift to telehealth assessments has challenged clinicians to reconsider approaches and assumptions that underlie the diagnostic assessment process, and to adopt new ways of individualizing standard assessments according to family and child needs. Mandates for physical distancing have uncovered deficiencies in diagnostic practices for suspected autism and have illuminated biases that have posed obstacles preventing children and families from receiving the services that they truly need. This Commentary outlines several considerations for improving diagnostic practices as we move forward from the current pandemic and continue to strive to build an adaptable, sustainable, equitable, and family‐centered system of care.Lay Summary: Physical distancing and the abrupt end to in‐person services for many children on the autism spectrum has forced clinicians to examine the existing challenges with autism spectrum disorder (ASD) diagnostic assessment and consider things they want to keep and things that should be changed in the years ahead. New approaches such as telehealth both alleviated and exacerbated existing disparities, and brought into stark focus the importance of equitable and timely access to family‐centered care. This commentary suggests ways of improving clinical practices related to ASD assessment to continue along this path.