ECHO (Extension for Community Healthcare Outcomes) Autism STAT: A Diagnostic Accuracy Study of Community-Based Primary Care Diagnosis of Autism Spectrum Disorder.

OBJECTIVE: Children can be reliably diagnosed with autism spectrum disorder (ASD) by a highly trained clinician as early as 12 to 24 months of age, but recent estimates indicate that the average age of diagnosis is 4.4 years. We hypothesized that trained primary care physicians and practitioners can reliably and accurately diagnose children 14 to 48 months with unambiguous symptoms of ASD. METHODS: Through this diagnostic accuracy study, 20 patients diagnosed with ASD by clinicians trained through the ECHO (Extension for Community Healthcare Outcomes) Autism STAT program participated in an independent gold-standard evaluation at a regional autism center. Caregiver perceptions of the diagnostic process were also assessed. RESULTS: Of the 20 patients who received a diagnosis of ASD by a trained clinician and completed the study, 19 diagnoses were confirmed by a gold-standard evaluation. Caregivers indicated that undergoing diagnosis in their local community rather than an autism specialty center was helpful (4.8/5 on a 5-point Likert scale, n = 19). Results of this study demonstrate that primary care clinicians can be trained to reliably diagnose ASD in children 14 to 48 months with unambiguous symptoms. CONCLUSION: Diagnosis in the primary care setting may lead to earlier diagnosis and quicker connection to evidence-based therapies and interventions. Given the potential impact of increasing access to high-quality diagnostic services, the role of primary care clinicians in the diagnosis of ASD should be further evaluated.

Implementing the WHO caregivers skills training program with caregivers of autistic children via telehealth in rural communities.

Background: For families with autistic children living in rural areas, limited access to services partly results from a shortage of providers and extensive travel time. Telehealth brings the possibility of implementing alternative delivery modalities of Parent Mediated Interventions (PMIs) with the potential to decrease barriers to accessing services. This study aimed to evaluate the feasibility and acceptability of implementing the World Health Organization-Caregivers Skills Training program (WHO-CST) via an online, synchronous group format in rural Missouri. Methods: We used a mixed methods design to collect qualitative and quantitative data from caregivers and program facilitators at baseline and the end of the program, following the last home visit. Caregivers of 14 autistic children (3-7 years), residents of rural Missouri, completed nine virtual sessions and four virtual home visits. Results: Four main themes emerged from the focus groups: changes resulting from the WHO-CST, beneficial aspects of the program, advantages and disadvantages of the online format, and challenges to implementing the WHO-CST via telehealth. The most liked activity was the demonstration (36%), and the least liked was the practice with other caregivers. From baseline to week 12, communication skills improved in both frequency (p < 0.05) and impact (p < 0.01), while atypical behaviors decreased (p < 0.01). For caregivers' outcomes, only confidence in skills (p < 0.05) and parental sense of competence (p < 0.05) showed a positive change. Conclusion: Our results support the feasibility of implementing the WHO-CST program via telehealth in a US rural setting. Caregivers found strategies easy to follow, incorporated the program into their family routines, and valued the group meetings that allowed them to connect with other families. A PMI such as the WHO-CST, with cultural and linguistic adaptations and greater accessibility via telehealth-plays an essential role in closing the treatment gap and empowering caregivers of autistic children.

Feasibility and Impact of Integrating an Artificial Intelligence-Based Diagnosis Aid for Autism Into the Extension for Community Health Outcomes Autism Primary Care Model: Protocol for a Prospective Observational Study.

BACKGROUND: The Extension for Community Health Outcomes (ECHO) Autism Program trains clinicians to screen, diagnose, and care for children with autism spectrum disorder (ASD) in primary care settings. This study will assess the feasibility and impact of integrating an artificial intelligence (AI)-based ASD diagnosis aid (the device) into the existing ECHO Autism Screening Tool for Autism in Toddlers and Young Children (STAT) diagnosis model. The prescription-only Software as a Medical Device, designed for use in children aged 18 to 72 months at risk for developmental delay, produces ASD diagnostic recommendations after analyzing behavioral features from 3 distinct inputs: a caregiver questionnaire, 2 short home videos analyzed by trained video analysts, and a health care provider questionnaire. The device is not a stand-alone diagnostic and should be used in conjunction with clinical judgment. OBJECTIVE: This study aims to assess the feasibility and impact of integrating an AI-based ASD diagnosis aid into the ECHO Autism STAT diagnosis model. The time from initial ECHO Autism clinician concern to ASD diagnosis is the primary end point. Secondary end points include the time from initial caregiver concern to ASD diagnosis, time from diagnosis to treatment initiation, and clinician and caregiver experience of device use as part of the ASD diagnostic journey. METHODS: Research participants for this prospective observational study will be patients suspected of having ASD (aged 18-72 months) and their caregivers and up to 15 trained ECHO Autism clinicians recruited by the ECHO Autism Communities research team from across rural and suburban areas of the United States. Clinicians will provide routine clinical care and conduct best practice ECHO Autism diagnostic evaluations in addition to prescribing the device. Outcome data will be collected via a combination of electronic questionnaires, reviews of standard clinical care records, and analysis of device outputs. The expected study duration is no more than 12 months. The study was approved by the institutional review board of the University of Missouri-Columbia (institutional review board-assigned project number 2075722). RESULTS: Participant recruitment began in April 2022. As of June 2022, a total of 41 participants have been enrolled. CONCLUSIONS: This prospective observational study will be the first to evaluate the use of a novel AI-based ASD diagnosis aid as part of a real-world primary care diagnostic pathway. If device integration into primary care proves feasible and efficacious, prolonged delays between the first ASD concern and eventual diagnosis may be reduced. Streamlining primary care ASD diagnosis could potentially reduce the strain on specialty services and allow a greater proportion of children to commence early intervention during a critical neurodevelopmental window. TRIAL REGISTRATION: ClinicalTrials.gov NCT05223374; https://clinicaltrials.gov/ct2/show/NCT05223374. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37576.

Project Extension for Community Health Outcomes (ECHO) Autism: A Successful Model to Increase Capacity in Community-Based Care.

Individuals with autism spectrum disorder (ASD) struggle to access high-quality health care due to the shortage of trained providers. ECHO (Extension for Community Healthcare Outcomes) Autism is a unique educational program that allows ASD experts to provide knowledge and skills to professionals in local communities to deliver evidence-based care to children with ASD and their families. The model teaches clinicians how to screen and diagnose ASD, as well as manage common co-occurring medical and mental health issues. ECHO Autism is particularly useful for addressing the complex needs of children with ASD and reducing disparities often present in rural and underserved communities. The model can be disseminated globally due to its flexibility in accommodating local and regional differences in social norms and constructs. This article provides an overview of the format of the ECHO Autism model, data supporting the model's efficacy, and discusses future research directions.

Facilitator Reflections on Shared Expertise and Adaptive Leadership in ECHO Autism: Center Engagement.

INTRODUCTION: Project Extension for Community Healthcare Outcomes (ECHO) is used to increase provider capacity in a wide range of health care specialties. ECHO Autism: Center Engagement is a program that promotes improvement in autism care by improving the management of autism care centers. The program's focus brought experienced clinicians together as both facilitators and participants in an ECHO series. ECHO Autism: Center Engagement facilitators devised a reflective writing exercise to prospectively study their experience leading this new curriculum. METHODS: Drawing on a qualitative thematic analysis of longitudinal reflective writing exercises from seven "Hub Team" facilitators, we describe how ECHO leaders cultivate a learning environment that emphasizes shared learning and acknowledges the expertise of ECHO participants. RESULTS: The analysis generated three main themes: (1) Hub Team facilitators valued reciprocal exchange with Spoke sites, a theme we name "shared learning," (2) Hub Team facilitators demonstrated high levels of awareness about their facilitation styles, and (3) Hub Team facilitators cultivated an interactional style they described as "all teach, all learn." DISCUSSION: Examining the experiences of ECHO facilitators produces qualitative accounts of continuing professional development that may not be captured in other program evaluation approaches. In the case of ECHO Autism: Center Engagement, facilitators cultivated an environment of shared learning, which acknowledged the expertise of both facilitators and participants. These findings are pertinent for scholars of continuing education in health professions who lead educational programs where participants and facilitators have high levels of overlap in their areas of expertise and years of experience.

ECHO Autism: Integrating Maintenance of Certification with Extension for Community Healthcare Outcomes Improves Developmental Screening.

OBJECTIVE: Recent estimates indicate that most pediatricians do not consistently meet the American Academy of Pediatrics developmental screening guidelines, contributing to the delay of vital evaluations and interventions for autism spectrum disorder (ASD). Our objective was to evaluate the utility of Maintenance of Certification (MOC) Quality Improvement (QI) training designed to improve developmental screening rates in underserved, rural primary care practices. Trainings on best screening practices were disseminated to primary care providers (PCPs) through Extension for Community Healthcare Outcomes (ECHO) Autism, a virtual learning network. METHOD: Across 2 cohorts, 24 PCPs were enrolled in MOC Part 4 training modules delivered through the ECHO Autism QI Learning Network. Throughout the 12 months of enrollment, PCPs reported information on general and ASD-specific developmental screenings conducted at 18- and 24-month well-child visits. A 1-year follow-up was conducted to assess the maintenance of screening rates. RESULTS: Baseline rates for general and ASD-specific developmental screenings were 53.3% and 68.3%, respectively. By the end of the 12-month learning module, screening rates increased significantly for general development (88.6%) and ASD-specific screenings (99.0%). At the 1-year follow-up, the rate for general developmental screening was 96.7% and for ASD-specific screening was 97.1%. CONCLUSION: Maintenance of Certification Part 4 training delivered through the ECHO Autism QI Learning Network was found to be incentivizing and highly effective in shaping and maintaining PCP developmental screening practices. Improved screening rates show promise in decreasing time to critical developmental evaluations, interventions, and resources. Our methodology is likely transferable to other ECHO communities and may facilitate expedient implementation of best practice standards in primary care.

ECHO Autism STAT: Accelerating Early Access to Autism Diagnosis.

Although early diagnosis of autism is critical for promoting access to early intervention, many children experience significant diagnostic delays. Shortages of healthcare providers, limited capacity at autism centers, and geographic and socioeconomic challenges contribute to these delays. The current pilot study examined the feasibility of a new model for training community-based primary care providers (PCPs) in underserved areas in screening and diagnosis of young children at highest risk for autism. By combining hands-on training in standardized techniques with ongoing virtual mentorship and practice, the program emphasized both timely diagnosis and appropriate referral for more comprehensive assessment when necessary. Results indicated improvements in PCP practice and self-efficacy, and feasibility of the model for enhancing local access to care.

ECHO Autism.

Children with autism spectrum disorder (ASD) have complex medical problems, yet they are at high risk for unmet health care needs. Primary care providers are perfectly positioned to meet these needs; however, they often lack training in ASD. This pilot project developed and tested a new model for training primary care providers in best-practice care for ASD using the Extension for Community Healthcare Outcomes (ECHO) framework. The 6-month ECHO Autism pilot project consisted of 12 biweekly clinics focused on screening and identification of ASD symptoms and management of medical and psychiatric comorbidities. Participants completed measures of practice behavior and self-efficacy in screening and management of children with ASD at baseline (pretest) and after 6 months of ECHO Autism (posttest). Statistically significant improvements were observed in self-efficacy, in adherence to ASD screening guidelines, and in use of ASD-specific resources. Participants also reported high satisfaction with the program.