Primary Care Providers' Perceived Barriers and Needs for Support in Caring for Children with Autism

Health Care for Autistic Children: A Public Health Perspective

Autism has been the subject of large-scale public health investment. These investments are increasingly shifting toward mitigating the lifelong disability and impairment associated with autism. Key efforts include bolstering screening schedules, accelerating the path to diagnosis and early entry into evidence-based therapies, and providing preventive management of common co-occurring conditions. Enhancing their implementation will necessitate addressing neurodiversity and health equity. Pediatric primary care teams continue to be important stewards in population-level initiatives to promote autistic health. To thrive in this role, these providers will benefit from specific educational and logistical supports from the health care system.

Understanding autism diagnosis in primary care: Rates of diagnosis from 2004 to 2019 and child age at diagnosis

LAY ABSTRACT

The current demand for autism diagnostic services exceeds the ability of the workforce to assess and diagnose children in a timely manner. One solution may be to equip primary care providers (PCPs) with the tools and expertise needed to diagnose autism within their practice. PCPs are often trusted professionals who have many touchpoints with children during early development, in which they can identify early signs of autism. Recent initiatives have focused on bolstering PCPs' diagnostic capabilities; however, no studies have examined how the rates of autism diagnosis in primary care have changed over time. We aimed to evaluate whether autism diagnosis in primary care has changed over time and how diagnosis in primary care relates to a child's age at the time of diagnosis. We found that the likelihood of a child being diagnosed by a PCP decreased by about 2% with every passing year from 2004 to 2019 when accounting for demographic characteristics. In our sample, PCPs diagnosed children approximately 1 year earlier than non-PCPs (e.g., psychologists and psychiatrists). Further research is needed to understand why the proportion of children diagnosed by PCPs decreases over time. However, this decrease suggests more work is needed to get capacity-building initiatives into community primary care practice. Though we must continue to find effective ways to build community PCPs' ability to diagnose autism, the present findings support the crucial role PCPs can play in early autism diagnosis.

Medical Home Care and Educational Services for Children and Youth on the Autism Spectrum: A Scoping Review

This scoping review examined current evidence on medical home care and its association with educational services for children and youth on the autism spectrum. We searched five databases and grey literature resulting in 328 publications. Publications meeting inclusion criteria were mapped to medical home care component(s) addressed, type(s) of educational services and their strength and type of association. The Andersen Behavioral Model of Health Services Use was used to summarize predisposing, enabling, and need factors considered. Eighteen publications were reviewed, including eight practice/policy reports and ten original research publications. Medical home care components most addressed included family-centered care (n = 10), referrals (n = 16), and effective care coordination (n = 13). Seven publications also addressed multiple educational service types. Two of the five publications that established a significant association between medical home care components and educational services had mixed results, with one publication reporting a negative association and the other publication reporting a positive association. Challenges to medical home care and educational services were most categorized as enabling factors. Results suggest three areas for further investigation: (1) limited evidence on the strength and type of association between medical home care components and educational services; (2) limited use of population data sources; and (3) the need to consider a broader range of factors when examining their association.

How do primary care providers and autistic adults want to improve their primary care? A Delphi-study

LAY ABSTRACT

Autistic adults often encounter different types of healthcare barriers. Because autistic adults also have an increased risk for health problems, the aim of this study was to evaluate barriers and to explore how primary care providers and autistic adults want to improve their primary healthcare. In this co-created study, semi-structured interviews with three autistic adults, two parents of autistic children and six care providers were performed to evaluate barriers in Dutch healthcare. Next, in the survey-study (using the Delphi-method including controlled feedback in three consecutive questionnaires), 21 autistic adults and 20 primary care providers rated the impact of barriers and the usefulness and feasibility of recommendations to improve primary healthcare. In the interviews, 20 barriers in Dutch healthcare for autistic people were found. In the survey-study, the primary care providers rated the negative impact of most barriers lower than the autistic adults. This survey-study resulted in 22 recommendations to improve primary healthcare focused on: primary care providers (including education in collaboration with autistic people), autistic adults (including improvement of preparation for general practitioner-appointments) and organization of general practice (including improvement of continuity in care). In conclusion, primary care providers seem to view healthcare barriers as less impactful than autistic adults. In this co-created study, recommendations to improve primary healthcare for autistic adults were identified, based on the needs of autistic adults and primary care providers. These recommendations provide a basis for primary care providers, autistic adults and their support network to start conversations about, for example, strategies to improve primary care providers' knowledge, autistic adults' preparation for a general practitioner-appointment and organization of primary care.

A Multisystem Approach to Improving Autism Care

Children with autism face significant barriers to accessing evaluations and intervention services often because of confusing referral processes, lack of centralized coordination across organizations serving children with autism, insurance coverage gaps, multiyear waitlists for diagnostic services, and limited provider knowledge about autism. Racism and systemic inequities exist and persist in autism care across the United States. This article reviews targeted initiatives implemented by a multidisciplinary team to advocate for, and address barriers faced, by autistic children and their families in Washington, DC. We describe initiatives across multiple levels of the health care system including: 1. infrastructure-building initiatives (eg, coalition-building, policy, and advocacy); 2. enabling services (eg, population- and community-level supports that increase provider capacity to serve children's and families' needs); and 3. direct services (eg, innovative, gap-filling programs that directly serve children and families). We review outcomes and describe lessons learned.

Healthcare professionals' experiences of situations during a procedure with a child with autism spectrum disorder in the high-technology environment

BACKGROUND

High technological environments can be challenging for children with autism spectrum disorders (ASD), because they can be sensitive to new environments, new faces and changes in daily routines. Those children are frequent visitors in those settings, and due to their heightened healthcare needs and their comorbidities, it could constitute a challenge for healthcare professionals to encounter those children. Exploring the healthcare professionals' experiences can contribute to facilitate the procedure for a child with ASD.

METHOD

A qualitative descriptive retrospective design with a critical incident technique has been used to capture the situations. Twenty healthcare professionals were interviewed about situations affecting the procedure in the high-technology environments, defined as anaesthesia and radiology departments.

RESULT

The findings revealed both favourable situations and unfavourable situations affecting the procedure in the high-technology environment. The situations described by the healthcare professionals often involved their interactions with the child and the parents. The interactions were influenced by the parents' attitudes to the procedure and also the healthcare professionals and the parents' different expectations on the procedure. Other experiences described by the healthcare professionals were the unpredictability in different situations. Those situations were related to the child's unpredictable behaviour in those environments and also to the unpredictable effect of premedication provided to the child. Moreover, the result revealed the organizational prerequisites for facilitating a procedure, such as not feeling any time pressure when leading a child through a procedure.

CONCLUSIONS

Interactions between healthcare professionals, children with ASD and parents in the high-technology environment are complex. Unpredictability characterizes situations when leading a child with ASD through a procedure. This place demands on the healthcare professional, the environment and the organization.

Ending Developmental-Behavioral Pediatrics Faculty Requirement for Pediatric Residency Programs-Desperate Times Do Not Justify Desperate Actions

This Viewpoint discusses the issues at stake and potential adverse consequences of the Accreditation Council for Graduate Medial Education’s proposal to remove the requirement for pediatric training programs to have board-certified developmental-behavioral pediatrician faculty members.

ECHO autism adult healthcare: Training community clinicians to provide quality care for autistic adults

Autistic adults experience significant unmet healthcare needs, with opportunities for improvement in both the systems and the practitioners who serve this population. Primary care physicians/practitioners (PCPs) are a natural choice to provide comprehensive care to autistic adults but often lack experience in serving this population. This pilot study developed and tested an Extension for Community Healthcare Outcomes (ECHO) Autism model adapted from our previous work, focused specifically on training PCPs in best-practice care for autistic adults. The project was informed directly by the perspectives and preferences of autistic adults, caregivers, and PCPs. Two consecutive cohorts of PCPs participated in ECHO Autism Adult Healthcare sessions. Each cohort met 1 h twice a month for 6 months, with 37 PCPs (n = 20 in Cohort 1, and n = 17 in Cohort 2) participating. Based on findings from the first cohort, adjustments were made to refine the session preparation, curriculum, conduct of the ECHO, resources, and evaluation. After participation in the ECHO Autism program, PCP self-efficacy and satisfaction improved, while the number of perceived barriers did not change. Knowledge did not improve significantly in Cohort 1, but after adjustments to the training model, participants in Cohort 2 showed significant knowledge gains. While attention to systems of care is critical to addressing barriers in healthcare in the autistic population, the ECHO Autism Adult Healthcare model is feasible and holds promise for improving PCP satisfaction and self-efficacy in working with autistic adults.

Exploring the Experiences of Autistic Transgender and Non-Binary Adults in Seeking Gender Identity Health Care

Background

This study sought to obtain an in-depth understanding of autistic transgender and/or non-binary adults' experiences in accessing, or trying to access, gender identity health care (GIH). To our knowledge, no prior study researched this topic.

Methods

Through semi-structured interviews, we obtained the first-hand experiences of 17 participants. H.B. (cisgender, non-autistic) conducted a reflexive thematic analysis using an inductive approach, in collaboration with K.M., an autistic transgender disability community researcher, and under the supervision of S.K.K., a cisgender autistic autism researcher.

Results

Thematic analysis determined that poor knowledge of professionals, accessibility issues, and bureaucratic and economic barriers impacted participants' experiences when accessing GIH. Participants experienced a perceived lack of professional knowledge around autism and gender diverse health care needs, limited communication methods and accommodations, and misdiagnosis of mental health difficulties. Accessibility issues included unmet sensory needs, disruption to routine, and a lack of local provision. Further, participants shared that they struggled with unclear processes, standardization of care, long waiting lists, and confusing or inaccessible insurance coverage. Recommendations for improvements highlighted the need to listen to service users to positively impact their experiences in accessing GIH.

Conclusion

This study suggests that more training needs to be given to health care providers and professionals around autistic experience to help improve providers' competence in communication and providing person-centered accommodations. More training around gender diverse identities is needed, as well as increased knowledge on the co-occurrence of autism and transgender/non-binary identities, to positively impact patient experiences and help improve access to care.

Developing "Adulting for Health": Investigating the Health Needs of Neurodivergent Emerging Adults

INTRODUCTION

Neurodivergent emerging adults - defined as individuals between the ages of 18 and 30 with intellectual and/or developmental disabilities (e.g., attention-deficit hyperactivity disorder (ADHD), autism, cerebral palsy, learning disabilities, seizures, developmental delays, with or without intellectual impairment) and physical and/or sensory disabilities (e.g., blindness or hearing impairment) - experience poor mental and physical health outcomes. Existing interventions are insufficient because they are not based on the self-reported and developmental needs of this population.

METHODS

The current study is an exploratory pilot study that features a multidimensional health-based needs assessment of self-identified neurodivergent emerging adults with ADHD, learning disabilities, autism, and other conditions, mean (M) age = 22.8; standard deviation (SD) = 3.4; n = 26). This research used validated measures. The assessment - administered via Qualtrics to the participants in two sites - included the Mental Health Continuum-Short Form, Kessler-6 Psychological Distress Scale, Project EAT (Eating and Activity over Time)-IV (with the intuitive eating, weight-related control, emotional eating, and physical activity subscales), and an original health-focused needs assessment developed by interdisciplinary healthcare professionals and neurodivergent individuals.

RESULTS

The sample reported low positive mental health, with only 3% reportedly "flourishing." The sample also reported high psychological distress according to clinical and psychometric cut-off scores; varied intuitive eating and weight-control behaviors and attitudes; and distinct needs related to integrating the principles of health promotion into daily life, navigating the healthcare system, and learning from healthcare professionals. Based on these findings, we present an initial conceptualization of "Adulting for Health," a potential virtual education program to promote health-related knowledge and capacities for this population.

CONCLUSIONS

The results from this exploratory pilot study can be incorporated into existing programs and spur efforts to develop and test new interventions that can ameliorate health disparities for neurodivergent emerging adults.

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.

Automatic design and optimization of educational space for autistic children based on deep neural network and affordance theory

In recent years, the incidence of autistic children has shown rapid growth worldwide. The rapid development of education and rehabilitation institutions for autistic children is of great significance to the rehabilitation of this group. However, the research on indoor space environments and functional facilities for autistic children in China is still in its infancy. Reasonably and effectively, zoning the education and rehabilitation space for autistic children can promote better communication and learning between autistic children and rehabilitation therapists and effectively promote the rehabilitation progress of autistic children. However, the existing education and rehabilitation space for autistic children has some problems, such as unscientific indoor partition, indoor space layouts mainly relying on manual work, heavy workload and low efficiency. Therefore, it is of great research value and practical significance to explore the intuitive design and optimization of the education and rehabilitation space layout for autistic children. This study first evaluates and optimizes the educational space for autistic children based on the affordability theory. Then, this study proposes a layout recommendation algorithm based on deep learning, which is used to improve the layout efficiency of the education and rehabilitation space for autistic children and realize real-time online layout. The scene information is digitized in binary code. The segmentation and layout network models are constructed through bidirectional long short-term memory (LSTM) to discover the long segment pre-segmentation of house type and obtain the layout results. The word embedding algorithm is used to abstract the cross features between each vector segment, and the dimension of the feature matrix is reduced to improve the speed and accuracy of the layout scheme recommendation. The experimental results show that our method can learn the design rules from the data set and has achieved better results than the existing methods. This study provides an adequate theoretical basis and design reference for the research of residential education space for autistic children.

Machine learning determination of applied behavioral analysis treatment plan type

BACKGROUND

Applied behavioral analysis (ABA) is regarded as the gold standard treatment for autism spectrum disorder (ASD) and has the potential to improve outcomes for patients with ASD. It can be delivered at different intensities, which are classified as comprehensive or focused treatment approaches. Comprehensive ABA targets multiple developmental domains and involves 20-40 h/week of treatment. Focused ABA targets individual behaviors and typically involves 10-20 h/week of treatment. Determining the appropriate treatment intensity involves patient assessment by trained therapists, however, the final determination is highly subjective and lacks a standardized approach. In our study, we examined the ability of a machine learning (ML) prediction model to classify which treatment intensity would be most suited individually for patients with ASD who are undergoing ABA treatment.

METHODS

Retrospective data from 359 patients diagnosed with ASD were analyzed and included in the training and testing of an ML model for predicting comprehensive or focused treatment for individuals undergoing ABA treatment. Data inputs included demographics, schooling, behavior, skills, and patient goals. A gradient-boosted tree ensemble method, XGBoost, was used to develop the prediction model, which was then compared against a standard of care comparator encompassing features specified by the Behavior Analyst Certification Board treatment guidelines. Prediction model performance was assessed via area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The prediction model achieved excellent performance for classifying patients in the comprehensive versus focused treatment groups (AUROC: 0.895; 95% CI 0.811-0.962) and outperformed the standard of care comparator (AUROC 0.767; 95% CI 0.629-0.891). The prediction model also achieved sensitivity of 0.789, specificity of 0.808, PPV of 0.6, and NPV of 0.913. Out of 71 patients whose data were employed to test the prediction model, only 14 misclassifications occurred. A majority of misclassifications (n = 10) indicated comprehensive ABA treatment for patients that had focused ABA treatment as the ground truth, therefore still providing a therapeutic benefit. The three most important features contributing to the model's predictions were bathing ability, age, and hours per week of past ABA treatment.

CONCLUSION

This research demonstrates that the ML prediction model performs well to classify appropriate ABA treatment plan intensity using readily available patient data. This may aid with standardizing the process for determining appropriate ABA treatments, which can facilitate initiation of the most appropriate treatment intensity for patients with ASD and improve resource allocation.

The implementation of the screening tool for autism in toddlers in Part C early intervention programs: An 18-month follow-up

LAY ABSTRACT

The early detection of autism spectrum disorder can lead to access to autism spectrum disorder-specific services that have been shown to have a large impact on a child's overall development. Although a stable diagnosis of autism spectrum disorder can be made by age 2 years, most children are not diagnosed until much later. To address this issue, this study examined the effectiveness of training Part C Early Intervention providers to use an interactive autism spectrum disorder screening tool, the Screening Tool for Autism in Toddlers. Sixty-nine providers attended a 1-day training workshop on the use of the Screening Tool for Autism in Toddlers. After the workshop, providers reported increased knowledge about recognizing the early signs of autism spectrum disorder, and about 45% of the providers reported using the Screening Tool for Autism in Toddlers with families in their caseloads 18 months after the training. These results suggest that the Screening Tool for Autism in Toddlers is feasible for use within Early Intervention settings. In addition, they suggest that specific providers might serve as a screening "point-person," rather than expecting the Screening Tool for Autism in Toddlers to be used by all providers. Future research should aim to identify specific characteristics of agencies or providers that might be best suited for using the Screening Tool for Autism in Toddlers.

Primary Care Clinician and Child Characteristics Impacting Autism Surveillance

Early detection of autism provides access to early intervention and subsequently fewer lifelong challenges. However, disparities in screening have been associated with socioeconomic status (SES) and race, and disparities in surveillance have been associated with clinician knowledge and beliefs about autism identification. The present study examines associations between demographic variables and clinician beliefs, and agreement between screening results and clinician surveillance. Surveillance included activities used by the primary care clinicians (PCCs) to assess risk for autism. PCCs reported their beliefs about autism screening and identification, their sex, race, years in practice, and racial distribution of their patient population. Children's demographic information was also collected. PCCs identified children as having, or not having, an increased likelihood of autism, and parents of children completed an autism screener. Agreement between screening and surveillance results were examined across PCC, practice, and child demographics. Higher confidence in autism knowledge and screening resources, female PCC sex, and majority White practice patient demographics all predicted agreement between screening and surveillance. Female child sex and higher maternal education also predicted agreement between screening and surveillance. These findings highlight the importance of PCC screening beliefs and child and PCC demographics on the autism identification process.

Autism Spectrum Disorder: The New Asthma?

While autism spectrum disorder (ASD) has traditionally been diagnosed in specialty care, rising prevalence rates have strained specialist capacity and created significant diagnostic bottlenecks. With long wait times for specialist evaluations, pediatricians are increasingly being asked to play a greater role in identifying, diagnosing, and managing ASD within the medical home. In this commentary we draw parallels between the challenges pediatricians faced two decades ago learning how to manage pediatric asthma in the medical home, to those faced today in the field of primary care ASD management. Reflecting on the lessons learnt in primary care asthma management may help us construct a roadmap towards a higher and more consistent standard of ASD primary care for patients and their families.

Separate scoring algorithms for specific identification priorities optimize the screening properties of the Screening Tool for Autism in Toddlers (STAT)

The Screening Tool for Autism in Toddlers (STAT) is a validated stage-2 autism spectrum disorder (ASD) screening measure that takes 20 minutes to administer and comprises 12 play-based items that are scored according to specific criteria. This study examines an expanded version (STAT-E) that includes the examiner's subjective ratings of children's social engagement (SE) and atypical behaviors (AB) in the scoring algorithm. The sample comprised 238 children who were 24-35 months old. The STAT-E assessors had limited ASD experience to mimic its use by community-based non-specialists, and were trained using a scalable web-based platform. A diagnostic evaluation was completed by clinical experts who were blind to the STAT-E results. Logistic regression, ROC curves, and classification matrices and metrics were used to determine the screening properties of STAT-E when scored using the original STAT scoring algorithm versus a new algorithm that included the SE and AB ratings. Inclusion of the SE and AB ratings improved positive risk classification appreciably, while the specificity declined. These results suggest that the STAT-E using the original STAT scoring algorithm optimizes specificity, while the STAT-E scoring algorithm with the two new ratings optimizes the positive risk classification. Using multiple scoring algorithms on the STAT may provide improved screening accuracy for diverse contexts, and a scalable web-based tutorial may be a pathway for increasing the number of community providers who can administer the STAT and contribute toward increased rates of autism screening.

Autism presentation in female and Black populations: Examining the roles of identity, theory, and systemic inequalities

LAY ABSTRACT

Although the prevalence of autism has been rising in recent years, disparities in diagnosis still remain. Female and Black populations in the United States are diagnosed later, are more likely to have an intellectual disability, and are excluded from research as well as services designed for autistic individuals. Autistic Black girls are effectively invisible in the current scientific literature. Intersectional theory, which looks at a person as a whole, examines models that are inclusive toward diverse gender, ability, and racial/ethnic backgrounds. This theory may be a useful approach to clinical and research work with autism so that practitioners may be most effective for the whole population of autistic people. The authors recommend research focusing on inclusion of autistic populations with intellectual disability and research studies that include evaluations as part of the procedure. Clinically, the authors recommend a focus on screening all young children for autism and improving provider knowledge in working with diverse autistic populations.

The impact of autism-related training programs on physician knowledge, self-efficacy, and practice behavior: A systematic review

LAY ABSTRACT

Autism spectrum disorder is estimated to impact 1.5 million children and almost 5.5 million adults. However, most physicians do not receive training on how to provide care to this increasingly large group of people. After performing a systematic review of the literature and screening over 4,500 unique articles focused on the effectiveness of autism-specific training programs designed for physicians and physician trainees, we determined that 17 studies met the pre-determined criteria for inclusion in this systematic review. The results reported by these studies suggest that by completing specialized training programs related to autism, physicians were more knowledgeable on topics related to the condition, more confident in their ability to provide care to autistic individuals, and more likely to screen their patients for autism spectrum disorder. However, further studies with higher quality data are needed to validate these findings and provide additional insight on the ability of these programs to improve physician behavior and patient outcomes. We are therefore advocating that medical educators develop and evaluate specialized autism training programs with an increased focus on improving physician behavior related to all aspects of providing care to autistic people.

Reducing Barriers to Autism Screening in Community Primary Care: A Pragmatic Trial Using Web-Based Screening

OBJECTIVE

To determine whether an intervention addressing both logistical and knowledge barriers to early screening for autism spectrum disorder (ASD) increases evidence-based screening during 18-month well-child visits and primary care providers' (PCPs') perceived self-efficacy in caring for children with ASD.

METHODS

Forty-six PCPs from 10 diverse practices across four counties in Washington State participated. PCPs attended a 2-hour training workshop on early recognition and care for toddlers with ASD and use of a REDCap-based version of the Modified Checklist for Autism in Toddlers-Revised with Follow-up (webM-CHAT-R/F) that provided automated presentation and scoring of follow-up questions. Data were collected at baseline and 6 months following each county's training window. PCPs' screening methods and rates and perceived self-efficacy regarding ASD care were measured by self-report and webM-CHAT-R/F use was measured via REDCap records.

RESULTS

At follow-up, 8 of the 10 practices were using the webM-CHAT-R/F routinely at 18-month visits. The proportion of PCPs reporting routine M-CHAT screening increased from 82% at baseline to 98% at follow-up (16% increase, 95% confidence interval [CI] 3%-28%; McNemar exact P = .02). The proportion using the M-CHAT-R/F follow-up interview questions increased from 33% to 82% (49% increase, 95% CI 30%-68%, exact McNemar test, P < .001). Significant increases in self-efficacy were found for all seven areas assessed (Ps ≤ .008).

CONCLUSIONS

This brief intervention increased PCPs' self-reported valid use of the M-CHAT-R/F at 18 months and their self-efficacy regarding ASD care. Combining educational information with a web-based ASD screen incorporating the M-CHAT-R/F follow-up questions may increase universal ASD screening with improved fidelity.

Feasibility and impact of integrating an artificial intelligence-based autism spectrum disorder diagnosis aid into the primary care ECHO Autism STAT Model: protocol for a prospective observational study (Preprint)

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

Physician Perspectives on Severe Behavior and Restraint Use in a Hospital Setting for Patients with Autism Spectrum Disorder

Hospitals, with many features that can evoke severe behavior in patients with autism spectrum disorder (ASD), often use restraint as a behavior management strategy. Prior research on restraint in patients with ASD has primarily focused on children or specific departments. Twenty-five physicians and medical trainees from an urban teaching hospital participated in discussions about experiences managing severe behavior in patients with ASD across the lifespan. Twenty themes emerged from thematic analysis of participant transcripts. The five most salient themes included: lack of procedural knowledge with restraint implemented by other hospital professionals; alternative strategies to manage severe behavior; negative perceptions of restraint; helpful role of caregivers; and limited experience treating patients with ASD, and critical need for training in function-based management.

Effect of Brief Training to Identify Autism Spectrum Disorder During Toddler Well-Child Care Visits

OBJECTIVE

To examine the effect of a brief Enhanced training using the information-motivation-behavior (IMB) change model on improving providers' surveillance rates and accuracy of autism spectrum disorder (ASD) detection.

METHOD

Toddlers (n = 5,672) were screened for ASD during their pediatric well-child visits. Pediatric providers (n = 120) were randomized to receive Enhanced (incorporating components of the IMB model) or Control training. Providers indicated whether they had an ASD concern at each well-child visit. Toddlers who were positive on any screener and/or whose provider indicated ASD concern were invited for a diagnostic evaluation. Differences in provider-indicated ASD concerns before and after training were evaluated using log-linear analyses.

RESULTS

The Enhanced training did not have a significant effect on provider-endorsed ASD concerns (p = 0.615) or accuracy of endorsing concerns (p = 0.619). Providers in the Control training showed a significant reduction in indicating whether or not they had concerns after the training (from 71.9% to 64.3%), which did not occur in the Enhanced group. The Enhanced training led to more frequent endorsements of language (χ2 = 8.772, p = 0.003) and restricted and repetitive behavior (χ2 = 7.918, p = 0.005) concerns for children seen after training.

CONCLUSION

Provider training had limited impact on ASD surveillance, indicating the importance of using formal screening instruments that rely on parent report during well-child visits to complement developmental surveillance. Future research should examine whether providers who indicate specific concerns are more likely to accurately refer children for ASD evaluations.

Where are US outpatient mental health facilities that serve children with autism spectrum disorder? A national snapshot of geographic disparities

LAY ABSTRACT

There has been a rise in the observed prevalence of autism spectrum disorder among children. Existing studies show the share of counties with a treatment facility that offers care for children with autism spectrum disorder. However, no estimates exist of the share of US outpatient mental health treatment facilities that provide services for children with autism spectrum disorder. We identified key facility-level characteristics in offering mental health care for children with autism spectrum disorder. We used a telephone survey to contact almost all outpatient mental health treatment facilities in the contiguous United States. We asked the facilities if they provided mental health care for children with autism spectrum disorder. We took the results of this survey and estimated multivariable regressions to examine county- and facility-level predictors of offering services. We found that over half (50.3%) of the 6156 outpatient facilities reported offering care for children with autism spectrum disorder. Non-metro counties, counties with a lower percentage of non-White residents, counties with a higher percentage of uninsured residents, and counties with a higher poverty rate had fewer outpatient mental health treatment facilities providing care for children with autism spectrum disorder. Facilities accepting Medicaid as a form of payment, offering telehealth, and private for-profit facilities were more likely to provide services for children with autism spectrum disorder. Because only half of outpatient mental health treatment facilities offer care for children with autism spectrum disorder, public health officials and policymakers should do more to ensure that this vulnerable population has access to mental health services.

Generosity of state insurance mandates and growth in the workforce for autism spectrum disorder

LAY ABSTRACT

To improve access to health services for children with autism spectrum disorder, US states have passed laws requiring health insurers to cover autism-related care, commonly known as state insurance mandates. However, the features of mandates differ across states, with some state laws containing very generous provisions and others containing very restrictive provisions such as whether the mandates include children aged above 12 years, whether there is a limit on spending, and whether there are restrictions on the types of services covered. This study examined the relationship between generosity of mandates and growth in the health workforce between 2003 and 2017, a period during which 44 states passed mandates. We found that states that enacted more generous mandates experienced significantly more growth in board-certified behavioral analysts who provide behavioral therapy as well as more growth in child psychiatrists. We did not find differences in the growth of pediatricians, which is a less specialized segment of the workforce. Our findings were consistent across eight different mandate features and suggest that the content of legislation may be as important as whether or not legislation has been passed in terms of encouraging growth in the supply of services for children with autism spectrum disorder.