First name
Whitney
Last name
Guthrie

Title

Short report: Prevalence of autism spectrum disorder in a large pediatric primary care network.

Year of Publication

2023

Number of Pages

13623613221147396

Date Published

01/2023

ISSN Number

1461-7005

Abstract

Historically, children from non-Hispanic Black and Hispanic backgrounds, those from lower-income families, and girls are less likely to be diagnosed with autism spectrum disorder. Under-identification among these historically and contemporaneously marginalized groups can limit their access to early, autism spectrum disorder-specific interventions, which can have long-term negative impacts. Recent data suggest that some of these trends may be narrowing, or even reversing. Using electronic health record data, we calculated autism spectrum disorder prevalence rates and age of first documented diagnosis across socio-demographic groups. Our cohort included children seen at young ages (when eligible for screening in early childhood) and again at least after 4 years of age in a large primary care network. We found that autism spectrum disorder prevalence was unexpectedly higher among Asian children, non-Hispanic Black children, children with higher Social Vulnerability Index scores (a measure of socio-economic risk at the neighborhood level), and children who received care in urban primary care sites. We did not find differences in the age at which autism spectrum disorder diagnoses were documented in children's records across these groups. Receiving primary care at an urban site (regardless of location of specialty care) appeared to account for most other socio-demographic differences in autism spectrum disorder prevalence rates, except among Asian children, who remained more likely to be diagnosed with autism spectrum disorder after controlling for other factors. We must continue to better understand the process by which children with autism spectrum disorder from traditionally under-identified and under-served backgrounds come to be recognized, to continue to improve the equity of care.

DOI

10.1177/13623613221147396

Alternate Title

Autism

PMID

36652297

Title

Autism Spectrum Disorder Screening During the COVID-19 Pandemic in a Large Primary Care Network.

Year of Publication

2022

Number of Pages

1384-1389

Date Published

12/2022

ISSN Number

1876-2867

Abstract

OBJECTIVE: To assess the impact of the COVID-19 pandemic on screening for autism spectrum disorder (ASD) and screening equity among eligible children presenting for well-child care in a large primary care pediatric network, we compared rates of ASD screening completion and positivity during the pandemic to the year prior, stratified by sociodemographic factors.

METHODS: Patients who presented for in-person well-child care at 16 to 26 months between March 1, 2020 and February 28, 2021 (COVID-19 cohort, n = 24,549) were compared to those who presented between March 1, 2019 and February 29, 2020 (pre-COVID-19 cohort, n = 26,779). Demographics and rates of completion and positivity of the Modified Checklist for Autism in Toddlers with Follow-up (M-CHAT/F) were calculated from the electronic health record and compared by cohort using logistic regression models.

RESULTS: Total eligible visits decreased by 8.3% between cohorts, with a greater decline in Black and publicly insured children. In the pre-COVID-19 cohort, 89.0% of eligible children were screened at least once, compared to 86.4% during the pandemic (P < 0.001). Significant declines in screening completion were observed across all sociodemographic groups except among Asian children, with the sharpest declines among non-Hispanic White children. Sociodemographic differences were not observed in screen-positive rates by cohort.

CONCLUSIONS: Well-child visits and ASD screenings declined across groups, but with different patterns by race and ethnicity during the COVID-19 pandemic. Findings regarding screen-completion rates should not be interpreted as a decline in screening disparities, given differences in who presented for care. Strategies for catch-up screening for all children should be considered.

DOI

10.1016/j.acap.2022.04.005

Alternate Title

Acad Pediatr

PMID

35460894

Title

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

Year of Publication

2022

Number of Pages

32

Date Published

05/2022

ISSN Number

1866-1955

Abstract

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients' clinical narratives.

METHODS: To address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method.

RESULTS: Through a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders.

CONCLUSION: Our ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making.

DOI

10.1186/s11689-022-09442-0

Alternate Title

J Neurodev Disord

PMID

35606697

Title

Consistency and inconsistency in caregiver reporting of vocabulary.

Year of Publication

2022

Number of Pages

81-96

Date Published

06/2022

ISSN Number

1547-5441

Abstract

Vocabulary checklists completed by caregivers are a common way of measuring children's vocabulary knowledge. We provide evidence from checklist data from 31 children with and without autism spectrum disorder. When asked to report twice about whether or not their child produces a particular word, caregivers are largely consistent in their responses, but where they are inconsistent, these inconsistencies affect verbs more than nouns. This difference holds both for caregivers of children with autism spectrum disorder and caregivers of typically-developing children. We suggest that caregivers may be less sure of their child's knowledge about verbs than nouns. This data converges with prior evidence comparing language samples of words children produce in a recorded interaction with checklist data, and it has implications for how researchers use checklist data in cases where the reliability of estimates of verb knowledge is critical.

DOI

10.1080/15475441.2021.1931233

Alternate Title

Lang Learn Dev

PMID

35603229

Title

Healthcare utilization among children with early autism diagnoses, children with other developmental delays and a comparison group.

Year of Publication

2021

Date Published

2021 May 26

ISSN Number

2042-6313

Abstract

To describe healthcare utilization patterns among children with autism (n = 1821), and compare these patterns to children with other developmental delays (DD; n = 12,336) and a population comparison (PC; n = 18,210) cohort. Retrospective study of administrative billing data. Children with autism had roughly six-times more annual outpatient visits as PC children and twice as many as children with DD. Children with autism were more likely than PC children to use nearly all services, but comparisons between the autism and DD cohorts were mixed. Children with autism were more likely to have psychiatry/psychology visits, 'other' specialty care visits and psychotropic prescriptions, but less likely to have pediatric specialty care visits, immunizations and some prescriptions. Findings reveal opportunities to streamline, coordinate or improve care for young children with autism, particularly for outpatient services, and to give caregivers appropriate anticipatory guidance about what to expect after an autism diagnosis.

DOI

10.2217/cer-2021-0056

Alternate Title

J Comp Eff Res

PMID

34037425

Title

Autism Spectrum Disorder Screening during the COVID-19 Pandemic in a Large Primary Care Network.

Year of Publication

2022

Date Published

2022 Apr 20

ISSN Number

1876-2867

Abstract

<p><strong>OBJECTIVE: </strong>To assess the impact of the COVID-19 pandemic on screening for autism spectrum disorder (ASD) and screening equity among eligible children presenting for well-child care in a large primary care pediatric network, we compared rates of ASD screening completion and positivity during the pandemic to the year prior, stratified by socio-demographic factors.</p>

<p><strong>METHODS: </strong>Patients who presented for in-person well-child care at 16-26 months between 3/1/2020 and 2/28/2021 (COVID-19 cohort, n=24,549) were compared to those who presented between 3/1/2019 and 2/29/2020 (pre-COVID-19 cohort, n= 26,779). Demographics and rates of completion and positivity of the Modified Checklist for Autism in Toddlers with Follow-up (M-CHAT/F) were calculated from the electronic health record (EHR) and compared by cohort using logistic regression models.</p>

<p><strong>RESULTS: </strong>Total eligible visits decreased by 8.3% between cohorts, with a greater decline in Black and publicly insured children. In the pre-COVID-19 cohort, 89.0% of eligible children were screened at least once, compared to 86.4% during the pandemic (p&lt;0.001). Significant declines in screening completion were observed across all socio-demographic groups except among Asian children, with the sharpest declines among non-Hispanic White children. Socio-demographic differences were not observed in screen-positive rates by cohort.</p>

<p><strong>CONCLUSIONS: </strong>Well-child visits and ASD screenings declined across groups, but with different patterns by race and ethnicity during the COVID-19 pandemic. Findings regarding screen-completion rates should not be interpreted as a decline in screening disparities, given differences in who presented for care. Strategies for catch-up screening for all children should be considered.</p>

DOI

10.1016/j.acap.2022.04.005

Alternate Title

Acad Pediatr

PMID

35460894

Title

The Early Screening for Autism and Communication Disorders: Field-testing an autism-specific screening tool for children 12 to 36 months of age.

Year of Publication

2021

Number of Pages

13623613211012526

Date Published

2021 May 07

ISSN Number

1461-7005

Abstract

<p><strong>LAY ABSTRACT: </strong>There is a critical need for accurate screening tools for autism spectrum disorder in very young children so families can access tailored intervention services as early as possible. However, there are few screeners designed for children 18-24 months. Developing screeners that pick up on the signs of autism spectrum disorder in very young children has proved even more challenging. In this study, we examined a new autism-specific parent-report screening tool, the Early Screening for Autism and Communication Disorders for children between 12 and 36 months of age. Field-testing was done in five sites with 471 children screened for communication delays in primary care or referred for familial risk or concern for autism spectrum disorder. The Early Screening for Autism and Communication Disorders was tested in three age groups: 12-17, 18-23, and 24-36 months. A best-estimate diagnosis of autism spectrum disorder, developmental delay, or typical development was made. Analyses examined all 46 items and identified 30 items that best discriminated autism spectrum disorder from the non-spectrum groups. Cutoffs were established for each age group with good sensitivity and specificity. Results provide preliminary support for the accuracy of the Early Screening for Autism and Communication Disorders as an autism-specific screener in children 12-36 months with elevated risk of communication delay or autism spectrum disorder.</p>

DOI

10.1177/13623613211012526

Alternate Title

Autism

PMID

33962531

Title

Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

Year of Publication

2020

Number of Pages

322

Date Published

2020 Dec 30

ISSN Number

1472-6947

Abstract

<p><strong>BACKGROUND: </strong>Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations.</p>

<p><strong>METHODS: </strong>We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied&nbsp;CLAMP, cTAKES, and MetaMap on 544 full-text articles and 20,408 abstracts from PubMed to extract&nbsp;ASD-related terms. We evaluated the predictive performance using precision, recall, and F1 score.</p>

<p><strong>RESULTS: </strong>We found that CLAMP has the best performance in terms of F1 score followed by cTAKES and then MetaMap. Our results show that CLAMP has much higher precision than cTAKES and MetaMap, while cTAKES and MetaMap have higher recall than CLAMP.</p>

<p><strong>CONCLUSION: </strong>The analysis protocols used in this study can be applied to other neuropsychiatric or neurodevelopmental disorders that lack well-defined terminology sets to describe their phenotypic presentations.</p>

DOI

10.1186/s12911-020-01352-2

Alternate Title

BMC Med Inform Decis Mak

PMID

33380331

Title

Person Ability Scores as an Alternative to Norm-Referenced Scores as Outcome Measures in Studies of Neurodevelopmental Disorders.

Year of Publication

2020

Number of Pages

475-480

Date Published

2020 11 01

ISSN Number

1944-7558

Abstract

<p>Although norm-referenced scores are essential to the identification of disability, they possess several features which affect their sensitivity to change. Norm-referenced scores often decrease over time among people with neurodevelopmental disorders who exhibit slower-than-average increases in ability. Further, the reliability of norm-referenced scores is lower at the tails of the distribution, resulting in floor effects and increased measurement error for people with neurodevelopmental disorders. In contrast, the person ability scores generated during the process of constructing a standardized test with item response theory are designed to assess change. We illustrate these limitations of norm-referenced scores, and relative advantages of ability scores, using data from studies of autism spectrum disorder and creatine transporter deficiency.</p>

DOI

10.1352/1944-7558-125.6.475

Alternate Title

Am J Intellect Dev Disabil

PMID

33211814

Title

Provider Responses to Positive Developmental Screening: Disparities in Referral Practices?

Year of Publication

2020

Date Published

2020 Sep 07

ISSN Number

1536-7312

Abstract

<p><strong>OBJECTIVES: </strong>Guidelines recommend universal screening for developmental concerns in young children in pediatric primary care, with referral to early intervention (EI) as early as possible for children with a positive screen. However, participation in EI differs by child race, ethnicity, language, and sex. This study evaluated disparities in rates of referral to EI and estimated the factors associated with referral before and immediately after a positive developmental screen.</p>

<p><strong>METHODS: </strong>Children seen in a large primary care network that has implemented universal developmental screening were included if they screened positive on the Survey of Well-being of Young Children (SWYC) Milestones during a 16- to 30-month well-child visit (n = 7358). Demographics, screening results, and referrals were extracted from the electronic health record.</p>

<p><strong>RESULTS: </strong>Among children who screened positive, 17.5% were already in EI, and 39.9% were referred to EI during the visit with positive screen; 42.5% were not referred. In adjusted regression, the following factors were associated with being in EI before the positive screen: lower SWYC score and being male, older, and White. The following factors were associated with new referral to EI during a visit with positive SWYC: having lower SWYC score or lower income and being male, older, and Black race.</p>

<p><strong>CONCLUSION: </strong>The finding that White children were more likely referred before developmental screening and non-White children more likely referred at the time of positive screen suggests that screening decreases disparities by increasing referral for children with developmental delays from traditionally underserved backgrounds.</p>

DOI

10.1097/DBP.0000000000000855

Alternate Title

J Dev Behav Pediatr

PMID

32909974

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