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      Prevalence and Variation of Developmental Screening and Surveillance in Early Childhood

      research-article
      , PhD 1 , , , PhD 1 , , MSPH 2 , , MS 3 , , PhD 4
      JAMA Pediatrics
      American Medical Association

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          Abstract

          Importance

          Since 2001, the American Academy of Pediatrics has recommended universal developmental screening and surveillance to promote early diagnosis and intervention and to improve the outcomes of children with developmental delays and disabilities.

          Objective

          To examine the current prevalence and variation of developmental screening and surveillance of children by various sociodemographic, enabling, and health characteristics.

          Design, Setting, and Participants

          This cross-sectional analysis of the Health Resources and Services Administration’s 2016 National Survey of Children’s Health—a nationally representative survey of US children completed between June 2016 and February 2017—examined 5668 randomly selected children 9 through 35 months of age whose parent or caregiver responded to the address-based survey by mail or via a website. All analyses were weighted to account for the probability of selection and nonresponse and to reflect population counts of all noninstitutionalized US children residing in housing units.

          Main Outcomes and Measures

          Developmental screening was measured through a validated set of 3 items indicating receipt in the past year of parent-completed screening from a health care professional with age-appropriate content regarding language development and social behavior. Surveillance was determined by an item capturing verbal elicitation of developmental concerns by a health care professional.

          Results

          Of the estimated 9.0 million children aged 9 through 35 months, an estimated 30.4% (95% CI, 28.0%-33.0%) were reported by their parent or guardian to have received a parent-completed developmental screening and 37.1% (95% CI, 34.4%-39.8%) were reported to have received developmental surveillance from a health care professional in the past year. Characteristics associated with screening and/or surveillance that remained significant after adjustment included primary household language, family structure, household education, income, medical home, past-year preventive visit, child health status, and special health care needs. Having health care that meets medical home criteria was significantly associated with both developmental screening (adjusted rate ratio, 1.34; 95% CI, 1.13-1.57) and surveillance (adjusted rate ratio, 1.24; 95% CI, 1.08-1.42), representing an 8 to 9 absolute percentage point increase. State-level differences spanned 40 percentage points for screening (17.2% in Mississippi and 58.8% in Oregon) and surveillance (19.1% in Mississippi and 60.8% in Oregon), with approximately 90% of variation not explained by child and family characteristics.

          Conclusions and Relevance

          Despite more than a decade of initiatives, rates of developmental screening and surveillance remain low. However, state-level variation indicates continued potential for improvement. Systems-level quality improvement efforts, building on the medical home, will be necessary to achieve recommended screening and surveillance goals.

          Abstract

          This cross-sectional analysis uses the 2016 National Survey of Children’s Health to examine the current prevalence and variation of developmental screening and surveillance of children by various sociodemographic, enabling, and health characteristics.

          Key Points

          Question

          What are the latest national estimates of standardized developmental screening and surveillance, as well as individual and state variation, that may identify opportunities for improvement?

          Findings

          In this cross-sectional analysis of the 2016 National Survey of Children’s Health, an estimated 30.4% of children 9 through 35 months of age received a parent-completed developmental screening and 37.1% received developmental surveillance from a health care professional in the past year. State-level differences far exceeded those by child and family characteristics, spanning 40 percentage points for screening (17.2% in Mississippi and 58.8% in Oregon) and surveillance (19.1% in Mississippi and 60.8% in Oregon).

          Meaning

          Overall rates of developmental screening and surveillance remain low; however, substantial state-level variation underscores the importance and potential of quality improvement efforts.

          Related collections

          Most cited references29

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          Estimating model-adjusted risks, risk differences, and risk ratios from complex survey data.

          There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted risks, risk differences, and risk ratio estimates can be obtained directly from logistic regression models in the complex sample survey setting to yield population-based inferences. Complex sample survey designs typically involve some combination of weighting, stratification, multistage sampling, clustering, and perhaps finite population adjustments. Point estimates of model-adjusted risks, risk differences, and risk ratios are obtained from average marginal predictions in the fitted logistic regression model. The model can contain both continuous and categorical covariates, as well as interaction terms. The authors use the SUDAAN software package (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates, standard errors (via linearization or a replication method), confidence intervals, and P values for the parameters and contrasts of interest. Data from the 2006 National Health Interview Survey are used to illustrate these concepts.
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            Early intensive behavioral intervention (EIBI) for young children with autism spectrum disorders (ASD).

            The rising prevalence of autism spectrum disorders (ASD) increases the need for evidence-based behavioral treatments to lessen the impact of symptoms on children's functioning. At present, there are no curative or psychopharmacological therapies to effectively treat all symptoms of the disorder. Early intensive behavioral intervention (EIBI), a treatment based on the principles of applied behavior analysis delivered for multiple years at an intensity of 20 to 40 hours per week, is one of the more well-established treatments for ASD. To systematically review the evidence for the effectiveness of EIBI in increasing the functional behaviors and skills of young children with ASD. We searched the following databases on 22 November 2011: CENTRAL (2011 Issue 4), MEDLINE (1948 to November Week 2, 2011), EMBASE (1980 to Week 46, 2011), PsycINFO (1806 to November Week 3, 2011), CINAHL (1937 to current), ERIC (1966 to current), Sociological Abstracts (1952 to current), Social Science Citation Index (1970 to current), WorldCat, metaRegister of Controlled Trials, and Networked Digital Library of Theses and Dissertations. We also searched the reference lists of published papers. Randomized control trials (RCTs), quasi-randomized control trials, or clinical control trials (CCTs) in which EIBI was compared to a no-treatment or treatment-as-usual control condition. Participants must have been less than six years of age at treatment onset and assigned to their study condition prior to commencing treatment. Two authors independently selected and appraised studies for inclusion and assessed the risk of bias in each included study. All outcome data were continuous, from which standardized mean difference effect sizes with small sample correction were calculated. We conducted random-effects meta-analysis where possible, which means we assumed individual studies would provide different estimates of treatment effects. One RCT and four CCTs with a total of 203 participants were included. Reliance on synthesis from four CCTs limits the evidential base and this should be borne in mind when interpreting the results. All studies used a treatment-as-usual comparison group. We synthesized the results of the four CCTs using a random-effects model of meta-analysis of the standardized mean differences. Positive effects in favor of the EIBI treatment group were found for all outcomes. The mean effect size for adaptive behavior was g = 0.69 (95% CI 0.38 to 1.01; P < 0.0001). The mean effect size for IQ was g = 0.76 (95% CI 0.40 to 1.11; P < 0.0001). Three measures of communication and language skills all showed results in favor of EIBI: expressive language g = 0.50 (95% CI 0.05 to 0.95; P = 0.03), receptive language g = 0.57 (95% CI 0.20 to 0.94; P = .03), and daily communication skills g = 0.74 (95% CI 0.30 to 1.18; P = 0.0009). The mean effect size for socialization was g = 0.42 (95% CI 0.11 to 0.73; P = 0.0008), and for daily living skills was g = 0.55 (95% CI 0.24 to 0.87; P = 0.0005). Additional descriptive analyses of other aspects related to quality of life and psychopathology are presented. However, due to the inclusion of non-randomized studies, there is a high risk of bias and the overall quality of evidence was rated as 'low' using the GRADE system, which rates the quality of evidence from meta-analyses to determine recommendations for practice. There is some evidence that EIBI is an effective behavioral treatment for some children with ASD. However, the current state of the evidence is limited because of the reliance on data from non-randomized studies (CCTs) due to the lack of RCTs. Additional studies using RCT research designs are needed to make stronger conclusions about the effects of EIBI for children with ASD.
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              Prevalence of developmental delays and participation in early intervention services for young children.

              The objective of this study was to use a nationally representative longitudinal sample of children born in the United States in 2001 to estimate rates of eligibility for Part C early intervention, to estimate rates of access to services for developmental delays, and to examine factors that are associated with access to services. Data for this study were collected as part of the Early Childhood Longitudinal Study, Birth Cohort, which obtained data from participants when children were 9 and 24 months of age. Descriptive analyses were used to generate national estimates of the prevalence of developmental delays that would make children eligible for Part C services and rates of participation in early intervention services. Logistic regression analyses were conducted to examine whether child developmental delay, race, insurance availability, and poverty status were associated with the probability of receiving services. Results indicated that approximately 13% of children in the sample had developmental delays that would make them eligible for Part C early intervention. At 24 months, only 10% of children with delays received services. Children with developmental delays were more likely to receive services than those who do not have delays; black children were less likely to receive services than children from other ethnic and racial groups. The prevalence of developmental delays that make children eligible for Part C services is much higher than previously thought. Moreover, the majority of children who are eligible for Part C services are not receiving services for their developmental problems. Strategies need to be developed to monitor patterns of enrollment in early intervention services and reach out to more minority children, particularly black children.

                Author and article information

                Journal
                JAMA Pediatr
                JAMA Pediatr
                JAMA Pediatr
                JAMA Pediatrics
                American Medical Association
                2168-6203
                2168-6211
                9 July 2018
                September 2018
                13 August 2018
                9 July 2018
                : 172
                : 9
                : 857-866
                Affiliations
                [1 ]Maternal and Child Health Bureau, Health Resources and Services Administration, Rockville, Maryland
                [2 ]Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee
                [3 ]Department of Pediatrics, Oregon Health and Sciences University, Portland
                [4 ]Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                Author notes
                Article Information
                Accepted for Publication: April 18, 2018.
                Published Online: July 9, 2018. doi:10.1001/jamapediatrics.2018.1524
                Correction: This article was corrected on August 13, 2018, to add the Open Access paragraph to the acknowledgments section.
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2018 Hirai AH et al. JAMA Pediatrics.
                Corresponding Author: Ashley H. Hirai, PhD, Maternal and Child Health Bureau, Health Resources and Services Administration, 5600 Fishers Ln, Rockville, MD 20857 ( ahirai@ 123456hrsa.gov ).
                Author Contributions: Dr Hirai had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Hirai, Reuland, Bethell.
                Acquisition, analysis, or interpretation of data: Hirai, Kogan, Kandasamy, Bethell.
                Drafting of the manuscript: Hirai.
                Critical revision of the manuscript for important intellectual content: All authors.
                Statistical analysis: Hirai, Kandasamy, Bethell.
                Administrative, technical, or material support: Hirai.
                Supervision: Kogan, Bethell.
                Conflict of Interest Disclosures: None reported.
                Funding/Support: Dr Bethell was partially supported by Maternal and Child Health Measurement Research Network grant UA6MC26253 from the US Department of Health and Human Services, Health Resources and Services Administration, Maternal and Child Health Bureau.
                Role of the Funder/Sponsor: As part of the partial support to Dr Bethell, the funder/sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
                Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Health Resources and Services Administration.
                Additional Contributions: David Van Riper, MS, Spatial Analysis Core, Minnesota Population Center, provided expert consultation on the maps. He was not compensated for his contribution.
                Article
                poi180039
                10.1001/jamapediatrics.2018.1524
                6143066
                29987317
                367a6415-7809-481f-9b0d-d8393e5377e6
                Copyright 2018 Hirai AH et al. JAMA Pediatrics.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 25 January 2018
                : 17 April 2018
                : 18 April 2018
                Funding
                Funded by: US Department of Health and Human Services
                Funded by: Health Resources and Services Administration
                Funded by: Maternal and Child Health Bureau
                Categories
                Research
                Research
                Original Investigation
                Online First

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