Transcript Epidemiology of CSHCN - Association of University Centers
Early Identification of Developmental Delays or Concerns to Receipt of Early Intervention Services Among Infants and Toddlers: A Systematic Review
Brian Barger, PhD+^ Cathy Rice, PhD
+National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention (CDC) ^Disability Research and Dissemination Center University of South Carolina
AUCD November 11, 2014
Early Identification
Early identification of developmental concerns allows families to seek intervention during the crucial period of early child brain, body, and behavioral development
It is never too late to start supports and services for a person in need.
Starting as early as possible is best.
Overview
Individuals with Disabilities Act (IDEA) Part C – Funding for early intervention (EI) support services for infants and toddlers with developmental delays and their families (IDEA, 2004; PL 108-466) – Each state establishes coordinated EI systems including: Child Find Referral Assessment Individualized Family Service Plan (IFSP) professional development systems (Blackman, Healy, & Ruppert, 1992; Bricker et al., 2013)
Early Identification is a Public Health Concern
Part C Child Find is a major system used to identify children early for EI services, however: Many children with developmental disabilities (DD) are not identified as early as they could be Only
30%
(Palfrey, 1987) of children with
DD
identified
before Kindergarten
EI can significantly impact acquisition of important life skills for many children with disabilities (Guralnick, 1997; 2011; NPDC, 2014)
•
1 in 6
children will have a developmental disability
•
1 in 68
with autism*
(Boyle et al., 2011; CDC, 2014) *Autism Spectrum Disorder (ASD)
Early Identification is a Process
Part C and early identification literature
Much research on the effectiveness of EI – Including Part C Much research on the effectiveness of developmental screeners (Macy, 2012) Very little research on Part C systems tracking data from Child Find to assessment to entrance to EI
Purpose of Study
Characterize peer-reviewed literature on reporting data following populations of young children with developmental risk through the process of early identification leading to Part C EI services
Systematic Review: Search
Search Engines: – ERIC, PsycINFO, Proquest, and Web of Science Search terms: –
individuals with disabilities education act
,
part c
,
part h
,
child find
,
title V
,
108-446
,
105-17
,
99 457
,
101-476
,
102-119
, and
105-17
– paired with:
monitor*
,
surv*
,
eligib*
,
screen*
,
ancil*
,
assess*
,
interven*
,
established risk
,
category one
,
presumed eligibility
,
established condition
or
presumptive eligibility
.
Systematic Review: Search
Ancestral searches from studies considered for the final analysis January 1986 to July 2013.
– January 1986 IDEA was re-authorized with the Part C addition
Model of Extracted Data
Study Inclusion Criteria
Published since 1986 Cited Part C of IDEA in – abstracts or – literature reviews At least two of the key steps from the Model – (A) the total population of children monitored – – (B) children screened positive, referred for and/or received a developmental evaluation; or (C) children deemed or assessed eligible for and/or actually receiving Part C EI services
Study Exclusion Criteria
Pre 1986 publication Psychometric studies Professional opinions/training
Search Flow Chart (Final N = 39)
Study Codes
Setting – Primary – Specialized – All data broken down according to these classifications
Study Codes
Descriptive – Years of publication – – Sample age range State/region
Study Codes
Descriptive – sample type Cohort/epidemiological population, Convenience/community samples, or Other/unreported
Study Codes
Descriptive – analysis focus Systems level Measurement/individual level (excluded), or Both
Study Codes
Descriptive – Centrality of reference to IDEA law Minor – One reference Moderate – Two references Major – Three + references
Study Codes
Descriptive – Journal/academic-field Developmental/disability Education/intervention Medical
Study Codes
Model systems – Systems following total populations of children from screening or referral to actually entering EI Primary model Specialized model – Criteria: Recent publication (i.e., since 2006) Presence of
all 3 major model data components
Data on the number of children who entered EI Not national survey data.
Results: Trends for primary and specialized
39 studies identified Years of publication:1987 to 2012, – majority post- 2006. Individual states or multiple states weighted for national representation – Community service systems Population based sampling
Results: Trends for primary and specialized
Two aspects of model Most children birth to three years – A few reporting on children older than three Journals – Medical (N = 22) – Developmental/disability (N = 6) – Education/intervention (N = 11)
Recent increase in citations from medical journals
Results: Trends for primary setting studies
Historically understudied Primarily from medical literature Major to moderate focus on IDEA Part C law
Results: Trends for secondary setting studies
Historically most prevalent From medical and education literature Minor focus on IDEA Part C law
Meta-analysis of model steps
Fixed effects analysis – Note: descriptive of studies only and not to be used to infer actual population estimates Estimated proportions of children (redundant studies omitted) – – Screened/referred 4 primary 9 secondary Assessed eligible or entered into EI 5 primary studies 10 secondary studies
Meta-analysis of model steps;
FE meta analysis-- not to be used to infer actual population estimates
Primary Setting Specialized Setting
19% Screened Positive or Referred 58% Screened Positive or Referred 13% Assessed Entered EI 31% Assessed Eligible or Entered
Results: Primary Model Data System
• Pregnancy to Early Life Longitudinal (PELL) Data Project from Massachusetts (e.g., Clements et al., 2008) • Links data systems from • Birth records • • • • Death records Hospital records Part C Other social services
Results: Primary Model Data System
• Partners • • • Boston University School of Public Health Massachusetts (MA) Department of Public Health Centers for Disease Control and Prevention
Results: Secondary Model Data System
• • • Developmental Tracking Infant Progress Stateside (TIPS) (NE; Jackson & Needleman, 2007) Tracks NICU survivors 3 follow up levels • • • Level 1 low risk infants • Developmental screening with validated screeners Level 2 moderate risk infants (e.g., low birth weight) • Brief developmental assessments Level high-risk infants (e.g., very low birth weight) • Comprehensive developmental assessment
Results: Secondary Model Data System
• Partners • • NE Departments of Education Health and Human Services
Discussion: Historical trends
Historically understudied Increasing interest from medical community in Part C Child Find – APA 2006 policy statement – ACA
Discussion: Meta-analysis
Higher rates of children screened positive/referred and assessed eligible/entered – National average for eligible/entered ~3% (Department of Education’s Office of Special Education Programs, 2010)
Discussion: Meta-analysis
Several factors driving our numbers – – Large N PELL study from “broad” state (MA) More longitudinal versus “point in time” studies National numbers to congress are “point in time” Infant Toddler Coordinators Association argues for longitudinal “birth cohorts – Report numbers more in line with our meta analysis – Reminder: Our numbers are descriptive of the studies reported and
may not
be used to infer the proportions of children screened positive, referred to, assessed by, or ultimately receiving services from Part C systems
Discussion: Partnership opportunities
Many partners interested in this issue and may have dovetailing policies – Medical AAP NICU ACA – – Social Work Child Abuse Prevention and Treatment Act (CAPTA) – Requires Part C referrals Head Start Requires developmental screening
Discussion: Model Systems
Primary and Secondary models – Both- Importance of federal, state, and local
partnerships
– MA PELL- importance of
data linkage
across systems – NE TIPS- importance of
developmental screening
Discussion: non-Model Systems
Other non-model studies had great insights including the importance of: – Community planning and communication, developing staff “buy in,” and systems training (Shannon & Anderson, 2008) “on the ground” focus – Partnering with similarly missioned organizations (i.e., Head Start; Sinclair, 1993; Peterson et al., 2004)
Limitations and Future Directions
Limitations – Part C mentioned in lit review or abstract – FE analyses limits reports of proportions to this data only – extrapolations beyond this report are inappropriate – National surveys Future directions – – Data systems (electronic health records) National Surveys of Children’s Health – Learn the Signs. Act Early. Ambassadors
Collaborators
Becky Wolf and LTSAE team Suzanne McDermott, Margaret Turk, Deborah Salzberg, USC-DRDC Christina Anne Simmons, UGA
References
Blackman, J. A., Lindgren, S. D., Hein, H. A., & Harper, D. C. (1987). Long-term surveillance of high-risk children. Archives of Pediatrics & Adolescent Medicine, 141(12), 1293.
Blackman, J. A., Healy, A., & Ruppert, E. S. (1992). Participation by pediatricians in early intervention: impetus from public law 99-457. Pediatrics, 89(1), 98-102.
Boyle, C. A., Boulet, S., Schieve, L. A., Cohen, R. A., Blumberg, S. J., Yeargin-Allsopp, M., ... & Kogan, M. D. (2011). Trends in the prevalence of developmental disabilities in US children, 1997 –2008. Pediatrics, peds 2010.
Brinker, R. P., Frazier, W., Lancelot, B., & Norman, J. (1989). Identifying infants from the inner city for early intervention. Infants & Young Children, 2(1), 49-58.
Centers for Disease Control, Developmental, D. M. N. S. Y., & 2010 Principal Investigators. (2014). Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2010. Morbidity and mortality weekly report. Surveillance summaries (Washington, DC: 2002), 63, 1.
Clements, K. M., Barfield, W. D., Kotelchuck, M., & Wilber, N. (2008). Maternal socio economic and race/ethnic characteristics associated with early intervention participation. Maternal and Child Health Journal, 12(6), 708-717.
Guralnick, M. J. (1997). Effectiveness of early intervention for vulnerable children: A developmental perspective. American Journal on Mental Retardation, 102(4), 319-345.
Guralnick, M. J. (2011). Why early intervention works: A systems perspective. Infants and Young Children, 24(1), 6.
Jackson, B. J., & Needelman, H. (2007). Building a system of child find through a 3-tiered model of follow-up. Infants & Young Children, 20(3), 255-265.
References
Macy, M. (2012). The evidence behind developmental screening instruments. Infants & Young Children, 25(1), 19-61.
National Professional Development Center on ASD (NPDC) Palfrey, J. S., Singer, J. D., Walker, D. K., & Butler, J. A. (1987). Early identification of children's special needs: a study in five metropolitan communities. The Journal of pediatrics, 111(5), 651-659.
Peterson, C. A., Wall, S., Raikes, H. A., Kisker, E. E., Swanson, M. E., Jerald, J., ... & Qiao, W. (2004). Early Head Start Identifying and Serving Children with Disabilities. Topics in Early Childhood Special Education, 24(2), 76-88.
Shannon, P., & Anderson, P. R. (2008). Developmental screening in community health care centers and pediatric practices: an evaluation of the Baby Steps Program. Journal Information, 46(4).
Sinclair, E. (1993). Early Identification of Preschoolers with Special (Needs in Head Start. Topics in Early Childhood Special Education, 13(2), 184-201.