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% of children with DD identified before Kindergarten
(Palfrey, 1987)

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, 99457, 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,
–

Individual states or multiple states weighted
for national representation
–

majority post- 2006.
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;
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
FE meta-
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 metaanalysis
–
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



–
Social Work

–
AAP
NICU
ACA
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, peds2010.
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 socioeconomic 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.