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

Early Identification of Developmental Delays or Concerns to Receipt of Early Intervention Services Among Infants and Toddlers: A Systematic Review

AUCDNovember 11, 2014

Early Identification

It is never too late to start supports and services for a person in need.

Starting as early as possible is best.

Early identification of developmental concerns allows families to seek intervention during the crucial period of early child brain, body, and behavioral development

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 aPublic 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, 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

19% Screened Positive or Referred

13% Assessed Entered EI

Specialized Setting

58% Screened Positive or Referred

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.