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Maternal and Child Health Journal

, Volume 18, Issue 4, pp 1031–1037 | Cite as

Restricting State Part C Eligibility Policy is Associated with Lower Early Intervention Utilization

  • Beth M. McManus
  • Dawn Magnusson
  • Steven Rosenberg
Article

Abstract

To examine if state differences in early intervention (EI) utilization can be explained by recent restrictions on EI state eligibility policy. The sample (n = 923), derived from the 2009/10 National Survey of Children with Special Health Care Needs, included CSHCN who were ages 0–3 with a developmental delay or disability that affected their function. Multi-level logistic modeling was used to describe state differences in EI utilization and to determine if narrower state eligibility policy explained these differences. EI utilization ranged from 6 to 87 % across states. Having a severe condition (β = 0.99, SE = 0.28) and a usual source of care (β = 0.01, SE = 0.001) was associated with higher odds of utilizing EI. Compared to a diagnosed disability, having a developmental delay (β = −0.61, SE = 0.20) was associated with lower odds of utilizing EI. Living in a state with narrow and narrower state eligibility policy (β = −0.18, SE = 0.06) was significantly associated with lower odds of EI utilization, and this effect was strongest for children with the most severe functional impairments. Significant state variation in EI rates exists that can be explained, in part, by the restrictiveness of state eligibility criteria. Children with the most severe functional impairments appear to be least likely to utilize EI in states with the most restrictive eligibility policies.

Keywords

Part C eligibility policy Early intervention Developmental delay National Survey of Children with Special Health Care Needs Multilevel modeling 

Notes

Conflict of interest

The authors have no conflicts of interest, financial or otherwise, to disclose.

References

  1. 1.
    PL 108–446. Individuals with Disabilities Education Act, Reauthorization 2004. Accessed September 13, 2012 from: http://www.copyright.gov/legislation/pl108-446.pdf.
  2. 2.
    Spiker, D., et al. (2000). A framework for describing variation in state early intervention systems. Topics in Early Childhood Special Education, 20, 195–207.CrossRefGoogle Scholar
  3. 3.
    Rosenberg, S. A., Robinson, C. C., Shaw, E. F., & Ellison, M. C. (2013). Part C early intervention for infants and toddlers: Percentage eligible versus served. Pediatrics, 131, 38–46.PubMedCrossRefGoogle Scholar
  4. 4.
    McManus, B. M., et al. (2009). The effect of state early intervention (EI) eligibility on EI participation among Children with Special Health Care Needs. Pediatrics, 124, S368–S374.PubMedCrossRefGoogle Scholar
  5. 5.
    Feinberg, E., et al. (2011). The impact of race on participation in Part C early intervention services. Journal of Developmental and Behavioral Pediatrics, 32(4), 284–291.CrossRefGoogle Scholar
  6. 6.
    Rosenberg, S. A., et al. (2008). Prevalence of developmental delays and participation in early intervention services for young children. Pediatrics, 121(6), e1503–e1509.PubMedCrossRefGoogle Scholar
  7. 7.
    Shakelford, J. (2006). State and jurisdictional eligibility definitions for infants and toddlers with disabilities under IDEA. NECTAS Notes, 21, 43–47.Google Scholar
  8. 8.
    Infant and Toddlers Association. Part C implementation: State challenges and responses. IDEA Infant and Toddler Coordinators Association. December, 2009. Accessed September 13, 2012 from: http://www.ideainfanttoddler.org/pdf/09_Annual_Survey_Report-State_Challenges.pdf.
  9. 9.
    Percentage of all children (including at risk) under three receiving services (2004). Child count data. IDEA Infant and Toddlers Coordinator’s Association. Accessed September 13, 2012 from: http://www.ideainfanttoddler.org/05_Child_Count_Data_Charts.pdf.
  10. 10.
    Data Resource Center for Child and Adolescent Health (2005). 2005–2006 National Survey of Children with Special Health Care Needs.Google Scholar
  11. 11.
    Blumberg, S. J., et al. (2008). Design and operation of the National Survey of Children with Special Health Care Needs, 2005–2006. National Center for Health Statistics. Vital Health Statistics, 1, 1–188.Google Scholar
  12. 12.
    Subramanian, S. V., Jones K. Multilevel statistical models: Concepts and applications. Boston, MA: Center for Society and Health, Harvard School of Public Health/Bristol, UK: Centre for Multilevel Modeling, University of Bristol.Google Scholar
  13. 13.
    Tang, B. G., et al. (2012). Missed opportunities in the referral of high-risk infants to early intervention. Pediatrics, 6, 1027–1034.CrossRefGoogle Scholar
  14. 14.
    Bussing, R., et al. (2003). Agreement between CASA parent reports and provider records of children’s ADHD services. The Journal of Behavioral Health Services Research, 30(4), 462–469.PubMedCrossRefGoogle Scholar
  15. 15.
    D’Souza-Vazirani, D., et al. (2005). Validity of maternal report of acute health care use for children younger than 3 years. Archives of Pediatrics and Adolescent Medicine, 159, 167–172.PubMedGoogle Scholar
  16. 16.
    Hoagwood, K., et al. (2000). Concordance between parent reports of children’s mental health services and service records: The services assessment for children and adolescents (SACA). Journal of Child and Family Studies, 9(3), 315–331.CrossRefGoogle Scholar
  17. 17.
    Vernacchio, L., et al. (2007). Validity of parental reporting of recent episodes of acute otitis media: A slone center office-based research (SCOR) network study. Journal of the American Board of Family Medicine, 20(2), 160–163.PubMedCrossRefGoogle Scholar
  18. 18.
    Forrest, C. B., et al. (2004). Predictors of children’s healthcare use: The value of child versus parental perspectives on healthcare needs. Medical Care, 42(3), 232–238.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Beth M. McManus
    • 1
  • Dawn Magnusson
    • 2
  • Steven Rosenberg
    • 3
  1. 1.Department of Health Systems, Management and Policy, Colorado School of Public Health, Children’s Outcomes Research GroupChildren’s Hospital ColoradoAuroraUSA
  2. 2.Department of Population Health SciencesUniversity of Wisconsin-MadisonMadisonUSA
  3. 3.Department of PsychiatryUniversity of Colorado School of MedicineAuroraUSA

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