Birth Hospitals’ Role in Access to Early Intervention Services among Drug-Exposed Infants

1. Birth Hospitals’ Role in Access to Early Intervention Services among Drug-Exposed Infants Taletha Derrington, PhD & Milton Kotelchuck, PhD, MPH 141st APHA Annual Meeting November 4, 2013 ● Boston, MA

2. Policy Context • 2003 Keeping Children and Families Safe Act (better known by it’s precursor law, CAPTA – Child Abuse Prevention and Treatment Act) • 2004 Individuals with Disabilities Education Improvement Act (IDEA)

3. Study Question 1 • What are the rates and trends of Early Intervention (EI) referrals by hospitals among drug-exposed infants (DEI) born from 1998-2005?

4. Study Question 2 • Are any of the following predictors of referral? • Neonatal abstinence syndrome (NAS) diagnosis • Toxicology screen results • Insurance type • Maternal race/ethnicity • Hospital maternity level of care • Birth hospital discharge status

5. CORE Birth Certificate Hospital Discharge Delivery (Mother) Hospital Discharge Birth (Child) Child post-birth records (to age 3) Early Intervention Service Records 1998-2008 Drug Exposed Infant Identification Algorithm(DEIIA) Pregnancy to Early Live Longitudinal (PELL) Data System Maternal prenatal records (DOB – Gestational Age) Non-birth Hospital Discharge 7,348 DEI (1.2% of births) Observational Stays Emergency Department 624,269 live births from 1998-2005 4,436 referrals (60.9% of DEI)

6. Analytic Methods • Hospital referral source • Pre- to Post-Mandate differences in referral • Chi squared • Time series

7. Analytic Methods • Predictors of referral • Generalized estimating equations (GEE) logistic regression • Interaction analyses with “Ai-Norton” corrections for NAS and toxicology screens • Difference in differences to model interaction effects

8. Hospital Referrals of DEI * Chi Squared P < .01 8

9. Mandate Births Referrals Hospital Referrals Hospital Referrals of DEI 9

10. Predictors of Referral Good or expected outcome Disparity for reference group Disparity for comparison group *** P < .001 ** P < .01 * P < .05 Ins = insurance; NAS = neonatal abstinence syndrome; NHW = Non-Hispanic White; Tox = Toxicology Screen

11. Predictors of Referral Good or expected outcome Disparity for reference group Disparity for comparison group *** P < .001 ** P < .01 * P < .05 NICU = Neonatal Intensive Care Unit; PC = Parental care a Adjusted for: birth weight, gestational age, clinical risk factors for EI eligibility, conditions establishing EI eligibility (e.g., Down syndrome), maternal characteristics (age, education, and nativity), maternal custody of infant, region of residence, rural/urban residence, and neighborhood poverty

12. NAS Diagnosis Interaction 24.4 11.2 19.6 Difference in differences: None vs. Pvt. = -8.4 (P < .0001) Pub. vs. Pvt. = 4.8 (not significant)

13. NAS Diagnosis Interaction 25.8 23.3 18.2 Difference in differences: Well-baby vs. NICU = -7.6 (P < .05) Special Care vs. NICU = -2.5 (not significant)

14. Toxicology Screen Interaction 16.8 4.3 - 3.7 Difference in differences: None vs. Pvt. = 8.0 (not significant) Pub. vs. Pvt. = 20.5 (P< .0001)

15. Toxicology Screen Interaction 15.5 14.4 13.4 Difference in differences: Well-baby vs. NICU = -1.1 (P < .01) Special Care vs. NICU = 1.0 (P < .05)

16. Conclusions • DEI access to EI is suboptimal • 34% of post-mandate births not referred • Hospitals could identify and refer most DEI • Referred only 17% of post-mandate births • General program improvement for all birth hospitals needed to accelerate the weak upward trend in referrals 16

17. Conclusions • Referrals of DEI with NAS or positive toxicology screens should not vary across non-clinical factors • All children with NAS or positive toxicology screens should be referred • Type of insurance should not be related • Targeted program improvement needed for well-baby hospitals

18. Limitations • Potential under-ascertainment of referral • EI linkage rates 84%, similar to other studies • DEI may have lower linkage rates due to greater adoption & mobility • Validity of key measures • Referral source in EI data • Toxicology screen measure on birth certificate

19. Implications for Research & Policy • Birth hospitals as potential universal referral source • Encourage birth hospitals to refer – use DEIIA • DEIIA – feasible screening tool & should undergo further validation studies as a research tool • More longitudinally linked data systems are needed for research to inform program improvement and policy

20. Implications for Research & Policy • Need additional research on EI referrals by hospitals • Why are DEI born to mothers with private insurance are not being referred as often? • Why is private insurance related to different referral patterns for children with NAS or positive toxicology screens?

21. Acknowledgements This study is dedicated to the memory of Dr. Lorraine Vogel Klerman, an inspirational mentor and champion of students Dissertation Committee • Marji Erickson Warfield • Jody Hoffer Gittell • Dominic Hodgkin • Milton Kotelchuck Dissertation funding support • Nancy Lurie Marks Institute on Disability Policy Fellowship • Grants from the Heller Alumni Association and the Office of the Provost, Brandeis University I have no financial interests or disclosures

22. Thank You! E-mail: taletha.derrington@sri.com Web: http://dasycenter.org REFERENCES Ai, C & Norton, EC. Interaction terms in logit and probit models. Economics Letters. 2003; 80(1):123-129. Derrington, TM. Development of the Drug-Exposed Infant Identification Algorithm (DEIIA) and Its Application to Measuring Part C Early Intervention Referral and Eligibility in Massachusetts, 1998–2005. Maternal & Child Health Journal. 2012; 10.1007/s10995-012-1157-x Norton, EC, Wang, H & Ai, C. Computing interaction effects and standard errors in logit and probit models. State Journal. 2004; 4(2): 154-167.