birth hospitals’ role in access to early intervention services among drug-exposed infants taletha...
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Birth Hospitals’ Role in Access to Early Intervention
Services among Drug-Exposed Infants
Taletha Derrington, PhD & Milton Kotelchuck, PhD, MPH141st APHA Annual Meeting
November 4, 2013 ● Boston, MA
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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)
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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?
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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
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Drug Exposed Infant Identification Algorithm(DEIIA)
Pregnancy to Early Live Longitudinal (PELL) Data System
624,269 live births from 1998-2005
Birth Certificate
Hospital Discharge Delivery (Mother)
Hospital Discharge Birth (Child)
CORE
Child post-birth records(to age 3)
Maternal prenatal records(DOB – Gestational Age)
Emergency Department
Observational Stays
Non-birth Hospital Discharge
Early Intervention Service Records 1998-2008
7,348 DEI(1.2% of births)
4,436 referrals(60.9% of DEI)
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Analytic Methods
Hospital referral source Pre- to Post-Mandate differences in referral
• Chi squared • Time series
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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
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Hospital Referrals of DEI
DEI Births - All Referral Sources*
DEI Births - Hospital
Referral Source*
DEI Referrals - Hospital
Referral Source*
0%
50%
100%
59%
12% 21%
66%
17%25%
Pre- to Post-Mandate Differences in DEI Births Referred to EI
Pre: 1998-2003Post: 2004-2005Pe
rcen
t
* Chi Squared P < .01
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9Births Referrals Hospital Referrals
Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-060
20
40
60
80
100
120
140
Pre- and Post-Mandate Time Series of DEI Births, Referrals, & Hospital Referrals
Birth Month & Year
Coun
t
Mandate
Hospital Referrals of DEI
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Predictors of Referral
Other vs. NHW
Asian/Pacific Islander vs. NHW**
Hispanic vs. NHW
Non-Hispanic Black vs. NHW
No vs. Private Ins*
Public vs. Private Ins***
Positive vs. Negative Tox**
NAS Diagnosis vs. None***
0.0 0.5 1.0 1.5 2.0 2.5
Adjusted Odds Ratio a
Ins = insurance; NAS = neonatal abstinence syndrome; NHW = Non-Hispanic White; Tox = Toxicology Screen
Good or expected outcomeDisparity for reference groupDisparity for comparison group
*** P < .001** P < .01* P < .05
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Predictors of Referral
Home Health Discharge vs. PC***
Transferred vs. PC***
Special Care Nursery vs. NICU
Well-baby nursery vs. NICU*
0.0 0.5 1.0 1.5 2.0 2.5
Adjusted Odds Ratio a
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
Good or expected outcomeDisparity for reference groupDisparity for comparison group
*** P < .001** P < .01* P < .05
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NAS Diagnosis Interaction
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None Public Private30%
40%
50%
60%
70%
80%
90%
55% 56%
35%
66%
80%
55%
Differences in Predicted % DEI Referred by Insurance
No NASNAS Dx
Pred
icte
d Pe
rcen
t Ref
erre
d
24.4
Difference in differences: None vs. Pvt. = -8.4 (P < .0001)Pub. vs. Pvt. = 4.8 (not significant)
11.2
19.6
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NAS Diagnosis Interaction
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Well-Baby Special Care
Neonatal Intensive Care
30%
40%
50%
60%
70%
80%
90%
47%55% 55%
65%
78% 81%
Differences in Predicted % DEI Referred by Birth Hospital Maternity Level
No NASNAS
Pred
icte
d Pe
rcen
t Ref
erre
d
23.3
Difference in differences: Well-baby vs. NICU = -7.6 (P < .05)Special Care vs. NICU = -2.5 (not significant)
25.8
18.2
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Toxicology Screen Interaction
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None Public Private30%35%40%45%50%55%60%65%70%75%80%
56%60%
40%
60%
77%
36%
Differences in Predicted % DEI Referred by Insurance
NegativePostive
Pred
icte
d Pe
rcen
t Ref
erre
d
16.8
Difference in differences: None vs. Pvt. = 8.0 (not significant)Pub. vs. Pvt. = 20.5 (P < .0001)
- 3.7
4.3
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Toxicology Screen Interaction
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Well-Baby Special Care
Neonatal Intensive Care
30%35%40%45%50%55%60%65%70%75%80%
48%
60% 60%62%
76%74%
Differences in Predicted % DEI Referred by Birth Hospital Maternity Level
Negative
Postive
Pred
icte
d Pe
rcen
t Ref
erre
d
15.5
Difference in differences: Well-baby vs. NICU = -1.1 (P < .01)Special Care vs. NICU = 1.0 (P < .05)
14.4
13.4
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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
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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
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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
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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
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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?
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AcknowledgementsThis 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
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Thank You!E-mail: [email protected]: 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.
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