Profiles of Children with High Utilization of SIPP

1. Profiles of Children with High Utilization of SIPP Agency for Health Care Administration Briefing September 27-28, 2010 Svetlana Yampolskaya, Ph.D. Norín Dollard, Ph.D. Debra Mowery, Ph.D. Paul E. Greenbaum, Ph.D.

2. Background • Excessive utilization of institutional mental health services has been of longstanding public concern • Inpatient or residential treatment is costly, highly restrictive, and there is considerable controversy regarding its efficacy • There is a general consensus that children with persistent mental health problems should be served in the least restrictive environment • However, nationwide nearly 66,000 youth live in inpatient mental health programs

3. Study Goals The goals of this study were to examine factors associated with: • Longer length of stay in the State Inpatient Psychiatric Program (SIPP) • Time to re-admission to SIPP • Multiple admissions to SIPP among youth initially admitted to SIPP within four fiscal years (i.e., FY 2004-2005 through 2007-2008).

4. Data Sources • The State Child Welfare Information System for the State of Florida (from FY01-02 to FY06-07), HomeSafenet • The State Child Welfare Information System for the State of Florida (since FY07-08 ), Florida Safe Families Network (FSFN) • Florida Medicaid fee-for-services claims administrative databases

5. Study Design The study design consisted of two parts: • Longitudinal analyses of administrative data in which youth placed in SIPP were followed until discharge • A comparison between youth who were admitted to SIPP either once or twice versus those with multiple admissions (i.e., three or more).

6. Sample Characteristics • All children admitted to the State Inpatient Psychiatric Program (SIPP) during FY 2004-2005 through FY 2007-2008 were included in the study • The average age was almost 14 years (M = 13.83) • Race/Ethnicity • 49% Non-Hispanic White • 24% African-American • 10% Hispanic • 17% Other racial and ethnic groups • 65% involved with the child protection system

7. Predictor Variables • Child demographic characteristics: • Gender • Age at the time of admission to SIPP • Race/ethnicity • Child maltreatment history: • Maltreatment type • Physical Abuse • Sexual Abuse • Neglect • Threatened Harm • Caregiver Absence • Maltreatment severity

8. Predictor Variables (cont.) • ICD-9-CM mental health diagnoses • Bipolar disorder • Attention deficit hyperactivity disorder • Adjustment reaction disorder • Conduct disorder • Depression • Comorbidity • Involvement with the Child Protection System • Out-of-Home child welfare placement

9. Predictor Variables (Re-Admission) • Categories of aftercare mental health services • Basic outpatient • Intensive outpatient • Assessment • Treatment planning • Targeted case management • Specialized care (e.g., therapeutic foster care) • Length of stay in SIPP during the first episode

10. Analytic Approach • Cox regression, also known as proportional hazards modeling (Cox, 1972) • Logistic regression

11. Prevalence of Mental Health Disorders among Children Placed in SIPP

12. Length of Stay in SIPP

13. Length of Stay in SIPP

14. Factors Associated Length of Stay in SIPP • Hispanic or African-American children were approximately • 35% more likely to remain in SIPP longer as compared to • children from ‘Other’ racial and ethnic groups • Children with a history of sexual abuse had 26% greater • odds of remaining in SIPP longer in comparison to children • with other types of maltreatment • Compared to Medicaid eligible youth who were not involved • in the child welfare system, children who were placed in child • welfare out-of-home care were 37% more likely to experience • a delayed discharge

15. Re-Admission to SIPP • Of all children admitted to SIPP, 36% were re-admitted • during the four-year study period and of those who were • readmitted, 89% were readmitted within one year of discharge • Remaining in SIPP one day less during the first episode • corresponded to a 3% greater odds for re-admission • Higher levels of maltreatment severity are associated with • the shorter time between discharge and subsequent re- • admission to SIPP • The lack of basic outpatient services or the lack of Intensive • outpatient services predicted earlier re-admission • None of the examined mental health diagnoses were • associated with re-admission to SIPP

16. Multiple Admissions to SIPP • 15% of youth experienced multiple (i.e., more than two) • admissions • Youth with more than one mental health diagnosis had two • and one half times greater odds of experiencing multiple • admissions to SIPP • One less day spent in SIPP during the second episode • corresponded to a 1% increase in the likelihood that a child • would have a subsequent multiple admissions to SIPP • Higher number of assessments and higher number targeted • case management services were associated with an • increased likelihood for multiple admissions to SIPP

17. Conclusions • Among demographic characteristics, being younger was • associated with an increased length of stay, but being older • was linked to repeated admissions and shorter time to re- • admission • Among maltreatment variables, only sexual abuse and • maltreatment severity were significant predictors for spending • more time in SIPP and shorter time to re-admission • Although individual mental health diagnoses were not • associated with either length of stay in SIPP or re-admission • to SIPP , having more than one mental health disorder • strongly affected the chances for negative outcomes

18. Policy Implications • Greater attention needs to be paid to the trauma-informed • and trauma-specific interventions that systematically identify • and address trauma, attachment, traumatic grief, and loss • There needs to be continued vigilance to ensure that • discharge planning starts at admission, and that efforts are • needed to increase the use of Targeted Case Management • More technical assistance and consultation should be made • available to community providers to manage youth who • present with complex needs and to prevent their return to • restrictive levels of care. Other suggestions include providing • a greater focus on the evidence-based treatments that have • demonstrated efficacy for multiple diagnoses.

19. Contact Information Svetlana Yampolskaya yampol@fmhi.usf.edu Norín Dollard dollard@fmhi.usf.edu Debra Mowery mowery@fmhi.usf.edu Paul E. Greenbaum greenbaum@fmhi.usf.edu