Using Data to Plan Waiver Strategies and Drive Improvements: Key Indicators and Trends April 11, 2012.

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Presentation transcript:

Using Data to Plan Waiver Strategies and Drive Improvements: Key Indicators and Trends April 11, 2012

ASSESSING READINESS AND APPLICATION PLANNING Managing with Data in Child Welfare 2

Align Program Design with Existing Priorities Preventing Abuse and Neglect Keeping children safe and improving well- being through in-home services (including post-permanency supports to reduce re- entry) To facilitate a child or youth’s move to swift & certain permanency; promote successful transition to adulthood 3

Describe your Current System Review current data and trends – who are the children and families being served? What services are they getting? What is the ratio of placement expenditures to in- home expenditures? 4

Review Performance Measures – Assess your Strengths and Needs Consider National Context and Regional Characteristics Keep in mind case mix and the inter-relatedness of measures – states with very low entry rates may have longer lengths of stay 5

Consider all Available Data Sources CWS/CMS NCANDS, AFCARS and Federal CFSR Outcomes Longitudinal Data – timeliness and likelihood of achieving permanency Structured Decision Making Case Review Results (CFSR and local QA Activities) Contract monitoring Financial Data Qualitative data and feedback from stakeholders Research 6

OVERVIEW OF KEY CHILD WELFARE INDICATORS Managing with Data in Child Welfare

Trends in Out of Home Care Throughout these slides, CA data are from the CWS/CMS Dynamic Report System at National data are from NCANDS and AFCARS Nationwide, and in CA, the number of children in out of home care is declining Nationally, the decreasing number of children in out-of-home care has been driven by declining entries into care. This trend is starting to flatten out (or reverse) In CA, entries into care have been declining since FY08. Exits have been exceeding entries consistently.

In CA, the number of children in care has been declining as entries decline and exits continue to exceed entries

Point in Time Count of Children in Care On Jan 1 st

While the number of children in care has declined substantially, the absence of repeat maltreatment (a measure of child safety) has increased slightly in CA Among the 20 small counties, the absence of repeat maltreatment has remained relatively stable, but remains below state performance and below the national standard

Repeated Substantiated Maltreatment is only a fraction of the families who are repeatedly referred to Child Welfare services

The current placement system* (highly simplified) *adapted from Lyle, G. L., & Barker, M.A. (1998) Patterns & Spells: New approaches to conceptualizing children’s out of home placement experiences. Chicago: American Evaluation Association Annual Conference CHILD IN a bunch of stuff happens CHILD OUT the foster care system

CHILDREN ENTERING CARE Managing with Data in Child Welfare

Entry rates are highest for infants. Among all ages, entries are higher for Native American and African American children (National Data FY10, per 1000)

Key Questions: Entries What is the entry rate – by age/race? Are entries increasing/decreasing? for all groups? What strategies are in place/planned to reduce entries (and re-entries) into care?

Trends in the Number of Children Entering Care

Entry rates vary by county and may vary substantially over time in small counties. The entry rate for the 20 small group is considerably higher than the state.

By grouping all 20 counties, we are able to do more detailed analysis. Entry rates in the 20 small counties are highest for Native American and African American children

Entry rates in the 20 small counties are highest for infants

Possible reasons for county differences in entry rates: Service array – preventive and in home Standard of evidence Law enforcement removals Demographic risk factors Use of standardized risk assessment tools A variety of other policy/practice differences What strategies would safely reduce entry rates for infants? School aged children? Teens? Are services culturally relevant for African American and Native families?

CHILDREN IN CARE POINT IN TIME Managing with Data in Child Welfare

Key Questions: Children in Care What groups of children are in care NOW What types of placements? How long have they been in care? What is needed to move them to permanency?

Possible reasons for differences in in-care rates Length of stay and Placement type Service array Caseloads (agencies, courts) Case mix (age/service needs) Variation over time in small counties.

As a group, the 20 small counties have a slightly smaller proportion of children in kinship and congregate care placements than the statewide average – the use of kinship care has improved

Placement Type in the 20 Small Counties: Older youth are more likely to reside in group care, infants are less likely than other young children to be placed with kin

OUTCOMES: EXITS AND LENGTH OF STAY Managing with Data in Child Welfare

Key Questions: Permanency Outcomes What proportion of children entering care will eventually reunify? How does this differ by age at removal? What percent of children remain in care after 3 years? Are there differences by race or in different counties? Is this trend changing over time?

Reunification in 12 Months As a group, the 20 small counties reunify a larger proportion of children within 12 months. Infants and older teens are less likely to reunify in 12 months Entered care for the first time between July and Dec 2010 and remained in care at least 8 days.

Re-Entry After Reunification – As a group, the 20 small counties have slightly higher re-entries than the state average.

New Entries: Percent Exiting Over Time – 89% of the children who entered care for the first time achieved permanency within 36 months. This is higher than the statewide average of 83% Entered care for the first time between July and Dec 2008 and remained in care at least 8 days.

Achievement of permanency for longer stayers is Improving, (CFSR Measure C3.1)

Review Your Data Here!