1. Options for Allocating State Child Welfare Dollars to Wisconsin Counties Prepared for the Wisconsin Department of Children and Families Christine Durkin Adam Hartung Sara Kock Jennifer Russ Paul Waldhart

2. Problem ●Current formula may not match resources to need as effectively as it could ●To form our alternatives: ●Literature review ●Surveys ●Interviews ●With other states ●With Wisconsin counties

3. Overview ●Current policy ●Alternatives ●Recommendation ●Cross-county collaboration

4. Background ●State supervised, county administered system ●Differences in demand for services 10 Lowest Poverty Counties 10 Highest Poverty Counties

5. Background ●Funded with state and local dollars ●Declining state revenues ●Limiting property tax levy

6. Current Policy In 1986, Wisconsin allocated child welfare money based on: 1.Total population 2.Residents enrolled in Medicaid 3.Property values County A 2011 1986 State Child Welfare Dollars

7. Alternatives ●We examined two alternatives: 1.Risk Factor: More risk = More $ 2.Workload: More demonstrated need = More $ ●We considered but eliminated: 3.Updating the current formula 4.Percent-For-Service: DCF reimburses counties a percentage of service costs 5.Performance-Based Contracting: DCF purchases outcomes, counties sell outcomes

8. Alternative #1: Allocation based on Risk Factors Step 1 County need for child welfare services = β 1 Number of children in single parent families + β 2 Number of children living in poverty + ԑ(error) Step 2 County risk number = 0.33(Number of children in single-parent families in county) + 0.67(Number of children living in poverty in county) β 1 / (β 1 + β 2 ) = 0.33 and β 2 / (β 1 + β 2 ) = 0.67 0.33 + 0.67 = 100%

9. Alternative #1: Allocation based on Risk Factors Step 1 County need for child welfare services = β 1 Number of children in single parent families + β 2 Number of children living in poverty + ԑ(error) Step 2 County risk number = 0.33(Number of children in single-parent families in county) + 0.67(Number of children living in poverty in county) Step 3 County allocation = (County risk number / Sum of risk numbers for all counties) x Total CFA funding available

10. Alternative #1: Allocation based on Risk Factors Step 1 County need for child welfare services = β 1 Number of children in single parent families + β 2 Number of children living in poverty + ԑ(error) Step 2 532= 0.33 (400) + 0.67 (600) Step 3 $866,400= (532 / 35,000) x $57 million

11. Alternative #2: Allocation based on Workload More cases and/or more labor-intensive cases = More $ ●Children’s Research Center developed a framework ●DCF would: 1.Calculate time spent on each service area per case 2.Use eWiSACWIS to determine the number of cases 3.Calculate county workload (time per case x # of cases) 4.Allocate funds based on county’s proportion

12. Example County Workforce Estimate County Service Area Number of Cases per Month Worker Hours/Case per Month Total Worker Hours CPS Intake Screened-In CPS Reports1271.1140 Screened-Out CPS Reports750.322 CPS Investigation/Assessment Investigated Cases w/out Substantiation958.1773 Investigated Cases with Substantiation2313.4309 Child and Family Services New Child Case139.5127 Ongoing Child Case146.61,139 Total County Workload Demand in Worker Hours2,512 hrs County Proportion of State Aid 6.2%

13. Goals ●Effective ●Matches need with resources ●Minimal potential for cheating ●Equitable ●Measures need regularly ●Equal spending per person

14. Estimated County Allocation per Person, by Percent of County Population Living in Poverty CURRENT POLICY

15. Estimated County Allocation per Person, by Percent of County Population Living in Poverty CURRENT POLICY RISK FACTOR FORMULA WORKLOAD METHOD

16. Goals ●Effective ●Matches need with resources ●Minimal potential for cheating ●Equitable ●Measures need regularly ●Equal spending per person ●Lower Additional Cost to DCF ●Acceptable to Counties ●Methodology ●Magnitude of gains & losses ●Number of gainers & losers

17. Magnitude of Changes in County Allocation, by Percent of County Population Living in Poverty RISK FACTOR FORMULAWORKLOAD METHOD Percent of County Population Living in Poverty Highest Poverty Counties Lowest Poverty Counties Highest Poverty Counties Lowest Poverty Counties

18. Changes in County Allocation, by Percent of County Population Living in Poverty Percent of County Population Living in Poverty RISK FACTOR FORMULAWORKLOAD METHOD Decreased CFA No Change in CFA Increased CFA Highest Poverty Counties Lowest Poverty Counties Highest Poverty Counties Lowest Poverty Counties

19. Implementation Considerations ●Leaky bucket ●Receiving more state dollars may reduce county funding ●County levy limits ●Larger burden on counties who cannot raise revenue ●Solution: “No harm” exemption ●Large fiscal impacts on counties ●Significant declines would be hard to absorb ●Solution: Gradual implementation

20. Recommendation Risk Factor Formula ●Effective: ●Matches resources to need ●Data manipulation unlikely ●Equitable: ●Updated yearly ●Counties with similar poverty rates treated alike ●Low additional cost to DCF ●Counties likely will find it moderately acceptable

21. County Interviews and Surveys In-person interviews with county Human Services Departments ●2 small (Marquette and Richland) ●3 medium (Dodge, Rock, and Sauk) ●2 large (Milwaukee’s BMCW and Dane) On-line survey to all counties on cross-county collaborations for CPS ●11 responses from across the state

22. County Interviews and Surveys Four themes from counties 1.The importance of block grants and flexibility 2.The role of local decision-making 3.Differences between BMCW and counties 4.Constraints of state mandates

23. Cross-County Collaborations Suggestions for collaboration ●High-Risk or Catastrophic Case Insurance Pool ●Access and intake ●Training ●Foster care training for parents ●Specialized and high-cost services ●Use of teleconferencing for training

24. Cross-County Collaborations Some counties still won’t give up local control ●Screen-in discretion ●Out-of-county institutions ●Debate over where to locate a new regional service hub or institution

25. Cross-County Collaborations How DCF can facilitate ●“Lay the groundwork” for the first meeting ●Provide information collected by DCF ●Reduce or help navigate state mandates ●If DCF provides new funds: ●Help fund portions of specialized staff ●Grants for start-up services/institutions for multi-county collaborations

26. Cross-County Collaborations Problems to avoid ●Too many changes at once ●Poor budgeting and unrealistic expectations ●Lack of buy-in among stakeholders ●Unaccountable governing bodies

27. Conclusion ●We explained: ●CPS demands and funding ●Two alternatives ●Themes from county interviews and surveys ●We recommend: ●DCF adopt the Risk Factor Formula ●DCF encourage and facilitate cross-county collaboration

28. For further information Contact the La Follette School’s publications office at 608-263-7657 or publications@lafollette.wisc.edu Or see www.lafollette.wisc.edu/publications/workshops.html Thank you

29. APPENDIX SLIDES

30. Alternative #1 Risk Factor Coefficient Summary Risk FactorsCoefficients Standard Error Number of Children Living in Poverty 0.0795***(0.0129) Number of Children in Single-Parent Families 0.0386**(0.0157) Constant14.83(19.66) Number of Observations72 Counties R-Squared0.974 *** p<0.01, ** p<0.05, * p<0.1 Source: Authors, calculated using DCF (2010) and ACS (2010) data

31. Estimated County Allocation per Person Under Current Policy, by Percent of County Population Living in Poverty

32. Estimated County Allocation per Person Under Risk Factor Formula, by Percent of County Population Living in Poverty

33. Estimated County Allocation per Person Under Workload Method, by Percent of County Population Living in Poverty

34. Magnitude of Changes in County Allocation using The Workload Method, by Percent of County Population Living in Poverty Note: 1 st quartile are those counties with highest levels of poverty Highest Poverty Counties Lowest Poverty Counties

35. Changes in County Allocation using Risk Factor Formula, by Percent of County Population Living in Poverty Note: 1 st quartile are those counties with highest levels of poverty Highest Poverty Counties Lowest Poverty Counties

36. Changes in County Allocation using Workload Method, by Percent of County Population Living in Poverty Note: 1 st quartile are those counties with highest levels of poverty Highest Poverty Counties Lowest Poverty Counties

39. Background ●State supervised, county administered system ●Differences in demand for services

40. Background ●Funded with state and local dollars ●Declining state revenues ●Limiting property tax levy

41. Estimated County Allocation per Person, by Percent of County Population Living in Poverty CURRENT POLICY

42. Estimated County Allocation per Person, by Percent of County Population Living in Poverty CURRENT POLICY RISK FACTOR FORMULA WORKLOAD METHOD