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IV-E Waiver Cost Analysis #1 - How are IV-E Waiver dollars being - PowerPoint PPT Presentation

IV-E Waiver Cost Analysis #1 - How are IV-E Waiver dollars being spent? Goals: To track the money being allocated to each county by funding steam (e.g., EBPs vs. Family Support), to describe the goods and services provided, and to indicate


  1. IV-E Waiver Cost Analysis

  2. #1 - How are IV-E Waiver dollars being spent? • Goals: To track the money being allocated to each county by funding steam (e.g., EBPs vs. Family Support), to describe the goods and services provided, and to indicate the # of clients served • How? The Evaluation Team is working with DHR to develop a detailed spreadsheet that will be completed on a regular basis by each of the 24 Maryland jurisdictions.

  3. #2 - How have DHR’s costs shifted with the implementation of the Waiver? • Goal: To determine whether the flexibility afforded to DHR by the Waiver has resulted in reduced administrative costs and to evaluate whether out-of-home costs decline during the Demonstration period • How? The Evaluation Team will work with DHR to identify and track major funding sources (e.g., Title IV-E, TANF, Title IV-B, etc.) used to pay for child welfare activities and to further break down each funding source into its cost components (e.g., administration and maintenance, training). Trends over time will be examined.

  4. #3 – What is the net benefit/cost of implementing EBPs under the IV-Waiver? • Goal: To determine whether the costs associated with EBPs are offset by their associated benefits, such as reduced costs associated with out-of-home placements • How? Program costs related to personnel, facilities (e.g., rent), supplies, etc. will be collected from EBP providers on a semi- annual basis. For up to three EBPs, cost-benefit analyses will be conducted, with non-EBP youth in the same county serving as comparisons. Costs associated with non-EBP placements will be obtained from DHR.

  5. #4 – How does implementation of EBPs affect Medicaid costs? • Goals: To assess 1) whether MA claims for were reduced for youth following their participation in EBPs, and 2) whether MA claims for EBP participants are lower than those placed in out-of-home care. • How? Analyses will depend on the full implementation of EBPs and the availability of Medicaid claims data. Analyses will be conducted in future evaluation years.

  6. Maryland State-wide Indicators State Fiscal Years 2013-16

  7. State-wide Indicators  Throughout the Waiver implementation, several state- level indicators will be monitored to assess any changes from historical trends prior to the Waiver and during Waiver implementation  The following presents rates of reunification, adoption, and guardianship; placement stability; length of stay of removal; response track; and residential placements from SFY’s 2013 -15 (pre-Waiver) and 2016 (first year of Waiver implementation)

  8. Response Track Pre-Waiver Waiver 100% 80% 60% Alternative Response 40% Investigative 20% Response 0% SFY 13 SFY 14 SFY 15 SFY 16 (N=40,595) (N=36,034) (N=31,944) (N=30,817)

  9. Other Statewide Indicators Placement Stability Rates of Reunification, Adoption, & Guardianship 8.0 Waiver Pre-Waiver 100% Exits from OOHP 7.0 Pre-Waiver Waiver 80% 6.0 4.6 4.5 4.2 4.2 5.0 60% 4.0 40% 3.0 2.0 20% 1.0 0% 0.0 SFY 13 SFY 14 SFY 15 SFY 16 FY13 FY14 FY15 FY16 (N=3,218) (N=3,016) (N=2,633) (N=2,486) (N=2,532) (N=2,401) (N=2,185) (N=2,480) Reunification Adoption Guardianship Moves per 1,000 Days in Care Length of Stay of Removals Residential Placements 10% 250 Pre-Waiver Waiver Pre-Waiver Waiver 8% 200 6.5% 6.2% 136 132 130 5.6% 128 Entrie 6% 150 4.4% 4% 100 1.9% 1.8% 1.5% 1.3% 2% 50 0% 0 FY13 FY14 FY15 FY16 FY13 FY14 FY15 FY16 (N=2,533) (N=2,421) (N=2,195) (N=2,491) (N=2,532) (N=2,401) (N=2,185) (N=2,480) Average Days Removed Community Residential Non-Community Residential

  10. How to Contact Us: Elizabeth Greeno, PhD Pam Freeman, PhD Sara Betsinger, PhD Bethany Lee, PhD Lead Evaluator for Lead Evaluator for EBPs Lead Cost Evaluator Evaluation Director CANS-F/ Trauma sbetsinger@ssw.umaryland.edu egreeno@ssw.umaryland.edu blee@ssw.umaryland.edu pfreeman@ssw.umaryland.edu David Chen John Cosgrove Rochon Steward Maria Jose Horen Senior Data Analyst Senior Data Analyst Research Specialist Research Supervisor dchen@ssw.umaryland.edu jcosgrove@ssw.umaryland.edu rsteward@ssw.umaryland.edu mjhoren@ssw.umaryland.edu

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