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Analysis of HMIS Data in Wisconsin

Analysis of HMIS Data in Wisconsin. NAEH Annual Conference July 28, 2008 Washington, D.C. Wisconsin HMIS Background. Statewide HMIS implementation Encompasses Four Continuums of Care Went live May 2001 180 Agencies 770 Users 211,000 active client files as of July 2008.

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Analysis of HMIS Data in Wisconsin

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  1. Analysis of HMIS Data in Wisconsin NAEH Annual Conference July 28, 2008 Washington, D.C.

  2. Wisconsin HMIS Background • Statewide HMIS implementation • Encompasses Four Continuums of Care • Went live May 2001 • 180 Agencies • 770 Users • 211,000 active client files as of July 2008

  3. Elements to Success • Department of Commerce/Bureau of Supportive Housing wears three hats. • Funder (state funds, Emergency Shelter Grant, PATH, HOME TBRA). • Grantee (SHP recipient for HMIS project). • HMIS Administrators for entire state.

  4. Key Elements • Integration of HMIS into all homeless/housing funding streams. • High bed coverage in HMIS. • 75% Emergency Shelter • 91% Transitional Housing • 92% Permanent Supportive Housing • Highly qualified staff.

  5. Research Questions • What factors are associated with successful client outcomes in transitional housing programs? • Do differences in the structure of transitional housing program networks affect client outcomes?

  6. Network Analysis Project • A Network Analysis is the study of the relations between social actors or specific entities. • Network Analysis addressed clients who left transitional housing programs.

  7. Foci of Network Analysis Project • To determine if clients with significant barriers to achieving housing stability are being served in transitional housing programs. • To give transitional housing providers a program model associated with successful client outcomes. • Two networks analyzed: • Program network • Client-centered network • Two different network ties

  8. Analysis • Client Risk • Low risk vs. high risk clients • Network Ties • In-program Network • Out-program Network • Client and supportive Services • Variables • Length of Stay • Volume/Intensity of Services

  9. SP THP SP Program network 1 Program network 4 SP SP SP THP SP THP THP SP SP SP SP Program network 3 Program network 2 Network Tie Example A client with a tie to a provider in their THP’s program network, three ties to other program networks, and five ties to different supportive service providers Client

  10. Preliminary Results • 44% of Transitional Housing Programs in WI do not serve clients classified as high risk. • High risk clients are almost twice as likely as low risk clients to have a shelter stay after participation in a transitional housing program. • The longer clients stay in a transitional housing program, the less likely they are to have a shelter stay afterward.

  11. Preliminary Results • The more services clients receive during their stay in the transitional housing program, the less likely they are to have a shelter stay afterward. • The more supportive service providers to which clients are linked in a transitional housing program, the more likely those clients will have a shelter stay afterward.

  12. Preliminary Results • Clients who have ties to supportive service providers in the same program network as their transitional housing program are less likely to have a shelter stay afterward than those clients who do not. • Clients who have ties to supportive service providers in program networks other than their transitional housing program are more likely to have a shelter stay afterward than those clients who do not.

  13. Impact • An increased ability to award funding based on client risk • Knowledge of what data would further aid understanding client success • Further investigation into a model of extending program networks to aid client success

  14. Next Steps • More detailed network analysis • Singles vs. Families • Unmet needs • Employability and Income • Program analysis • Eviction Prevention Programs • Recidivism

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