Analysis of HMIS Data in Wisconsin

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