1. Housing Homeless People with Serious Mental Illness in California September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development Martha R. Burt

2. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 2 Overview Describe data analysis of clients and outcomes in a California program for homeless people with serious mental illness Use to illustrate some of the ways that data in an HMIS, if it were the right data and covered the right programs, might produce similar analyses

3. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 3 What Is AB 2034? California legislation providing flexible funding (“whatever it takes”) to counties Focus—people with serious mental illness, with or without co-occurring substance abuse, who are homeless or high risk Goals are to End homelessness for this population, especially long-term homelessness Prevent returns to homelessness or first-time homelessness for people with SMI leaving institutions

4. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 4 Where Does It Operate; How Many Does It Serve? First legislation passed in 1999; funded 3 pilot counties to start services in 2000 Expanded in 2001 based on preliminary evidence of success Now 52 programs—18 in Los Angeles County, 34 in other counties (1 county has 2 programs) Over 11,000 people served to date; current enrollment around 5,000

5. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 5 How Does It Document Its Activities? Extensive systematic data collection using common system (CAMINAR) Components: Circumstances at enrollment (demographics, homelessness, housing status, hospitalizations, incarcerations, employment, income sources) Experiences while enrolled (same categories) Disenrollment timing, reasons, and last known housing status

6. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 6 Potential for HMIS HMIS could collect much of the same data that CAMINAR does: Circumstances at enrollment (demographics, homelessness, housing status, hospitalizations, incarcerations, employment, income sources) Experiences while enrolled (same categories) Disenrollment timing, reasons, and last known housing status To do this, HMIS would have to cover PSH and also SSO programs

7. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 7 Why Is It Important to Know About AB 2034? Important in own right, as model legislation, model programs, and significant evidence of success in housing long-term homeless people New money coming— Proposition 63 passed in November 2004, provides masses of service money to Department of Mental Health to expand the types of programs that AB supports Also Prop 43 in 2003, provided new capital resources for housing for disabled people (although most already committed)

8. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 8 Why Do I Have These Data? Passage of Prop 63 meant DMH was going to have to figure out how to distribute money, what to ask for, what outcomes to expect/require Needed more information on AB programs, about their outcomes, their housing strategies, the challenges they have faced, and how they have responded

9. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 9 Why Do I Have These Data? Corporation for Supportive Housing (CSH) offered to assemble the relevant data Evaluation sponsors were: California Institute of Mental Health (association of county mental health agencies, which mostly have responsibility for AB programs) Conrad N. Hilton Foundation

10. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 10 Purpose of Evaluation  Identify the range of housing strategies implemented by programs in the 34 counties that have received AB2034 funding  Data that would be external to HMIS  Determine association between being able to house consumers and being able to retain consumers (lower dropout rate)  Should be able to get relevant data from HMIS  Determine if the housing strategies or range of strategies that a county (or program within a county) employed made a difference for successful housing outcomes  Analysis that would combine HMIS and other data

11. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 11 Analyzed housing outcome data available from the website www.ab34.orgwww.ab34.org Mental Health Association of Los Angeles provided further analysis of the CAMINAR data These two data sources are most similar to HMIS “Housing Strategies Survey” Developed survey and conducted phone interviews with AB2034 Coordinators or designated staff to gather survey responses Completed 41 surveys covering 44 programs (of 53) in 28 different counties, including 2 programs in two counties and 13 of Los Angeles’ 19 programs Response rate = 83% of all programs Data Sets Used

12. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 12 Set up 6 criteria for “hard to serve” (HtS) 70+% homeless at enrollment 60% street homeless at enrollment 180+ average homeless days in 12 months before enrollment 40+% incarcerated in 12 months before enrollment 50+ average incarcerated days in 12 months before enrollment 60+% with co-occurring substance abuse Could do with HMIS data Who Are AB Programs Serving?

13. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 13 % of Programs Meeting HtS Criteria (of 28 state and 18 LA programs with data)

14. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 14 % retained (currently enrolled), of everyone ever enrolled Median: 42% (state); 44% (LA) Range: 17-82% (state); 27-69% (LA) % housed, of everyone ever enrolled Median: 37% (state); 39% (LA) Range: 12-62% (state); 25-56% (LA) Relationship between % housed and % retained:.929 Or, “if you house them, you keep them” AB Program Outcomes (all potentially calculable with HMIS data)

15. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 15 Programs that enroll “more challenging” consumers (those that have had longer histories of homelessness or more barriers to housing stability) are not getting worse results in terms of housing outcomes In fact sometimes the results are better— higher average homeless days in year before enrollment is associated with higher proportion housed If client difficulty indicators suggest “Housing Unreadiness” to those who adhere to this concept, AB data show the concept is not a good predictor of housing outcomes Housing Outcomes

16. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 16 How quickly do consumers leave AB2034 programs? 56% of those who have enrolled in AB2034 programs have dis-enrolled. Among programs, the range is 17% to 83%. Of the 56% who have dis-enrolled : 25% dis-enrolled by 6 months 51% dis-enrolled by 12 months “dropouts” account for 51% of the reasons for dis- enrollment Other reasons include rehospitalization, death, movement to a lower level of care, and being inappropriate for the program (not having SMI, once substance abuse symptoms have subsided) Dis-enrollment (all calculable with HMIS data, if you collect it)

17. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 17 There is wide variation among counties/programs in the proportion of ever- enrolled consumers who are now in stable housing. The range is 12% to 62%. There is a very strong correlation (.929) between having a high proportion of ever- enrolled consumers who are in housing and having a very low proportion of consumers who dis-enroll. Also, the faster a program is able to move clients into housing from homelessness, the higher the retention rate. Housing Makes a Very Big Difference

18. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 18 Some strategies are being used by nearly every county/program – and offered to virtually every consumer. These include: Advocacy on behalf of individuals to help them find and get housing Supportive services to help people keep housing Back-up problem-solving help for landlords Housing Strategies

19. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 19 Other widely implemented housing strategies include: Assist consumers to apply for housing subsidies (all do) Provide short-term subsidies or help with move-in costs (all do, & most consumers get) Provide long-term rent subsidies to some consumers (all do, but few consumers get) Provide temporary or transitional housing to get people off the streets and/or for respite/crisis Housing Strategies, cont’d

20. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 20 Some strategies are used in about half of the counties/programs: Actively recruiting landlords, systematically finding available units, making arrangements with landlords to secure the next vacant unit Master-leasing buildings or apartments within buildings and sub-leasing units to consumers Use AB2034 funds to secure dedicated or set- aside units for consumers Housing Strategies, cont’d

21. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 21 Strategies more likely to be implemented in large/urban counties: Administer Section 8 or Shelter + Care rent subsidies that are available to consumers Partner with Housing Authority or other public agencies that control rent subsidies Work with PSH providers; partner to supply services if the other partner does development and/or operations Housing Strategies, cont’d

22. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 22 Strategies more likely to be implemented in smaller/rural counties: Offering maintenance or cleaning – either ongoing to help tenants keep housing or when tenants move out to keep landlords willing to rent to other consumers Housing Strategies, cont’d

23. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 23 Effective Strategies Many counties/programs offer a range of housing strategies including:  Partnering with housing providers  Recruiting landlords  Securing rent subsidies or set-aside units No single strategy appears to be more effective than others Nor do the total number of strategies used make much difference However, working with PSH providers appears effective in retaining clients for 24+ months And using your AB funds to pay rents long-term appears to be the least effective strategy Counties/programs that have been most successful have focused on expanding the supply or range of housing available to consumers, rather than just helping each individual find housing

24. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 24 What AB Providers Say Is Needed Most More affordable housing Permanent supportive housing Landlords and property managers who are tolerant and understanding of consumers “Wet/Damp” and “Harm Reduction” housing models for people with substance use problems Support for both landlords and tenants Wide range of housing options

25. September 13-14, 2005 St. Louis, Missouri Sponsored by the U.S. Department of Housing and Urban Development 25 Implications for HMIS Assess the types of analyses that will be most useful to your community for: Tracking outcomes Convincing funders that they should invest in particular types of programs Determine how much of the relevant data you could collect through HMIS Determine what other data you will need (in the AB case, information about the interventions) The AB study was done very quickly; was possible because the CAMINAR data were already available You could set up your HMIS system to do the same