Housing Homeless People with
Serious Mental Illness in California
Martha R. Burt
September 13-14, 2005
St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
5
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
6
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)
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
10
Data Sets Used
• Analyzed housing outcome data available from
the website www.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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
11
Who Are AB Programs Serving?
• 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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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% of Programs Meeting HtS Criteria
(of 28 state and 18 LA programs with data)
16
14
12
10
8
State (28)
LA (18)
6
4
2
0
70% HL
60%
street
HL
180+
days HL
40%
incar
50+
days
incar
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
60%
dual
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AB Program Outcomes
(all potentially calculable with HMIS data)
• % 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”
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Outcomes
• 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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
15
Dis-enrollment
(all calculable with HMIS data, if you collect it)
• 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 disenrollment
• 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)
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Makes a Very Big
Difference
• There is wide variation among
counties/programs in the proportion of everenrolled 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 everenrolled 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.
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Strategies
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Strategies, cont’d
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Strategies, cont’d
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 setaside units for consumers
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Strategies, cont’d
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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Housing Strategies, cont’d
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
23
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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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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
September 13-14, 2005 St. Louis, Missouri
Sponsored by the U.S. Department of Housing and Urban Development
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