using data to end homelessness
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USING DATA TO END HOMELESSNESS
Joshua D. Bamberger, MD, MPHJosh.bamberger@sfdph.org
San Francisco Department of Public HealthUniversity of California, San Francisco, Dept. of
Family and Community Medicine
Housing and Homeless Studies
• Cost• Before and after studies• Randomized controlled trials
• Mortality• Retrospective case control
• Quality of Life• Retrospective cohort studies
• Populations based homeless prevalence• Creating a Narrative
Creating a Narrative
• Housing is less expensive than homelessness• For people w/ homelessness and AIDS, ARVs are
necessary but not sufficient to improve mortality• The right treatment for the condition
Direct Access to Housing- 1600 units in 40 buildings Tailor housing to needs of individual
Initially SRO, now new buildingsPriority to people with multiple disabilities93% with Axis I mental illnessAt least 18% HIV+
SF Health Dept’s Housing
DAH Portfolio
•
253 286604 678 704 704 878
0 0
177 247 339
689
020040060080010001200140016001800
99-00 2001-2 2003-4 2005-6 2007-8 2009-10
2011-2015
NewMaster-lease
Cost: Plaza Retrospective Before and After• 106 Chronically homeless adults• Cost year before housing: $3,132,856 • Cost year after housing: $906,228• Reduction in healthcare costs: $2,226,568 • Cost of program: $1.1million/year• Reduction in public cost in first year: $1.1 million• More than 90% of reduction
among 15 tenants who cost more than $50,000/year prior to being housed
• Regression to the mean
• Brand new building with 174 units• Homeless, high users of a managed care system• Comprehensive healthcare utilization• Randomly assigned to treatment or regular care• Followed prospectively for 5 years• Outcomes included: Healthcare cost,
mortality, jail
Cost: KCC Random assignment trial
Cost- 1811 Eastlake, Seattle
• Compared to controls, housed Ps showed greater reductions in overall costs
• Cost offsets of housing > $4m for 1st year
• More time in housing associated with greater reduction in costs
• 6-mo within-subjects reductions in typical alcohol use
Figure and findings from Larimer et al. (2009)
Mortality
• Ranking of housing from worst to best housing• Private bath better than shared bath• New building better than renovated• Nursing better than no nursing• Senior better than non-senior
Quality of Housing and Outcome
Windsor Empress LeNain PBI CCR West Folsom Dore
Plaza 149 Mason
990 Polk Mission Creek
0.0
5.0
10.0
15.0
20.0
25.0
30.0
R² = 0.76418262009445
Move-out not death
Move-out not deathLinear (Move-out not death)Linear (Move-out not death)
Windsor Empress LeNain PBI CCR West Folsom Dore Plaza 149 Mason 990 Polk Mission Creek
7.6
3.5
6.8
3.9
5.3
2.7
5.0
3.5
2.5
4.0
3.1
R² = 0.388887624467414
Death by Quality of Housing%death
Death Rate/year0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
Death rate Le Nain vs. Mission Creek 2006-2011
Le Nain death %MCSC death %
The more beautiful the housing the better the outcome
POPULATION SNAPSHOT
Veteran PIT Counts, 2009-2012
* CoCs only required to conduct a new count of unsheltered homelessness in odd numbered years; in 2012, only 32% of CoCs opted not to do a new unsheltered count, providing an incomplete picture of trends in the number of unsheltered homeless VeteransSource: PIT data, 2009 - 2012
2009 2010 2011 2012 -
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
75,609 76,329
67,495 62,619
43,409 43,437 40,033
35,143
32,200 32,892 27,462 27,476
Total VeteransSheltered VeteransUnsheltered Veterans
Num
ber o
f Vet
eran
s
*
2010 2011 2012 2013 2014 20150
100
200
300
400
500
600
HennepinLexingtonTacomaFort WorthBirmingham
Measured
-------Projected
______
Number of Homeless Veterans in 5 Communities with Greater than 40% reduction 2010-2012
2005 2006 2007 2008 2009 2010 2011 20120
500
1,000
1,500
2,000
2,500
0%
2%
4%
6%
8%
10%
12%
14%
16%
1,932
1,9141,530
1,470 1,400
812601
542
14%14%
13%
10%
9%
5%4%
3%
Utah Annualized Chronic Homeless Count: 2005-2012
Chronic Count% Chronic of Total Homeless Persons
Source: 2012 Utah Homeless Point-In-Time Count
2009 2010 2011 20120
50
100
150
200
250
300267
224
177
126
Veterans in Minneapolis/Hennepin County 2009 - 2011
total veterans
2009 2010 2011 2012
775 779
566
351
Point-in-time count for Minneapolis/Hennepin County Con-tinuum
total chronic homeless
21.8424.26
17.59
10.36
• Common values and philosophy of practice, strong leadership, housing first
• Targeting• High level of communication (HIPPA busters)• Use of data to inform policy and measure success
Common aspects of “positive outliers”
Creating a Narrative
• Housing is less expensive than homelessness• For people w/ homelessness and AIDS, ARVs are
necessary but not sufficient to improve mortality• The right treatment for the condition
USING DATA TO END HOMELESSNESS
Joshua D. Bamberger, MD, MPHJosh.bamberger@sfdph.org
San Francisco Department of Public HealthUniversity of California, San Francisco, Dept. of
Family and Community Medicine
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