using data to end homelessness joshua d. bamberger, md, mph [email protected] san francisco...
TRANSCRIPT
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USING DATA TO END HOMELESSNESS
Joshua D. Bamberger, MD, MPH
San Francisco Department of Public Health
University of California, San Francisco, Dept. of Family and Community Medicine
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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
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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
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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
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DAH Portfolio
•
253 286604 678 704 704
8780 0
177 247 339
689
0200
400600
8001000
12001400
16001800
99-00 2001-2 2003-4 2005-6 2007-8 2009-10
2011-2015
NewMaster-lease
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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
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• 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
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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)
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Mortality
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• 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
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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)
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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
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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 %
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The more beautiful the housing the better the outcome
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POPULATION SNAPSHOT
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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 Veterans
Source: 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
Nu
mb
er
of
Ve
tera
ns
*
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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
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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
812
601542
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
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2009 2010 2011 20120
50
100
150
200
250
300267
224
177
126
Veterans in Minneapolis/Hennepin County 2009 - 2011
total veterans
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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
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• 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”
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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
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USING DATA TO END HOMELESSNESS
Joshua D. Bamberger, MD, MPH
San Francisco Department of Public Health
University of California, San Francisco, Dept. of Family and Community Medicine