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Health Serv Res. 2020;55(Suppl. 2):797–806.
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wileyonlinelibrary.com/journal/hesr
DOI : 10.1111 /1475-67 73.13 553
THEME ISSUE: DRIVERS OF HEALTH
A randomized trial of permanent supportive housing for
chronically homeless persons with high use of publicly funded
services
Maria C. Raven MD, MPH, MSc1,2 | Matthew J. Niedzwiecki PhD1,2,3 |
Margot Kushel MD4,5
This is an op en access article u nder the terms of the Creative Commons Att ribution License, which per mits use, distrib ution and reproduction in any medium,
provide d the origi nal work is properly cited.
© 2020 The Authors. Health Services Research published by Wiley Peri odicals LLC on behalf of Health Research and Educational Trust
1Department of Emergency Medicine,
University of California , San Francisco, San
Francisco, CA, USA
2Philip R . Lee Inst itute for Health Policy
Studies , University of California, San
Francisco, San Franc isco, CA , USA
3Mathematica Policy Research, Oakland,
CA, USA
4Center for Vulnerable Populations,
University of California , San Francisco, San
Francisco, CA, USA
5Department of Medicine, University of
Califo rnia, San Francisco, San Francisco,
CA, USA
Correspondence
Maria C. Raven , MD, MPH , MSc,
Department of Emergency Medicine,
University of California , San Francisco, 505
Parnassus Ave, Suite U -575, San Francis co,
CA 94143, USA .
Email: maria.raven@ucsf.edu
Funding information
Arnold Ventures
Abstract
Objective: To examine whether randomization to permanent supportive housing
(PSH) versus usual care reduces the use of acute health care and other services
among chronically homeless high users of county-funded services.
Data Sources: Between 2015 and 2019, we assessed service use from Santa Clara
County, CA, administrative claims data for all county-funded health care, jail and
shelter, and mortality.
Study Design: We conducted a randomized controlled trial among chronically home-
less high users of multiple systems. We compared postrandomization outcomes from
county-funded systems using multivariate regression analysis.
Data Collection: We extracted encounter data from an integrated database captur-
ing health care at county-funded facilities, shelter and jails, county housing place-
ment, and death certificates.
Principal Findings: We enrolled 423 participants (199 intervention; 224 control).
Eighty-six percent of those randomized to PSH received housing compared with 36
percent in usual care. On average, the 169 individuals housed by the PSH interven-
tion have remained housed for 28.8 months (92.9 percent of the study follow-up pe-
riod). Intervention group members had lower rates of psychiatric ED visits IRR 0.62;
95% CI [0.43, 0.91] and shelter days IRR 0.30; 95% CI [0.17, 0.53], and higher rates
of ambulatory mental health services use IRR 1.84; 95% CI [1.43, 2.37] compared to
controls. We found no differences in total ED or inpatient use, or jail. Seventy (37
treatment; 33 control) participants died.
Conclusions: The intervention placed and retained frequent user, chronically home-
less individuals in housing. It decreased psychiatric ED visits and shelter use, and
increased outpatient mental health care, but not medical ED visits or hospitalizations.
Limitations included more than one-third of usual care participants received another
form of subsidized housing, potentially biasing results to the null, and loss of power
due to high death rates. PSH can house high-risk individuals and reduce emergent
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1 | INTRODUCTION
Homelessness is associated with high use of acute health care ser-
vices, including emergency department (ED)1,2 and inpatient care.3
Among homeless individuals, a small group (referred to as “frequent
users”) account for a large proportion of all acute service use.4 Most
frequent users are chronically homeless individuals with tri-morbid
chronic physical and mental health conditions and substance use dis-
orders.5-7 In addition to high rates of use of ED and inpatient care,
many have high use of other publicly funded services (jail, home-
less shelters)8,9 and low use of longitudinal, outpatient health care.
Interventions to maintain housing and reduce acute care service use
in this population are a key policy interest for payers and providers.
Permanent supportive housing (PSH), defined as subsidized
housing with closely linked, voluntary supportive services (eg, case
management, physical and mental health services, substance use
treatment services) provides permanent housing for people with
chronic homelessness and behavioral health conditions.10 PSH is of-
fered on a “housing first”11 basis, meaning clients are not required to
be sober or engage in treatment. Most of the literature evaluating
the effect of PSH on health care and other service utilization has
used pre–post, noncontrolled, study designs.12,13 While these have
suggested large reductions in service use, they face threats to inter-
nal validity. By including only people who have enrolled successfully
in PSH, these studies do not provide insights into reach.14, 15 Because
they focus on change in utilization of a group selected on the basis of
high use, they are susceptible to regression to the mean.
Santa Clara, CA created 112 units of PSH earmarked for high
users of multiple public systems of care; over time, the project in-
creased to 130 units. As the population who met criteria greatly
exceeded PSH supply, we utilized lotter y-conditions to conduc t a
randomized controlled trial to examine the reach and effect on ser-
vice use of PSH comparing those randomized to PSH versus usual
care.
2 | METHODS
We evaluated differences in use of county health, shelter and
criminal justice services, housing placement and maintenance, and
mortality, comparing individuals randomized to PSH to usual care.
We used an intention-to-treat framework. Members of the control
group were eligible for PSH provided through other county-funded
programs.
We evaluated Project Welcome Home, a “Pay for Success” based
project to create PSH for the highest users of county public systems
(ED, inpatient services, and jail) in Santa Clara, CA. Approximately
28 percent of units were scattered site and 72 percent were con-
gregated. Most of the congregate units are set-aside units in private
or nonprofit affordable housing buildings. A limited number of other
units are located in converted hotels owned by local housing pro-
viders. Housing and case management services were provided by
Abode Services. Between July 2015 and September 2019, we as-
sessed service use from the Santa Clara County (SCC) administrative
claims data for all county-funded health care, criminal justice, and
shelter services and assessed deaths from county death certificates
for all study participants. The projec t is ongoing.
2.1 | Study screening and enrollment
The screening process includes administrative data screening to de-
termine eligibility by usage criteria, followed by an in-person screen-
ing to determine other eligibility criteria and ability to consent.
Randomization occured after consent. A proprietar y platform inte-
grates study data with real-time data feeds from multiple sources.
Staff screened potential participants based on their use of coun-
ty-funded services over the prior 1-2 years. Our research team
developed an electronic triage tool that uses administrative data
to predict the likelihood of future high use of county-funded ser-
vices. To meet criteria, potential participants must have used various
psychiatric services and shelter use. Reductions in hospitalizations may be more dif-
ficult to realize.
KEY WORDS
criminal justice, frequent users, homelessness, integrated data, permanent supportive housing
What This Study Adds
• We found that the PSH program intervention was able
to house 86 percent of chronically homeless adults ran-
domized to the treatment group based on their high use
of multiple systems who were randomized to the treat-
ment group.
• On average, it took 2.5 months for par ticipants rand-
omized to housing to become housed and 70 percent
moved at least once, demonstrating that PSH can be
successful with high-risk participants but requires time
and flexibility.
• By using a randomized controlled trial design, we found
that those randomized to housing (versus usual care)
had lower use of psychiatric emergency departments
and shelters, but did not have large reductions in service
use described in previous uncontrolled studies.
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combinations of the ED and psychiatric ED, medical and psychiatric
inpatient stays in the County-funded public hospital, and/or jail over
the past 1-2 years, at high enough levels to meet a threshold score.
We embedded the triage tool into the study database and generated
a list of potentially eligible participants with the highest scores, re-
doing the calculation throughout the enrollment period. All county
agencies or service providers could refer individuals they suspected
met eligibility criteria, but study staf f always used the list generated
by the triage tool to confirm initial eligibility. County staf f used this
list to outreach to the highest using individuals.
In addition to meeting threshold use levels, participants had to:
(a) meet the Federal definition of chronic homelessness (homeless
for more than a year or 4 or more episodes in the prior three years
that last for more than a year total, with a disabling condition); (b) live
in SCC; (c) not be incarcerated; (d) not engage in another intensive
case management program or other permanent supportive housing
program; (e) not require nursing home level care; and (f) not have
metast atic cancer or qualif y for hospice care.
After they identified that a prospective participant met eligi-
bility requirements, the staff conducted informed consent, using a
teach-back method to ensure understanding. Then, staff random-
ized participants using a random number generator. Staff referred
individuals randomized to the intervention group to Abode for en-
gagement in the permanent supportive housing. They informed par-
ticipant s randomized to usual care that they remained eligible for
all standard services, including other permanent supportive housing
programs provided by the County. We continued enrollment until all
the units filled and then enrolled additional participants whenever a
unit opened, through participants’ leaving housing, requiring higher
level of care, or death.
2.2 | Intervention
If an individual agreed to engage with Abode, they began to deliver
case management ser vices, even if a housing unit was not yet avail-
able. If the individual did not agree to engage immediately, staff con-
tinued to reach out to build rappor t at least one time per week for six
to nine months (depending on program capacity). If the staff could
not engage the participant, the staff ceased outreach attempts.
Abode's case management services use an Intensive Case
Management16 model. This includes community-based services, pro-
vided by master's level social behavioral health providers, bachelor's
level case managers, and staff with lived experience (peers). Abode
integrated these ser vices with a flexible array of housing options
delivered through a Housing First approach, to provide temporary
housing (if no permanent unit available immediately), permanent
supportive housing, and rehousing (locating new housing units if
the participant was evicted or otherwise lost a unit). Participants re-
ceived a rental subsidy to pay for the housing unit. Caseloads ranged
from 1:10 to 1:15. Abode did not employ nurses or physicians.
Abode offers a range of additional supportive services to par-
ticipants. These include mental health and substance use services;
medication support, community living skills, educational and voca-
tional support, money management, leisure and spiritual opportuni-
ties, and connection to primar y care. Those in the intervention group
who were not lost to follow-up continued to receive case manage-
ment services as part of the PSH intervention throughout the inter-
vention, whether or not they remain housed.
2.3 | Usual care
At the time of enrollment, staff provided all participants randomized
to usual care referrals to shelters and other homeless services.
These participants remained eligible to receive all services pro-
vided for individuals experiencing homelessness in SCC, including
any form of shelter, and temporary or permanent housing, includ-
ing PSH not designated for Project Welcome Home. Staff conduc ted
a Vulnerability Index-Service Prioritization Decision A ssistance
Too l ( V I-SPDAT) 17 assessment, in order to place clients on a list for
County housing interventions. During the intervention period, SCC
created other programs to provide PSH to chronically homeless indi-
viduals, and participants in the control group were eligible to receive
case management services through other county programs.
2.4 | Data
We extrac ted encounter data from the SCC integrated database
that combines county-funded health care utilization data (ED and
inpatient stays for medical or psychiatric causes, outpatient mental
health and substance use treatment, outpatient medical treatment)
with data from the County jail (all jail utilization) and shelter data
from the Homeless Management Information System.
We linked data using participants’ social security numbers,
names, and dates of birth. An out side entit y linked data via an en-
tity resolution process that used name, date of birth, social security
number, and unique identifiers within each system (such as medical
record numbers) coupled with a process to review and update any
matches across systems.
2.5 | Participant characteristics
We defined age at the date of enrollment. We included self-reported
sex, Hispanic ethnicity, race (White, Black, other), smoking status
(current versus former/never), insurance status (Medicaid, Medicare,
or both). We report on service use characteristics for county-funded
services in the two years prior to enrollment.
2.5.1 | Health services utilization
Santa Clara Valley Medical Center (SCVMC), a public safety net
hospital is the main acute care ser vice provider for homeless
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patients in SCC. SCVMC was the source of data for primary care
use, ED visits (including psychiatric ED), and inpatient hospitaliza-
tions (including psychiatric admissions). Hospitals that contract
with SCVMC to provide psychiatric inpatient care provided data.
We did not have access to data on physical health visits from other
settings.
SCVMC provided data on outpatient mental health care and
substance use treatment, including initial and ongoing, group and
individual treatment, including mental health outpatient services
provided by Abode.
We examined whether participants identified a regular source
of non-ED outpatient care. We examined the number of primary
care physician (PCP) visits each year, as recorded in County admin-
istrative data. We defined a PCP visit as a visit to a physician, nurse
practitioner, or physicians’ assistant at a primary care clinic. We cat-
egorized physical health ED visits in three ways: visits that result in
discharge, visits that result in hospital admission, and total visits. We
defined inpatient hospital care as the number of hospital admissions
a participant had at SCVMC. We examined the number of acute bed
days (length of stay). To examine mental health services use, we ex-
amined a participant's number of outpatient mental health appoint-
ments at county facilities, number of visits to the count y psychiatric
ED that resulted in discharge, and number of psychiatric hospitaliza-
tions. Regarding substance use treatment services use, we examined
participants’ number of days in inpatient and outpatient detoxifica-
tion and rehabilitation facilities, as well as other outpatient clinical
substance use services.
2.5.2 | Criminal justice
The Count y provided jail data through the Criminal Justice
Information System for study participants that included the timing
of arrest s and the length of stay in SCC jails.
2.5.3 | Housing and shelter outcomes
For all participants, we repor t on whether they received housing
at any point during the study. For participants in the intervention
group, Abode reported whether and when they obtained, left, and
regained housing. For descriptive purposes, we examined how long
(after study enrollment) it took for Abode to house each par ticipant
and how many times participants needed to be rehoused. To assess
housing retention for those in the intervention group housed by
Abode, we examined the ratio bet ween total days each par ticipant
remained housed and the total possible housing days (the par tici-
pant's first move-in date until the end of the study follow-up period).
We converted our result to months.
For participants in the intervention group who did not receive
housing by Abode and all participants in the usual care group, we ob-
tained data from SCC that identified whether or not the par ticipant
had received housing through other County housing programs. If so,
these dat a included the last recorded date of housing placement and
whether or not the par ticipant remained in housing or exited. For
those who had been housed but had exited, the data included where
they exited to (eg, another housing placement outside of the county;
with family; to homelessness).
For all participants, we checked for any use of the emergency
shelters in SCC through data from the SCC Homeless Management
Information System. We calculated amount of time in shelter. We did
not have data on privately funded shelters.
2.5.4 | Mortality
Abode provided data on death for all participants who died while
living in Abode housing. We queried County death certificate data
on all participants who did not appear in any source of study data for
6 or more months.
2.6 | Data analysis
To assess outcomes, we grouped data into one-year spans of time
for each individual in the treatment and control group. For ex-
ample, if an individual was enrolled for 4 years, they would have
four separate one-year spans in the regression analysis. The use
of spans allows us to include the most available data for each indi-
vidual in the study.
For participants who had potential spans that lasted ≥6 but
<12 months, we prorated utilization counts. To account for outliers
in the data, we top coded all span-level counts to the 99th percen-
tile. We included indicators in the regression analysis to signify the
year in the program in order to account for patterns of use that may
decrease or increase over time.
We censored spans at the time of death. To account for the pos-
sibility that participants moved out of County, we censored data
6 months after the last point of contact and constructed spans with
the data that remained.
We used negative binomial regression analysis on count data
outcomes using an intention-to-treat framework based on assign-
ment to the treatment group. Since the treatment and control groups
were balanced on baseline characteristics, we did not include covari-
ates in the negative binomial regressions. We controlled for the time
since enrollment (span indicators), to account for the differences in
enrollment period. We present results as incidence rate ratios (IRR).
We clustered standard errors at the individual level to account for
individuals with multiple spans.
In sensitivity analyses, we recoded outcome variables to a bi-
nary indicator for whether an individual used any of a given ser-
vice within the one-year span. We conducted sensitivity analyses
(Table S1). We explored allowing the treatment effect to var y by
how long the individual was enrolled in the program by including
interaction terms for treatment status and year indicators (results
not reported).
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3 | RESULTS
3.1 | Sample characteristics
After identification by the triage tool, county or health services
staff approached 426 potential participants. Two refused further
outreach. Study staff approached 424 participants, one of whom
refused consent. We enrolled 423 participants: 199 in the PSH in-
tervention group and 224 in usual care (Figure 1). We repor t on de-
mographics’ and county-funded services’ use in the two years prior
to enrollment in Table 1. We found no meaningful differences in
demographic characteristics between the groups. The participants’
mean age was 51.8 years for treatment, 51.2 years control. Most
were male (72 percent inter vention, 71 percent control). A quarter
identified as Hispanic (24 percent inter vention, 25 percent control).
Two-thirds identified as White (64 versus 66 percent) while a small
propor tion identified as Black (13 percent versus 15 percent). In the
two years prior to enrollment, those in the treatment group aver-
aged 5.1 inpatient admissions, 19.0 ED visits, 3.7 jail stays, and 36.7
shelter days. They had a mean of 6.5 outpatient substance use treat-
ment visits and 26.0 outpatient mental health visits. The control
group utilization was not statistically different from the treatment
group. However, participants in the control group had a higher prev-
alence of reporting a regular source of care in the two years prior to
enrollment (mean 83 percent vs. 70 percent).
3.2 | Descriptive statistics—outcomes
During the follow-up period, 86 percent of those randomized to the
PSH inter vention received housing compared with 36 percent of
those in the control group (Table 2). Of the 199 people randomized
to intervention, 169 received housing through this program; three
received housing through another program. The average time from
enrollment to housing placement was 74.2 days. Of the 169 partic-
ipants housed by Abode, 119 (70.4 percent) moved at least once.
Three-quarters (72.0 percent) of the participants who required
rehousing had no housing gap between placements. On average,
housed intervention group par ticipants moved an average of 2.06
times during the follow-up period (range 1-10 times). The 169 par-
ticipant s housed by Abode have remained housed for an average of
28.8 months and have been retained in housing (without gaps) for
92.9 percent of the possible study follow-up period. When examin-
ing one-year spans over the course of the study, the intervention
group was housed in 84.4 percent of a given span compared to 20.1
percent of those in the control group. (P < .01). Individuals in the
treatment group had 6.6 shelter days per year versus 16.8 in the
control group (P < .01).
Individuals in the treatment group received outpatient mental
health treatment 37.3 times per year versus 19.7 times per year in
the control (P < .01). Those in the treatment group had fewer psy-
chiatric emergency visits per year as compared to the control group:
FIGURE 1 Study Enrollment with
housing and mortality outcomes
comparing PSH intervention group to
usual care. Abbreviation: PSH, permanent
supportive housing
Located aer
triage tool
screening
n=426
Refused further
outreach
n=2
Located for in-
person screen
n=424
Refused consent
n=1
Enrolled
n=423
Died
n=33 (19.2%)
Not housed
n=27 (13.6%)
Ever housed
n=172 (86.4%)
Died
n=9 (11.1%)
Not housed
n=143 (63.8%)
Ever housed
n=81 (36.2%)
Treatment
n=199 (47.0%)
Died
n=4 (14.8%)
Usual Care
n=224 (53.0%)
Died
n=24 (16.8%)
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1.3 visits per year in the treatment group versus 1.9 per year in the
control group (P < .01).
Intervention and control groups had similar levels of ED visits,
inpatient admissions, psychiatric inpatient admissions, jail stays, and
outpatient substance abuse treatment services. We present mean
utilization rates during the study period for outcome variables in-
cluded in the regression analysis in Figure 2.
TABLE 1 Study sample demographic characteristics and health
services use in the t wo years prior to enrollment, treatment versus
usual care
Mean,
Treatment
Mean,
Control Difference
Follow-up duration
Months 35.8 36.8 1.1
Demographics
Male 72% 71% −2%
Hispanic ethnicity 24% 25% 1%
White race 64% 66% 2%
Black race 13% 15% 3%
Other race 23% 19 % −4%
Age in years 51. 8 51. 2 −0.595
Currently Smoking 65% 66% 1%
Insurance
Medicaid insurance 65% 66% 1%
Medicare insurance 73% 73% −1%
Health services use
Regular source of care
(not ED)
70% 83% 14%
Ambulatory care visits 7.3 8.8 1.5
Inpatient psychiatr y stays 0.2 0.3 0.1
Total inpatient stays 5.1 4.8 1.5
Total bed days 14.5 15.1 0.6
ED visits (total) 19.0 20.1 1.1
ED visits discharged
home
16.7 18.0 1.4
ED visits admitted 2.3 2.1 −0.3
Emergency psychiatry
visits
4.7 5.4 0.6
Jail
Jail stays 3.7 2.8 −0.9
Jail days 56.0 61.9 5 .9
Shelter use
Shelter stays 30.8 37. 5 6.6
Shelter days 36.7 42.0 5.2
Outpatient behavioral health
Outpatient subst ance use
treatment visits
6.5 5.5 −1.0
Outpatient mental health
visits
26.0 28.9 2.9
Abbreviation: ED, emergency department.
TABLE 2 Logistic and negative binomial regression analysis of treatment status on Medical, criminal justice, and housing outcomes
Ever housed ED visits
Emergency
psych visits
Total inpatient
stays
Inpatient
psych stays Jail stays Shelter days
Outpatient subst ance use
treatment visits
Outpatient mental
health visits
Treatment Group 22.34** 0.85 0.62* 0.97 0.73 1.01 0.30** 0.76 1.84**
[11.69,42.68] [0.67,1.08] [0.43,0.91] [0 .70,1. 35] [0.3 6,1.45] [0.73 ,1.40] [0.17,0.53] [0.4 6,1. 24] [1. 43 ,2 .3 7]
Span 1 (reference) 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
— — — — — — — — —
Span 2 1.11 0.81** 0.79* 0.80* 0.66 0.89 0.51* * 0.65* 0.95
[0.95 ,1. 29] [0.71,0.93] [0.64,0.97] [0.66,0.96] [0. 31,1.4 4] [0.76,1.04] [0.33,0.78] [0.45,0.95] [0.82,1.09]
Span 3 1.13 0.74** 0.80 0.70* 0.78 0.83 0.34** 0.18** 0.86
[0.91,1.40] [0.62,0.88] [0.63,1.01] [0.53,0.92] [0. 35,1. 74] [0. 67,1.02] [0.21,0.55] [0.13,0.27] [0.71,1.05]
Span 4 1. 51* 0.63** 0.69* 0.51* * 0.61 0.81 0.32** 0.16** 0.85
[0. 84,2 .11] [0.49,0.81] [0.49,0.97] [0.35,0.75] [0.21 ,1.8 2] [0.61,1.08] [0.14,0.73] [0.09,0.27] [0.67,1.09]
N1070 1070 1070 1070 1070 1070 1070 1070 1070
Note: All re sults presented as an odds ratio for the binary outcome “ever housed” from a logistic regre ssion and as incidence r ate ratios for all other outcomes from negative binomial regressions. 95% confidence
intervals also presented. Covariates include treatment status as well as span indicators to control for the time since enrollment. No other covariates were included as the treatment was randomly assigned.
Abbreviation: ED, emergency department.
*P < .05, **P < .01.
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A total of 37 (18.6 percent) in the intervention group and 33 (14.7
percent) in the control group died during the study follow-up period.
Of those who died, 89.2 percent of those in the intervention group
had ever received housing during the study period, compared with
29.0 percent of those in the control group.
3.3 | Regression analysis
The treatment group was more likely to be ever housed during
the study period (odds ratio [OR]: 22.34, 95% CI: [11.69,42.68]).
The inter vention group had nearly two-thirds fewer days in shel-
ter compared to the control group (IRR: 0.30, 95% CI: [0.17, 0.53]).
Individuals in the treatment group had nearly twice as many outpa-
tient mental health visits as those in the control group (IRR: 1.84,
95% CI: [1.43,2.37]). Assignment to the treatment group was associ-
ated with a 38 percent reduction in psychiatric ED visits (IRR: 0.62,
95% CI: [0.43,0.91]).
No other differences were statistically significant. Those in the
treatment group had 15 percent fewer ED visits (IRR: 0.85, 95% CI:
[0.67,1.08]) and 27 percent fewer psychiatric inpatient admissions
(IRR: 0.73, 95% CI: [0.36,1.45]) but the difference did not reach
statistical significance. Both groups had similar rates of inpatient
admissions (IRR: 0.97, 95% CI: [0.70,1.35]) and jail stays (IRR: 1.01,
95% CI: [0.73,1.40]). Those in the treatment group received 24 per-
cent fewer outpatient substance use treatment visits (IRR: 0.76,
95% CI: [0.46,1.24]), but the result was not statistically significant.
When we interacted treatment status with year of enrollment, we
found no statistically significant dif ferences in the treatment effect
for any of the outcomes studied, although we were underpowered
to do so. We examined differences in the number of hospital days
and jail days as secondar y outcomes and found no differences.
(Appendix S1).
4 | DISCUSSION
In a randomized control trial comparing chronically homeless indi-
viduals who were the highest users of multiple systems of care in
Santa Clara, CA randomized to receive permanent supportive hous-
ing versus usual care, we found that participants randomized to
PSH experienced reductions in psychiatric ED and shelter use but
no reductions in use of medical EDs, hospitals, or jail. Despite the
social complexity of the study participants, 86 percent of those ran-
domized to PSH entered housing and remained in housing for the
vast majority (92.9 percent) of the study follow-up period.
We found a significant reduction in use of psychiatric emergency
services and a concomitant increase in scheduled mental health vis-
its. Project Welcome Home included Intensive Case Management
with a low client-staff ratio led by licensed staff with behavioral
health training. Research has shown that experiencing homeless-
ness is one factor that leads to ED visits among psychiatric patients,
suggesting an unmet need for ment al health care.5,1 8 Our findings
suggest that these visits are amenable to prevention by providing
housing with associated low-barriers mental health ser vices. We did
not find a significant reduction in other acute medical care visits, al-
though the point estimates for both ED visits and psychiatric admis-
sions were less than one. These results differ from those reported
in studies of PSH that used uncontrolled designs. These found large
reductions in service use.12,19, 20 Without controls, these findings are
susceptible to regression to the mean.20, 21 Our finding of decreased
use in later span years independent of group assignment suggests
regression to the mean. Two related RCTs found statistically signifi-
cant reductions in ED visits, nonstatistically significant reductions in
inpatient medical hospitalizations and increases in psychiatric hos-
pitalizations.11,22 People who are high users of services likely have
unmet health needs that become apparent once housed. Our results
may have underestimated improvements due to misclassification:
FIGURE 2 Outcome variables, PSH intervention versus usual care. Abbreviations: ED, emergency department; PSH, permanent
supportive housing [Color figure can be viewed at wileyonlinelibrary.com]
40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0
inpaent psych stays
total inpaent stays
emergency psych visits
ED visits
Treatment
Control
mental health outpaent visits
outpaent substance use treatment
shelter days
jail stays
total bed days
804
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RAVEN Et A l.
14 percent of participant s in our study did not engage in housing,
although most of these participants did receive case management
services. At the time of the study, SCC increased it s provision of
PSH.23 Thirty-six percent of those in the control group received PSH
or other forms of subsidized housing through other programs. This
would bias our results toward the null and could have obscured our
ability to see subtle differences.
Despite selection criteria that identified those at highest risk
for frequent utilization, and thus, most likely to experience mental
health and substance use disabilities, we found the 86 percent of in-
dividuals randomized to PSH entered housing and remained housed,
on average, for 93 percent of the time in the study. Engagement and
retention in housing is an important priority for policy makers.24
Our selection criteria aimed to identify those who were the high-
est users of services. Similar to Coordinated Entry, a Housing and
Urban Development policy that requires Counties to prioritize those
with the most significant barriers to housing to receive housing and
homeless assistance services, we designed the triage tool to iden-
tify those who, due to their high use of acute care services and jail,
likely faced the biggest barriers. Thus, our study has implications for
jurisdic tions who are using coordinated entr y to provide PSH only
to those at highest risk. After our initial screening using administra-
tive data, only two individuals refused additional outreach and, after
screening in, only one refused to participate in randomization, sug-
gesting that this population is interested in receiving services. We
found that by providing housing with appropriate services, the vast
majority of high-risk individuals could be housed successfully. Prior
pre–postliterature has suggested that upwards of 85 percent of peo-
ple engaged in PSH remain housed. We found that 86 percent of
high-risk individuals randomized to the intervention entered hous-
ing and these individuals remained housed for the vast majority of
the time. This finding extends the finding of pre–poststudies in two
ways. While pre–poststudies cannot address the issue of engage-
ment, we found that, even among the highest risk population, the
intervention was able to engage 86 percent in housing. Our study's
use of a targeting tool include people whose usage patterns sug-
gest that they will have the highest ongoing acute care use provides
additional reassurance that even the most high-risk individuals can
be successfully housed using a Housing First approach with inten-
sive case management. The housing patterns we found, however,
suggest the need for flexibilit y. Consistent with the experience of
many Housing First programs, over t wo-thirds of the housed inter-
vention participants required rehousing after their first placement
did not succeed. The ability to offer a new housing placement is a
key component of successful Housing First strategies when work-
ing with high complexit y populations. With the widespread use of
Coordinated Entry that will require that counties place individuals
with similar risk profiles into PSH, our findings provide support for
the need for flexibility, including the ability to rehouse individuals,
in order to serve those at highest risk. Our results offer a measured
sense of expected changes in their use of other services.
We found a similar high mortality rate in both treatment and con-
trol groups. Individuals experiencing homelessness have a greater
age-adjusted mortality rate than housed counterparts. 25 Among
those who died, 89 percent of those in the intervention group had
been housed compared with 28 percent in the control group. After
longst anding homelessness, housing may not be sufficient to pre-
vent or delay death. However, avoiding deaths while people are
homeless has value. The study excluded those with metastatic can-
cer or those who health c are providers deemed eligible for hospice.
The high death rate despite these exclusions suggests the vulnera-
bility of the population and the challenge of predicting mortality. It
is possible that some of the participants would have benefited from
referral to a higher level of c are instead of PSH. This requires further
evaluation.26,27
We found no differences in criminal justice system encounters
betwee n participant s in the intervention and contro l groups, which is
consistent with prior research. 28 Individuals experiencing homeless-
ness are more likely to be arrested for offenses that can be directly
attributed to the state of being homeless, 29 including trespassing,
sleeping in vehicles, panhandling, and public use of illicit drugs and
alcohol. City-wide bans on public camping and panhandling have in-
creased by 69 and 43 percent, respectively, over the past decade.30
The lack of a difference may be attributed to the fact that some of
the jail st ays experienced by individuals who received housing were
caused by outstanding warrants that the criminal justice system
served once the individual received housing. For this high-risk pop-
ulation, programs to help detect and mitigate risk of criminal justice
involvement, as well as policies that support alternatives to incarcer-
ation, may need to be better integrated into PSH programs. This will
require future study.
4.1 | Limitations
Our study has impor tant limitations. We used a randomized, inten-
tion-to-treat framework so that all individuals who enrolled in the
study were included when evaluating outcomes. Sixteen percent of
individuals in the treatment group never received housing, and 36
percent of those in the control group received PSH through other
programs during a time of expansion of PSH in Santa Clara.23 This
could bias our findings toward the null. In addition, our higher-than-
expected mortality rate among participants limited follow- up peri-
ods for par ticipants who died. It is possible that we missed deaths
among the control group. This would ar tificially reduce service uti-
lization in this population and bias results toward the null. Only a
minority of individuals had a history of criminal justice system inter-
actions in the 2 years prior to enrollment. This may have limited our
power to detect differences, although our findings are consistent
with prior research. We had access to an integrated database that
allowed us to examine use of multiple county services. However,
we were unable to detect service use that may have occurred either
outside of the county or that occurred in other health care facilities
within SCC , with the exception of psychiatric inpatient services. This
may have led to underestimation of ser vice use in the study popu-
lation. If enrollment in the PSH intervention resulted in increased
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RAVEN Et A l.
likelihood of referral for medical care to the County hospital (as com-
pared to other hospitals in the County), this may have differentially
impacted our abilit y to detect service use in the inter vention group.
Alternatively if, due to their housing, participants in the intervention
group preferentially increased their use of other hospitals, this could
have led us to deflate use in the intervention group.
5 | CONCLUSIONS
We found PSH delivered in a Housing First method delivering ser-
vices through an Intensive Case Management model with a low
client to staff ratio successfully housed chronically homeless individ-
uals who were high users of multiple public systems of care. While
the inter vention reduced use of the psychiatric ED and shelters
and increased housing, it did not reduce ED use for physical health
care or hospitalizations. We found high death rates for participants
in both groups, emphasizing the medical frailty of the population.
While early, uncontrolled, studies of PSH may have overstated ex-
pected reductions in inpatient and ED care, these reductions may be
harder to realize in high need populations who experience underuse
of services. However, the intervention's ability to house, success-
fully, a high proportion of the most high-risk chronically homeless
population who were the highest user of multiple systems of care
demonstrates the potential of Housing First to house the highest
risk individuals.
ACKNOWLEDGMENTS
Joint Acknowledgment/Disclosure Statement: This publication was
supported by a grant from Arnold Ventures with assistance from
Santa Clara County and Abode Services. Its contents are solely the
responsibility of the authors and do not necessarily represent the
official views of Arnold Ventures, Santa Clara County, or Abode
Services. All authors conceived of and designed the study, inter-
preted the data, and contributed substantially to the article's revi-
sion. M. N. analyzed the data and M. C. R., M. K., and M. N. assisted
with data interpretation. M. C . R. and M. K. drafted the article. M.
C. R. had full access to all of the data in the study and takes respon-
sibility for the paper as a whole. The authors would also like to ac-
knowledge Vivian Way and St acey Murphy of Abode Ser vices, Greta
Hansen of Santa Clara County, and Alice Yu of Palantir for their as-
sistance with data extraction, quality assurance and technical sup-
port, as well as Virginia Chan for her administrative support.
ORCID
Matthew J. Niedzwiecki https://orcid.
org/0000-0001-9005-9054
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SUPPORTING INFORMATION
Additional suppor ting information may be found online in the
Supporting Information section.
How to cite this article: Raven MC , Niedzwiecki MJ, Kushel M.
A randomized trial of permanent supportive housing for
chronically homeless persons with high use of publicly funded
services. Health Ser v Res. 2020;55(Suppl. 2):797–806. h t t ps : //
doi .or g/10 .1111/1475 -6773.13553
