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Abstract

Objective:

The At Home/Chez Soi trial for homeless individuals with mental illness showed scattered-site Housing First with Assertive Community Treatment (ACT) to be more effective than treatment as usual. This study evaluated the cost-effectiveness of Housing First with ACT and treatment as usual.

Methods:

Between October 2009 and June 2011, a total of 950 homeless individuals with serious mental illness were recruited in five Canadian cities: Vancouver, Winnipeg, Toronto, Montreal, and Moncton. Participants were randomly assigned to Housing First (N=469) or treatment as usual (N=481) and followed up for up to 24 months. The intervention consisted of scattered-site Housing First, using rent supplements, with ACT. The treatment-as-usual group had access to all other services. The perspective of society was adopted for the cost-effectiveness analysis. Days of stable housing served as the outcome measure. Retrospective questionnaires captured service use data.

Results:

Most (69%) of the costs of the intervention were offset by savings in other costs, such as emergency shelters, reducing the net annual cost of the intervention to about Can$6,311 per person. The incremental cost-effectiveness ratio was Can$41.73 per day of stable housing (95% confidence interval=Can$1.96–$83.70). At up to Can$60 per day, Housing First had more than an 80% chance of being cost-effective, compared with treatment as usual. Cost-effectiveness did not vary by participant characteristics.

Conclusions:

Housing First with ACT appeared about as cost-effective as Housing First with intensive case management for people with moderate needs. The optimal mix between the two remains to be determined.

HIGHLIGHTS

In the At Home/Chez Soi Canadian trial of Housing First with assertive community treatment (ACT), about two-thirds of the costs of the intervention were offset by savings in other costs.
The net cost of the intervention per additional day of stable housing and the actual cost of the intervention per day are well within the range of the costs of many currently funded housing programs for people experiencing homeless that do not provide individualized and intensive services such as ACT.
The intervention appeared cost-effective regardless of participant sex, alcohol or drug abuse or dependence, level of functioning, prior hospitalizations, or recent arrest history.
A significant minority of homeless people experience serious mental illness (1). Housing First, which provides immediate access to subsidized housing together with support services, has proven the most effective approach to helping such individuals access and maintain permanent housing (2). Previous analyses have reported significant cost offsets associated with the provision of Housing First (3).
The At Home/Chez Soi trial compared outcomes of the scattered-site variant of Housing First, in which participants receive rent supplements for private-market apartments of their choice (4), to outcomes of treatment as usual. The trial tested, in parallel, both Housing First with assertive community treatment (ACT) (5, 6) for people who had more severe mental illness and functional difficulties (7) and Housing First with intensive case management for those whose needs were less severe (8). A cost-effectiveness analysis of Housing First with intensive case management has recently been published (9). Summary results of a cost analysis of Housing First with ACT, but not a cost-effectiveness analysis, were included in the main trial reports (7, 10). Herein we report on the cost-effectiveness of Housing First with ACT, compared with treatment as usual.

Methods

The cost-effectiveness analysis conformed to the published protocol of the At Home/Chez Soi study (4) and followed the Consolidated Health Economics Evaluation Reporting Standards (CHEERS) reporting guideline (11). The analysis began in 2013 and ended in 2019. The trial was conducted in Vancouver, Winnipeg, Toronto, Montreal, and Moncton. Ethics approval was obtained from the local ethics review board at each data collection site and from the Centre for Addiction and Mental Health, where the coordinating center was based (4). Participants provided written informed consent after the screening interview. The methods used were the same as those used for the cost-effectiveness analysis of Housing First with intensive case management compared with treatment as usual (9).

Participants

Details on sample recruitment are available elsewhere (4, 7). Briefly, potential participants were referred from various sources or found through street outreach. Inclusion criteria were adult age (≥18 years), legal status in province of residence, current mental disorder, and either absolutely homeless or precariously housed with previous episodes of absolute homelessness. Individuals who were currently receiving services from an ACT or intensive case management team were excluded.

Sample Recruitment and Randomization

Following the baseline interview, a computerized algorithm classified individuals as high need or moderate need. To be classified as high need, individuals needed to have a lower level of functioning (score of ≤62 on the Multnomah Community Ability Scale [12]); have a current diagnosis of a psychotic disorder or bipolar disorder; and have at least one of the following: two or more hospitalizations for mental illness within a 1-year period at some point during the previous 5 years, comorbid substance use, or one or more arrests or incarcerations in the past 6 months. Others were classified as moderate need. In Moncton, all participants were classified as high need because of the relatively small pool of potential participants (4). High-need individuals were randomly assigned to receive either Housing First with ACT or other services normally available to them (i.e., treatment as usual) (7). An adaptive randomization algorithm with allocation concealment was used (13). From October 2009 through June 2011, 950 individuals who met the criteria to be considered high need were recruited.

Interventions

Participants in the Housing First with ACT group received recovery-oriented supports from an ACT team with about ten participants per case manager (eight per case manager in Montreal), not counting a psychiatrist, who served most or all of the participants assigned to the team. In Moncton, a family physician with extensive experience working with homeless individuals served as the clinical lead. Each ACT team worked in collaboration with housing specialists, also paid by the project, to help participants find housing of their choice, usually an apartment on the private rental market, and maintain positive relations with landlords. Participants were required to pay 25% or 30% of their income toward the rent, depending on whether the rental amount covered heating costs. The project paid the remainder of the rent, and this supplement ranged from a mean of about Can$375 in Montreal to Can$600 in Vancouver. [Hereinafter, all currency is expressed in Canadian dollars.] Two assessments of fidelity of local implementation to the program model, one about 1 year after launch of the program and a second after 3 years of operation, combined with ongoing coaching, aided standardization of the interventions across sites (14).
Participants assigned to treatment as usual had access to services such as shelters, hospitals, and community-based health and housing services (15). A small number of treatment-as-usual participants also were able to access intensive case management or ACT services from other sources after they entered the study.

Data Collection

Participants were followed for up to 21 or 24 months. At baseline and every 6 months thereafter, a battery of standardized self-reported questionnaires was administered (4). Measures included three questionnaires adapted for this study and designed to assess use of services (4). Participants completed the Health Services and Justice Services Use (HSJSU) questionnaire at baseline and every 6 months thereafter. The HSJSU documented all non-overnight health and justice-related services. The Residential Time-Line Follow-Back instrument was administered every 3 months and asked participants where they had spent every night since the previous interview. To enable estimation of costs associated with service use, this instrument allowed coding of simultaneous places of residence—for example, if a participant had an apartment and was hospitalized, costs were associated with both places concurrently. Finally, the Vocational Time-Line Follow-back asked about income received month by month and any regular or casual work obtained during the previous 3 months (16). Because of the nature of the intervention and the inclusion of measures on service use and housing, neither participants nor interviewers could be blinded.

Choice of Outcome Measure

Days of stable housing (as assessed by the Residential Time-Line Follow-Back instrument) served as the outcome measure. Places where people stayed were classified as stable (own apartment, social housing, or with one’s parents as long as housing could be maintained for ≥6 months) or unstable.

Perspective of the Economic Analysis

As discussed in detail elsewhere (15), cost elements were collected and analyzed from the perspective of society (17). We modified this perspective slightly, following Weisbrod et al. (18), in that we included social assistance and disability benefits as costs. This modified societal perspective may be viewed as consistent with a social cost impact analysis (19, 20).

Calculation of Costs per Individual

We calculated many unit costs at a high level of specificity, distinguishing, for example, among supportive housing providers with different staffing levels. Whenever possible, we used financial statements and activity reports to estimate a fully allocated average cost of a service (21). The unit costs that we used and the methods that we used to derive them have been described elsewhere (15).
Unit costs for the intervention were based on reported expenses of each clinical team and housing provider. Program expenses were distributed among participants on the basis of the time that each had been receiving services from his or her clinical team, as estimated by using the HSJSU questionnaire, and on the basis of the number of nights that each had a subsidized apartment or housing unit provided by the project.
All unit costs were originally in 2011 Canadian dollars or adjusted to 2011 dollars. We used the city-specific Consumer Price Index to convert costs into 2016 Canadian dollars (22). We calculated costs per individual by multiplying frequencies by the corresponding unit cost, including the intervention cost for experimental group participants, and adding to that social assistance and other contributions by society to their income and subtracting income earned (15, 23).

Discounting

For each participant, costs as well as days stably housed were estimated over a 2-year period. Costs and days of stable housing in the second year were discounted at a 3% rate, a common rate for a base case analysis (21).

Statistical Analysis

All analyses employed multiple imputation with chained equations (20 imputations) to account for missing data (24). Mean costs per year after randomization, aggregated across sites but grouped into different categories (15), were compared between the Housing First with ACT and treatment-as-usual groups at baseline and over each of the 2 years after baseline. Mean total costs per year were then compared site by site between the Housing First with ACT and treatment-as-usual groups.
Confidence intervals for incremental cost-effectiveness ratios (ICERs) were computed via bootstrapping, with 500 bootstrap resamples (24, 25). We plotted the bootstrap resamples on the cost-effectiveness plane.
We then used the net-benefit approach to describe further the impact of sampling uncertainty (21). The intervention is deemed cost-effective if λμΔE–μΔC > 0, where λ is the threshold ratio (in dollars per additional day of stable housing) above which the decision maker no longer finds the intervention cost-effective, μΔE is the average difference in effectiveness between the two groups, and μΔC is the average difference in costs. Using the bootstrap resamples, we plotted the cost-effectiveness acceptability curve, showing the estimated probability that the intervention is cost-effective as a function of λ.
We then regressed, using values of λ ranging from $0 to $100, each individual’s net monetary benefit (λei–ci,, where λ has the same meaning as above, ei is the individual’s annualized number of days of stable housing during the 2-year follow-up, and ci is the individual’s annualized cost during the same period) on several variables selected a priori as potentially relevant. These variables included group assignment, site, age, sex, presence of psychotic disorder, Multnomah Community Ability Scale score, duration of longest previous episode of homelessness, and number of hospital days in the year prior to study entry. To evaluate how participant characteristics might mediate the cost-effectiveness of Housing First (21, 26) and in the absence of any strong a priori hypotheses about which characteristics might be relevant, we then tested, one by one, interactions between these variables and the group assignment variable. We retained interaction terms with a two-sided p<0.1 for a final model with interactions. Fitted models were checked for misspecification by plotting the residuals against the fitted value of the dependent variable as well as continuous covariates. The Rubin rule was used to derive 95% confidence intervals (CIs) (24). Statistical analyses were performed with Stata, version 15.

Sensitivity analyses

We tested the robustness of the results to the choice of discount rate by using 5% and 0% instead of 3%. We also checked the effects of adjusting for baseline differences in costs, using a regression-based method (27), and performed a two-way sensitivity analysis on these factors.

Results

A total of 950 individuals were originally randomly assigned: males, N=649, 68%; females, N=291, 31%; and other, N=10, 1%; ages 30–49, N=555, 58%. Of these 950, a total of 917 (97%) provided useable data for this analysis. (A chart showing participant flow into and through the trial is included in an online supplement to this article.)
Table 1 provides descriptive statistics for the sample at baseline. Participants’ longest single period of homelessness was 33.8±50.2 months. Values for other variables not used in this analysis have been reported elsewhere (7).
TABLE 1. Baseline characteristics of participants, by randomization group
 Housing First (N=469)Treatment as usual (N=481)
CharacteristicN%N%
Age group    
 <301102410923
 30–492806027557
 ≥5079179720
Sex    
 Female1433114831
 Male3206832968
 Other6141
Substance abuse or dependence    
 Alcohol2134522346
 Drug2866128058
 Alcohol or drug3337135975
Hospitalization historya2385126154
Arrest historyb2014320342
Homelessness    
 Longest period (M±SD months)35.1±53.6 32.6±46.7 
 Median period (interquartile range)16 (6, 36) 13 (6, 36) 
MCASc    
 Score (M±SD)54.5±7.4 54.4±7.2 
 Median (interquartile range)55.0 (50.0–60.0) 55.0 (50.0–60.0) 
Study site    
 Moncton1012210021
 Montreal81178217
 Toronto972110021
 Winnipeg100219921
 Vancouver901910021
a
Two or more hospitalizations within 1 year at some point during the 5 years before baseline.
b
One or more arrests or incarcerations during the 6 months before baseline.
c
Multnomah Community Ability Scale. Possible scores range from 17 to 85, with higher values indicating better functioning.
Table 2 shows costs at baseline and for the first year and second year, by type of cost, for the Housing First and treatment-as-usual groups. During the 2-year follow-up period, meaningful cost offsets (mean reductions in costs attributable to the intervention) were observed for shelters (–$1,943), supportive housing (–$1,793), ambulatory visits (–$4,759), and incarcerations (–$1,485). For other cost categories, the 95% CIs for offsets included zero, or the point estimate was less than $1,000. Excluding the intervention cost, the total mean cost offset was –$14,056. However, after including the mean cost of the intervention ($20,367, calculated from Table 2), the mean total per person cost for Housing First participants exceeded that for treatment-as-usual participants by $6,311. Thus 69% of the cost of the intervention was offset, reducing its net cost to $6,311. For most services, as well as in total, the cost difference was less favorable to Housing First in the second year than in the first.
TABLE 2. Mean (unadjusted) costs (2016 Can$) per person per year in the two randomization groups, by cost category and timea
 Treatment as usual (N=454)Housing First (N=463)Difference (Housing First– treatment as usual)
Cost category and timeM95% CIM95% CIM95% CI
Shelters      
 Baseline6,4125,518, 7,2876,2455,347, 7,037–168–1,363, 980
 First year4,3633,751, 5,0911,8401,502, 2,247–2,523–3,373, –1,821
 Second year2,2801,819, 2,748917664, 1,205–1,364–1,891, –853
 Mean of first and second years3,3222,836, 3,8531,3791,125, 1,669–1,943–2,554, –1,431
Substance use treatment      
 Baseline1,171644, 1,8221,476828, 2,169305–659, 1,139
 First year1,7941,134, 2,681604347, 896–1,190–2,085, –416
 Second year1,325843, 1,813921530, 1,346–404–1,061, 222
 Mean of first and second years1,5591,108, 2,109762505, 1,018–797–1,463, –256
Supportive housingb      
 Baseline2,1461,536, 2,9161,506992, 2,207–640–1,494, 224
 First year2,5761,977, 3,287608412, 830–1,968–2,690, –1,370
 Second year2,3671,814, 3,007750497, 1,054–1,617–2,288, –955
 Mean of first and second years2,4721,956, 3,053679497, 893–1,793–2,437, –1,249
Ambulatory visits      
 Baseline14,75512,499, 17,15018,58515,438, 21,6183,83052, 7,725
 First year11,4809,591, 13,6835,1454,460, 5,881–6,335–8,714, –4,212
 Second year8,0816,726, 9,8474,8984,053, 5,993–3,182–5,092, –1,358
 Mean of first and second years9,7808,437, 11,4885,0214,400, 5,649–4,759–6,495, –3,233
ED visits      
 Baseline2,8342,418, 3,2753,4232,729, 4,126590–220, 1,378
 First year1,8501,535, 2,2981,9151,467, 2,34065–581, 578
 Second year1,5291,230, 1,9201,7891,421, 2,163260–273, 712
 Mean of first and second years1,6891,402, 2,1051,8521,466, 2,249162–419, 600
Hospitalizations (physical)      
 Baseline1,518474, 2,8422,300875, 4,071782–1,374, 2,838
 First year2,4981,403, 3,8812,2921,200, 3,667–205–2,081, 1,815
 Second year4,2682,701, 6,2693,1751,969, 4,557–1,093–3,535, 1,038
 Mean of first and second years3,3832,228, 4,6572,7341,960, 3,841–649–2,109, 950
Hospitalizations (psychiatric)      
 Baseline21,49116,241, 27,28025,20919,442, 31,3783,718–4,218, 11,669
 First year13,1539,270, 16,98411,0967,929, 14,175–2,057–7,028, 3,366
 Second year11,7988,353, 15,4177,6895,173, 10,586–4,109–8,762, 360
 Mean of first and second years12,4768,982, 16,2269,3937,086, 11,811–3,083–7,216, 1,275
Other (e.g., help lines, day centers)      
 Baseline3,3702,937, 3,8643,1982,681, 3,691–172–846, 471
 First year1,5931,412, 1,8081,3901,170, 1,610–203–483, 85
 Second year1,066909, 1,242999813, 1,178–67–313, 174
 Mean of first and second years1,3291,185, 1,4831,1941,009, 1,359–135–350, 89
Police      
 Baseline12,81110,920, 15,12311,0779,220, 13,032–1,734–4,834, 1,246
 First year9,0037,372, 10,9387,9686,530, 9,409–1,035–3,561, 1,245
 Second year6,7795,638, 8,1196,5345,301, 7,937–245–1,976, 1,566
 Mean of first and second years7,8916,667, 9,2017,2516,096, 8,478–640–2,411, 1,117
Incarcerations      
 Baseline3,7372,641, 5,0213,4222,305, 4,499–315–1,954, 1,349
 First year4,2563,105, 5,3902,9481,971, 3,942–1,308–3,001, 257
 Second year4,7473,487, 6,1233,0842,185, 4,085–1,663–3,309, –28
 Mean of first and second years4,5013,423, 5,5553,0162,125, 3,851–1,485–3,001, –73
Welfare and disability benefits      
 Baseline2,6512,505, 2,8262,9312,766, 3,10627936, 531
 First year8,2447,908, 8,6258,9548,574, 9,321711159, 1,235
 Second year9,0238,688, 9,3699,6529,281, 10,026629117, 1,110
 Mean of first and second years8,6338,325, 8,9659,3038,948, 9,641670190, 1,119
Income earned      
 Baseline280178, 38512176, 180–159–278, –34
 First year903613, 1,266428306, 584–474–858, –159
 Second year1,001732, 1,322682455, 913–319–716, 36
 Mean of first and second years952677, 1,277555400–733–397–776, –105
Total excluding intervention cost      
 Baseline71,73865,179, 78,10178,14471,198, 85,6206,406–2,831, 16,234
 First year59,90654,486, 65,26344,33240,338, 47,822–15,575–21,716, –9,225
 Second year52,26247,354, 57,28539,72535,903, 43,701–12,537–18,849, –6,396
 Mean of first and second years56,08451,501, 60,82842,02838,750, 45,141–14,056–19,823, –8,991
Total including intervention cost      
 First year59,90654,486, 65,26365,98861,727, 69,9686,081–592, 12,710
 Second year52,26247,354, 57,28558,80254,073, 63,4156,540–467, 12,904
 Mean of first and second years56,08451,501, 60,82862,39558,843, 65,8976,311309, 12,350
a
Usable data for 917 of the 950 participants were available for analysis. For days of stable housing, 27 elements (one per month and three before the baseline interview) were included. Missing rates (addressed by using multiple imputation) were 18% for the treatment-as-usual group and 14% for the Housing First group. For costs, 279 elements were included; missing rates were 16% and 13%, respectively.
b
Includes both rooms in buildings with on-site support staff and, notably for Toronto, subsidized rooms in buildings without on-site support staff.
Table 3 disaggregates costs by site rather than by cost category. The magnitude of the mean net cost, including the cost of the intervention, ranged from –$4,386 in Toronto to $14,815 in Moncton. Toronto was the only site where the point estimate was negative, indicating that the intervention resulted in reductions in costs in other categories that exceeded the cost of the intervention itself. All confidence intervals except that for Moncton included 0.
TABLE 3. Total (unadjusted) annualized costs (2016 Can$) per person in the two randomization groups, by sitea
 Treatment as usual (N=454)Housing First (N=453)Difference (Housing First– treatment as usual)
Cost category and timeM95% CIM95% CIM95% CI
Cost of ACT teamb    
 Moncton  7,2055,954, 8,797  
 Montreal16,26113,739, 19,241
 Toronto13,06610,581, 15,417
 Winnipeg12,6209,592, 15,886
 Vancouver15,61313,506, 18,375
Cost of housing team and rent supplements    
 Moncton  9,6039,149, 10,111  
 Montreal5,5654,839, 6,196
 Toronto8,4757,712, 9,221
 Winnipeg4,9374,355, 5,446
 Vancouver9,2748,571, 9,890
Total cost without intervention      
 Moncton29,56624,993, 34,25827,57321,184, 35,632–1,993–10,572, 7,107
 Montreal70,25859,501, 80,56749,85743,625, 56,715–20,401–32,669, –7,594
 Toronto76,96064,376, 91,22351,03443,040, 58,835–25,926–41,936, –11,896
 Winnipeg47,94740,769, 54,58640,21035,215, 45,329–7,737–16,761, 1,154
 Vancouver59,27248,895, 70,41643,73837,065, 51,032–15,534–28,201, –3,463
Total cost including      
intervention      
 Moncton29,56625,117, 34,37144,38137,542, 51,16514,8156,577, 23,074
 Montreal70,25860,757, 80,72471,68265,488, 77,8551,424–10,509, 13,195
 Toronto76,96065,404, 90,37972,57463,420, 82,072–4,386–22,357, 9,243
 Winnipeg47,94741,003, 57,10357,76651,512, 65,5059,820–460, 20,763
 Vancouver59,27248,814, 69,95468,62561,217, 77,1189,353–4,815, 21,993
a
Usable data for 917 of the 950 participants were available for analysis.
b
ACT, assertive community treatment.
Days with stable housing were higher by 151.30 days (95% CI=137.67–166.86) in the Housing First group, compared with the treatment-as-usual group, with a cost difference of $6,310.93 (95% CI=$309.31–$12,349.65). Thus the ICER was $41.73 per additional day of stable housing (95% CI=$1.96–$83.70).
A figure in the online supplement shows 500 bootstrap replicates of mean incremental cost and the corresponding mean incremental number of days of stable housing. All but a few points fell into the upper right-hand quadrant, with the others in the lower right-hand quadrant, indicating that taking all sites together, the intervention unambiguously increased days stably housed and almost certainly increased costs as well.
The cost-effectiveness acceptability curve shown in Figure 1 indicates that if, for instance, the decision maker is willing to pay up to $60 per night stably housed, there is a more than 80% chance that Housing First is cost-effective, compared with treatment as usual. If the decision maker is willing to pay up to nearly $100 per day of stable housing, then the probability that the intervention is cost-effective increases to 100%.
FIGURE 1. Cost-effectiveness acceptability curve for Housing First, by willingness to pay up to $250 per night of stable housing
A table in the online supplement shows the results of net benefit regressions that do not include interactions. As the decision maker’s willingness to pay for an additional day of stable housing (represented by λ) rises from 0 to $100, the adjusted net benefit of receiving Housing First is initially negative (net benefit of –$6,147 per person per year) but increases quickly, so that at $100 the net benefit is positive, reaching $8,975. Adjusted net benefit was lower in Vancouver, Toronto, and Montreal, compared with Moncton, the more so the greater the value assigned to a day of stable housing. The cost of usual services was less in Moncton to begin with (15), so there was less potential to offset costs in that city. Thus the net cost of the intervention per additional day of stable housing was greater in Moncton. Net benefit was also lower for those who had two or more psychiatric hospitalizations in 1 year over the 5 years before baseline, by about $10,000 regardless of λ; the cost for these individuals was about that much more than for the others, on average, per year over the 2-year follow-up period of the study. Similarly, a longer previous period of homelessness over the person's lifetime was associated with greater costs. The coefficient indicates an increase of about $120 per additional month of homelessness. This amount also hardly varied according to λ. Neither age, sex, nor alcohol and drug abuse or dependence were associated with net benefit, regardless of λ, after adjustment for site and the other factors.
Table 4 shows the results of adding interactions between group assignment and the variables selected by using the procedure described above. The results suggest that Housing First may have been more cost-effective in Toronto, the only site where the intervention actually reduced overall costs. The results also suggest that the intervention may have been more cost-effective for people ages 30–49 than for younger participants. None of the other interaction terms meaningfully altered cost-effectiveness at any value of λ.
TABLE 4. Net benefit regression results for the Housing First intervention for various values assigned to an additional day of stable housing, with interaction termsa
 λb=$0λb=$20λb=$40
VariableM95% CIM95% CIM95% CI
Housing First–24,882–42,142, –7,621–21,994–39,457, –4,530–19,106–36,807, –1,404
Montrealc–35,023–49,217, –20,828–36,087–50,444, –21,731–37,152–51,700, –22,604
Torontoc–38,745–53,112, –24,378–39,445–53,977, –24,913–40,145–54,870, –25,419
Winnipegc–15,066–28,386, –1,745–15,894–29,352, –2,435–16,721–30,344, –3,098
Vancouverc–20,034–34,090, –5,978–21,061–35,282, –6,840–22,088–36,504, –7,672
Ages 30–49d–9,010–19,241, 1,221–8,911–19,254, 1,433–8,811–19,287, 1,664
Ages ≥50d3,785–9,676, 17,2464,098–9,511, 17,7074,411–9,372, 18,194
Female–3,278–9,851, 3,295–2,970–9,609, 3,668–2,663–9,380, 4,054
Alcohol or drug abuse or dependencee–2,913–10,123, 4,296–2,968–10,262, 4,326–3,023–10,415, 4,370
MCAS scoref3,313–1,354, 7,9803,657–1,066, 8,3794,000–786, 8,786
Hospitalization historyg–13,840–23,075, –4,606–13,615–22,954, –4,276–13,390–22,851, –3,929
Arrest historyh–4,983–11,111, 1,145–5,396–11,592, 800–5,810–12,086, 467
Longest period homelessi–108–171, –45–110–174, –46–112–176, –47
Interaction terms      
 Montreal × Housing First12,542–7,152, 32,23612,084–7,823, 31,99111,626–8,529, 31,781
 Toronto × Housing First19,223–31, 38,47719,343–114, 38,80019,463–233, 39,159
 Winnipeg × Housing First5,740–12,217, 23,6984,744–13,409, 22,8973,747–14,636, 22,130
 Vancouver × Housing First400–18,649, 19,449744–18,519, 20,0081,089–18,427, 20,605
 Ages 30–49 × Housing First13,160–1,136, 27,45713,480–976, 27,93513,800–843, 28,442
 Ages ≥50 × Housing First3,218–15,613, 22,0503,413–15,632, 22,4583,607–15,687, 22,901
 Hospitalized × Housing First5,855–6,938, 18,6476,063–6,875, 19,0026,272–6,837, 19,381
Constant–32,735–64,498, –971–31,942–64,073, 189–31,150–63,710, 1,410
 λb=$60λb=$80λb=$100
 M95% CIM95% CIM95% CI
Housing First intervention–16,217–34,189, 1,754–13,329–31,603, 4,944–10,441–29,047, 8,164
Montrealc–38,217–52,983, –23,451–39,281–54,292, –24,271–40,346–55,626, –25,066
Torontoc–40,845–55,791, –25,899–41,545–56,738, –26,352–42,245–57,711, –26,780
Winnipegc–17,549–31,362, –3,736–18,377–32,403, –4,350–19,204–33,468, –4,941
Vancouverc–23,115–37,756, –8,475–24,142–39,036, –9,249–25,170–40,343, –9,997
Ages 30–49d–8,712–19,339, 1,914–8,613–19,409, 2,183–8,513–19,497, 2,470
Ages ≥50d4,724–9,257, 18,7055,037–9,165, 19,2405,350–9,096, 19,796
Female–2,355–9,163, 4,452–2,048–8,958, 4,863–1,740–8,764, 5,284
Alcohol or drug abuse or dependencee–3,077–10,581, 4,427–3,132–10,759, 4,495–3,186–10,948, 4,575
MCAS scoref4,344–514, 9,2024,688–249, 9,6245,0318, 10,054
Hospitalization historyg–13,165–22,765, –3,566–12,940–22,694, –3,186–12,715–22,639, –2,791
Arrest historyh–6,223–12,591, 145–6,637–13,107, –166–7,050–13,634, –467
Longest period homelessi–113–179, –48–115–181, –49–117–184, –50
Interaction terms      
 Montreal × Housing First11,168–9,271, 31,60710,710–10,045, 31,46510,252–10,851, 31,355
 Toronto × Housing First19,583–386, 39,55219,703–574, 39,98019,823–793, 40,439
 Winnipeg × Housing First2,750–15,897, 21,3971,754–17,189, 20,696757–18,511, 20,025
 Vancouver × Housing First1,433–18,372, 21,2391,778–18,351, 21,9072,123–18,364, 22,609
 Ages 30–49 × Housing First14,119–737, 28,97614,439–657, 29,53514,759–602, 30,120
 Ages ≥50 × Housing First3,801–15,776, 23,3783,995–15,898, 23,8884,190–16,050, 24,430
 Hospitalized × Housing First6,481–6,821, 19,7836,690–6,828, 20,2086,899–6,856, 20,653
Constant–30,358–63,405, 2,690–29,566–63,157, 4,026–28,773–62,962, 5,416
a
Usable data for 917 of the 950 participants were available for analysis. Models estimated with net monetary benefit not adjusted for baseline differences in costs. Dependent variable is (di ∙ λ) – ci, where λ is the threshold ratio (in Canadian dollars per additional day of stable housing), di is participant i’s annualized number of days of stable housing, and ci is the corresponding total cost.
b
Decision maker’s willingness to pay for an additional day of stable housing.
c
Reference, Moncton site.
d
Reference, age <30.
e
Reference, no alcohol or drug abuse or dependence.
f
Multnomah Community Ability Scale. Coefficients indicate partial association with a 10-point increase in MCAS score.
g
Two or more hospitalizations for mental illness during a 1-year period during the 5 years before baseline.
h
One or more arrests or incarcerations in the 6 months before baseline.
i
During lifetime, in months.
Sensitivity analyses (shown in a table in the online supplement) indicated that our results were robust to changes in the discount rate and only somewhat sensitive to the adjustment for baseline differences, or a combination of both. Changes in the discount rate had a minimal effect. Adjusting for baseline differences decreased the ICER from $41.73 to $33.86. The largest change was obtained by adjusting for baseline differences, without altering the discount rate: the ICER became $33.85 (95% CI=cost-saving, $68.42).

Discussion

Across five Canadian sites, 69% of the cost of scattered-site Housing First with ACT for persons with severe mental illness and high needs ($20,367 per person per year) was offset by cost reductions. Net program cost was $6,311 per person per year. An additional day of stable housing cost about $41.73. Cost-effectiveness seemed to be about the same regardless of participant characteristics, although it may have been higher for participants ages 30–49 than for those who were younger.
In previous reports of the At Home/Chez Soi study, the intervention cost was reported as Can$22,257 per participant annually (in 2011 dollars), and the mean net cost offset was 96% of the cost of the intervention (7, 10). The numerical estimates presented herein differ from the earlier ones for several reasons. Most important, we did not adjust here for baseline differences in costs (27), whereas the earlier reports used a relatively simple difference-in-differences method, applied to mean costs per person per site. Second, we allocated the cost of the intervention to individual study participants. Third, we refined several unit cost calculations, compared with the earlier report.
The cost-effectiveness analysis of Housing First with intensive case management from At Home/Chez Soi reported that the intervention cost $14,496 per participant per year, or about 71% of the cost of Housing First with ACT (9). Despite the higher cost of Housing First with ACT, the cost per additional day of stable housing in this study was $41.73, instead of $56.08 for Housing First with intensive case management (26% less). In part, this is probably a result of the intervention’s—Housing First with intensive case management—being no more effective: the mean annual increase in days of stable housing was 140.34 for Housing First with intensive case management, compared with 151.30 days for Housing First with ACT. The reason for the greater cost-effectiveness of Housing First with ACT was mainly the large cost offset of $14,056 per person per year, compared with $6,629 for Housing First with intensive case management. Baseline costs among high-need participants were about 50% higher, compared with costs for those with moderate needs: $74,910 versus $50,708 (9). This provided greater opportunity to achieve large cost offsets. Indeed, in each of the four cities where both Housing First with ACT and Housing First with intensive case management were tested, the cost offset was greater with the former than with the latter. Further research is needed to determine the ideal mix between the two, considering, on one hand, the higher need of high-need participants but, on the other, the possibility that offering Housing First with intensive case management to moderate-need participants may prevent the conditions of some from deteriorating to the point of their needing more intensive services.
The magnitude of the cost offsets exceeded that of the cost of the intervention in one city—Toronto. This may well have been the result of chance, given that the 95% CI for the difference in costs included 0. To the extent that cost offsets were actually greater in Toronto, this may be due to the fact that the usual costs of shelters and ambulatory visits were all especially high in that city (15); the intervention substituted directly for these costs. The costs of contacts with the police were also unusually high in Toronto, but as shown in Table 2, we found no evidence that Housing First resulted in a significant reduction in police costs.
The results of this study may appear disappointing in that the intervention did not generate cost offsets greater than its own cost, except in Toronto —in other words, it did not “pay for itself.” This is consistent with the results of a recent literature review, which found that randomized trials, which are not subject to bias caused by regression to the mean, are much less likely to report net cost savings from Housing First, compared with studies following a before-and-after design (3).
The fact that Housing First with ACT did not prove both more effective and less costly does not mean that it should not be implemented. Most health and social interventions do not pay for themselves. Rather, they yield benefits judged sufficient to merit their cost. The cost of the intervention itself, which was about $56 per participant per day in the program, is well within the range of the costs of many currently funded forms of emergency shelter and supportive housing with on-site supports (15). Moreover, these forms of shelter do not provide the kind of individualized and intensive support that ACT does.
In this trial, careful attention was paid to implementation fidelity, with the New York City Pathways model serving as reference (28). Fidelity was rated as fair to excellent across sites (14). Other work has reported an association between higher fidelity and improvements in housing stability, quality of life, and community functioning (29), as well as other positive outcomes (30, 31). Not all Housing First implementations are as careful to follow the Pathways model as were those of the At Home/Chez Soi trial; for instance, caseloads may be increased or rent supplements reduced. Although such changes may reduce the cost of the intervention, the magnitude of the cost offsets observed here may not remain the same. It is also possible that the intervention could be rendered most cost-effective by either adjusting the clinical supports or the amount of the rent supplement, or both (32). Further research is needed to address this issue.
Strengths of this study included a carefully defined and implemented intervention, a large and well-defined sample, multiple trial sites, and high retention rates, with low differential attrition. Service use was measured in a more comprehensive way than is typical in cost-effectiveness studies. Unit costs were carefully estimated.
Limitations included a reliance on participant self-reports. Although these are subject to recall biases, the most costly components of costs were gathered at 3-month intervals, increasing their validity (33). The validity of self-reports in the At Home/Chez Soi study has also been corroborated directly (34, 35). The At Home/Chez Soi trial considered any form of housing where a participant could remain 6 months or more as stable housing. This allowed certain forms of transitional housing that participants especially in the treatment-as-usual group accessed to be counted as stable housing. Had a stricter criterion for stable housing been applied, cost-effectiveness would have been even greater. The cost of medications was not included, because of the difficulty of obtaining this information by questionnaire and restrictions on sharing of participant-level administrative data across provinces. Given that ACT teams typically seek to increase adherence to medications, having included medications in the analysis would likely have increased the cost per day of stable housing. Still, even a 15% increase in the cost of the intervention—about $3,000 per participant per year—would not change the results materially.
The follow-up period was 2 years, and we do not know how cost-effectiveness may change over a longer period. The use of days of stable housing as an outcome measure did not allow comparison of cost-effectiveness with that of other health care interventions; however, as argued elsewhere (9), Housing First is a social care as well as a health care intervention, and thus evaluation of its effectiveness by using quality-adjusted life years would be inappropriate. The study was not designed to test which of the rent supplement or the clinical supports most contributed to cost-effectiveness, as has been done previously (32). Further research is needed to address this issue. Furthermore, our study did not try to capture costs with a more subjective value, such as the empathic distress that many individuals experience when they see people living on the street. Had it done so, the cost-effectiveness of Housing First would likely have increased. Finally, we did not take into account the administrative costs of transfer payments (17); however, because most participants in both groups received social assistance payments, doing so would have had little impact.

Conclusions

In this multisite trial of Housing First, reductions in the costs of several services offset about two-thirds of the cost of a Housing First intervention. The cost of the intervention per person and the net cost were modest in relation to current expenditures on individuals who are homeless. Furthermore, we found no evidence that cost-effectiveness varied according to participant characteristics, with the possible exception of age. Comparing our results with those from a similar analysis of homeless individuals with moderate needs who were served by an intensive case management team (9), cost offsets were greater for high-need participants, and the net cost per additional day stably housed was similar. The optimal mix between the two interventions remains to be determined and needs to consider both the higher need of high-need individuals and the risk that without help the conditions of moderate-need individuals may deteriorate and these individuals may themselves become high need.

Acknowledgments

The authors thank Jayne Barker, Ph.D. (2008–2011), Cameron Keller (2011–2012), and Catharine Hume (2012–2013), who served as the Mental Health Commission of Canada At Home/Chez Soi National project leads; the National Research Team; the five site research teams; the site coordinators; the numerous service and housing providers; and the persons with lived experience who contributed to this project and the research.

Footnotes

This research was made possible through a financial contribution from Health Canada to the Mental Health Commission of Canada. Trial registration: isrctn.org identifier, ISRCTN42520374.
The views expressed herein solely represent those of the authors.

Supplementary Material

File (appi.ps.202000029.ds001.pdf)

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Information & Authors

Information

Published In

Go to Psychiatric Services
Go to Psychiatric Services
Psychiatric Services
Pages: 1020 - 1030
PubMed: 32838679

History

Received: 14 January 2020
Revision received: 3 March 2020
Accepted: 19 March 2020
Published online: 25 August 2020
Published in print: October 01, 2020

Keywords

  1. Homeless mentally ill
  2. Cost-effectiveness analysis

Authors

Details

Eric A. Latimer, Ph.D. [email protected]
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Daniel Rabouin, M.Sc.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Zhirong Cao, M.Sc.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Angela Ly, M.H.A
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Guido Powell, M.Sc.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Tim Aubry, Ph.D.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Jino Distasio, Ph.D.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Stephen W. Hwang, M.D., M.P.H.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Julian M. Somers, Ph.D.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Ahmed M. Bayoumi, M.D., M.Sc.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Craig Mitton, Ph.D.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Erica E. M. Moodie, Ph.D.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
Paula N. Goering, R.N., Ph.D.
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).
For the At Home/Chez Soi Investigators
Department of Psychiatry, McGill University, Montreal (Latimer); Douglas Research Centre, Montreal (Latimer, Rabouin, Cao); Montreal West Island Integrated University Health and Social Services Centre, Montreal (Ly); Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal (Powell, Moodie); Department of Psychology, University of Ottawa, Ottawa (Aubry); Department of Geography, University of Winnipeg, Winnipeg, Manitoba (Distasio); Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto (Hwang); Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto (Hwang, Bayoumi); Department of Psychiatry, Simon Fraser University, Burnaby, British Columbia (Somers); Dalla Lana School of Public Health, University of Toronto, Toronto (Bayoumi); School of Population and Public Health, University of British Columbia, Vancouver (Mitton); Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto (Goering, who died in May 2016).

Notes

Send correspondence to Dr. Latimer ([email protected]).
A preliminary version of this report was presented at the meeting of the Canadian Association for Health Services and Policy Research, Toronto, May 24–26, 2017.

Competing Interests

The authors report no financial relationships with commercial interests.

Funding Information

Health Canada via Mental Health Commission of Canada:

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