These programs provide permanent supportive housing to chronically homeless single adults. Most of the studies reviewed here used the Housing First model which provides independent apartments with no specific requirements for abstinence or treatment. Programs typically provide intensive case management and services. Housing is in independent apartments—participants hold the lease but receive subsidies to pay rent. Supported housing is associated with significant reductions in homelessness which we are unable to monetize at this time. To test the sensitivity of our benefit-cost results to this known limitation of our model, we examined a recent comprehensive benefit-cost study of housing vouchers (Carlson et al., 2011). Our benefit-cost results would not change significantly if we had included the benefits of providing housing estimated by this study. Carlson, D., Haveman, R., Kaplan, T., & Wolfe, B. (2011). The benefits and costs of the Section 8 housing subsidy program: A framework and estimates of first‐year effects. Journal of Policy Analysis and Management, 30 (2), 233-255.

 

^{^}WSIPP’s benefit-cost model does not monetize this outcome.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured	Treatment age	Primary or secondary participant	No. of effect sizes	Treatment N	Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis						Unadjusted effect size (random effects model)
					First time ES is estimated			Second time ES is estimated
					ES	SE	Age	ES	SE	Age	ES	p-value
Crime Any criminal conviction according to court records, sometimes measured through charges, arrests, incarceration, or self-report.	40	Primary	8	3833	-0.083	0.047	40	0.000	0.000	41	-0.083	0.077
Alcohol use disorder Clinical diagnosis of alcohol use disorder or symptoms measured on a validated scale.	40	Primary	2	478	-0.051	0.144	40	0.000	0.000	41	-0.051	0.723
Employment Any employment, including part-time work.	40	Primary	3	514	0.179	0.111	40	0.000	0.000	41	0.192	0.183
Illicit drug use disorder Clinical diagnosis of illicit drug use disorder or symptoms measured on a validated scale. When possible, we exclude cannabis/marijuana use disorder from this outcome.	40	Primary	1	332	0.062	0.105	40	0.000	0.000	41	0.062	0.553
Hospitalization Hospital admission, for any reason.	40	Primary	7	2490	-0.129	0.054	40	0.000	0.000	41	-0.129	0.016
Hospitalization (psychiatric) Admission to a psychiatric ward or hospital.	40	Primary	4	2727	-0.058	0.028	40	0.000	0.000	41	-0.058	0.036
Homelessness^ A lack of stable housing, often measured through self-report of conditions like living on streets or in shelters in a given time period.	40	Primary	10	4467	-0.505	0.023	40	n/a	n/a	n/a	-0.505	0.001
Emergency department visits Whether someone visited the emergency department, or the number of times they visited the emergency department.	40	Primary	5	570	-0.164	0.064	40	0.000	0.000	41	-0.164	0.011
Primary care visits^ Visit to a primary care physician for any reason.	40	Primary	3	733	0.157	0.052	40	n/a	n/a	n/a	0.157	0.003

Basu, A., Kee, R., Sadowski, L.S., & Buchanan, D. (2012). Comparative cost analysis of housing and case management program for chronically ill homeless adults compared to usual care. Health Services Research, 47, 523-543.

Cheng, A.L., Lin, H., Kasprow, W., & Rosenheck, R.A. (2007). Impact of supported housing on clinical outcomes: Analysis of a randomized trial using multiple imputation technique. The Journal of Nervous and Mental Disease, 195(1), 83-88.

Culhane, D.P., Metraux, S., & Hadley, T. (2002). Public service reductions associated with placement of homeless persons with severe mental illness in supportive housing. Housing Policy Debate, 13(1), 107-163.

Gilmer, T.P., Stefancic, A., Ettner, S.L., Manning, W.G., & Tsemberis, S. (2010). Effect of full-service partnerships on homelessness, use and costs of mental health services, and quality of life among adults with serious mental illness. Archives of General Psychiatry, 67(6), 645-52.

Gulcur, L., Stefancic, A., Shinn, M., Tsemberis, S., & Fischer, S. (2003). Housing, hospitalization, and cost outcomes for homeless individuals with psychiatric disabilities participating in continuum of care and housing first programmes. Journal of Community and Applied Social Psychology, 13(2), 171-186.

Johnson, G., Kuehnle, D., Parkinson, S., Sesa, S., & Tseng, Y. (2014). Resolving long-term homelessnes: A randomized controled trial examining the 36 month costs, benefits, and social outcomes from the journey to Social Inclusion Pilot Program. Sacred Heart Mission, St. Kilda.

Johnson, G., Kuehnle, D., Parkinson, S., Sesa, S., & Tseng, Y. (2012). Resolving long-term homelessnes: A randomized controled trial examining the 24 month costs, benefits, and social outcomes from the ourney to Social Inclusion Pilot Program. Sacred Heart Mission, St. Kilda.

Larimer, M.E., Malone, D.K., Garner, M.D., Atkins, D.C., Burlingham, B., Lonczak, H.S., et al. (2009). Health care and public service use and costs before and after provision of housing for chronically homeless persons with severe alcohol problems. JAMA, 301(13), 1349-1357.

Lipton, F.R., Nutt, S., & Sabatini, A. (1988). Housing the homeless mentally ill: A longitudinal study of a treatment approach. Hospital & Community Psychiatry, 39(1), 40-45.

Mares, A., Rosenheck, R.A. (2007) HUD/HHS/VA Collaborative to Help End Chronic Homelessness National Performance Outcomes Assessment Preliminary Client Outcomes Report. West Haven, CT: VA Northeast Program Evaluation Center.

Rosenheck, R., Kasprow, W., Frisman, L., & Liu-Mares, W. (2003). Cost-effectiveness of supported housing for homeless persons with mental illness. Archives of General Psychiatry, 60(9), 940-951.

Sadowski, L.S., Kee, R.A., VanderWeele, T.J., & Buchanan, D. (2009). Effect of a housing and case management program on emergency department visits and hospitalizations among chronically ill homeless adults: A randomized trial. JAMA, 301(17), 1771-1778.

Shern, D.L., Felton, C.J., Hough, R.L., Lehman, A.F., Goldfinger, S., Valencia, E., ... (1997). Housing outcomes for homeless adults with mental illness: Results from the second-round McKinney program. Psychiatric Services, 48(2), 239-241.

Srebnik, D., Connor, T., & Sylla, L. (2013). A pilot study of the impact of housing first-supported housing for intensive users of medical hospitalization and sobering services. American Journal of Public Health, 1039(2), 316-21.

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