Factors Contributing to Eviction from HUD-VASH Dennis Culhane, PhD Director of Research, National Center on Homelessness Among Veterans Dana and Andrew Stone Professor of Social Policy, School of Social Policy and Practice, University of Pennsylvania

Exits from Permanent Supportive Housing High rate of housing retention in PSH, but exits may be associated with a number of factors Nonpayment of rent1 Use of emergency services2 Substance abuse3–5 About 1 in 10 Veterans leave HUD-VASH due to eviction, which is associated with negative consequences Ongoing residential instability6 Relocation to neighborhoods with higher poverty and crime7 Relocation to substandard, lower-quality housing, which may directly impact health8–10 Material hardship11 Homelessness4,11,12

Study Objectives To identify correlates of eviction—both tenant characteristics and precipitating events—that may signal imminent eviction To assess potential utility of a real-time, data-driven system of notification for services providers

Methods Potential Correlates Sample & Analysis Veterans’ characteristics Tenure in HUD-VASH housing Sex Age Military experience Service-connected disability Medical, mental, and behavioral health diagnoses Precipitating events Inpatient admissions Emergency Department (ED) visits Outpatient care Sample: 20,146 Veterans who exited HUD-VASH (10/2008–2/2016) Evicted Accomplished goals Analysis: logistic regressions—controlling for demographics, diagnoses—with 3 patterns of precipitating events/services use

Precipitating Events Services Use Model Eviction Used inpatient, ED, outpatient care Services Use Model Eviction Increased Services Use Model Eviction Increased use of inpatient, ED, outpatient care 1 inpatient admission or 2 ED visits Acute Care Use Model Eviction Inpatient and ED care categorized as medical, mental health, substance use; outpatient care categorized as primary care, medical, mental health, substance use, HUD-VASH case management; acute care includes any type of inpatient or ED service

Veterans’ Characteristics Evicted (n=4,684) Accomplished Goals (n=15,462) p Length of residence (months) 19.2 27.2 <.001 Female (%) 9.1 14.5 Age (%) < 35 11.3 10.6 35–54 43.4 39.2 55+ 45.4 50.3 Combat exposure (%) 4.7 5.5 .011 Service-connected disability (%) 41.4 46.8 Diagnoses (%) Chronic medical condition 36.2 31.5 Depression 43.2 36.1 PTSD 18.0 15.6 Psychosis 9.5 4.8 Suicide/self-harm 10.7 1.5 Alcohol use disorder 32.5 11.2 Drug use disorder 38.6 12.2

Services Use 90 Days Prior to Exit Inpatient Admissions Emergency Department Visits Acute Care Use

Veterans’ Characteristics  Eviction Decreased Odds of Eviction Increased Odds of Eviction

Services Use Model Outpatient Emergency Inpatient

Increased Services Use Model Outpatient Emergency Inpatient

Acute Care Use Model

Precipitating Events  Eviction Any inpatien t admissio n or ED visit, particula rly related to substanc e use Acute care Outpatie nt care related to substanc e use (Best predictor s: increases in use over time and use 30 days prior to exit) Primary care and medical outpatie nt care HUD- VASH case manage ment Increased odds of eviction Decreased odds of eviction

Potential Utility of Predictive Model Veterans’ characteristics and precipitating events (patterns of acute health services use) are related to increased likelihood of eviction In each model, the use of specific types of acute care within 30 days of exit are the best predictors Allows little time to intervene but may serve as an efficient, and hopefully effective, warning flag Other variables (e.g., nonpayment of rent) may also predict eviction, but are not readily available

For More Information Montgomery, A. E., Cusack, M. C., Szymkowiak, D., Fargo, J. D., & O’Toole, T. P. (2017). Factors contributing to eviction from permanent supportive housing: Lessons from HUD-VASH. Evaluation and Program Planning, 61, 55–63. doi:10.1016/j.evalprogplan.2016.11.014 http://www.sciencedirect.com/science/article/pii/S0149718916301379

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