Abstract

Background: There is a paucity of reliable, household-level data on evictions. We have no data on how many Veterans are evicted each year, whether they regain housing or not after eviction, or the costs to VA of rehousing evicted Veterans and treating eviction-related health conditions. If we knew these costs to be substantial, we could better budget for programs, such as the Supportive Services for Veteran Families (SSVF), that are designed to reduce housing insecurity. Significance: We will acquire the names and addresses on all eviction filings starting in 2013 from Minnesota, Indiana, Cook County (Chicago), IL and the Puget Sound (Seattle) region of Washington State. We will match these filings by name and address to VA clinical and housing databases. This offers three major opportunities for VA. First, it allows VA researchers to estimate the effects of eviction on health and housing outcomes and VA costs. Knowing the costs of evictions informs the level of effort the VA should apply to mitigate those costs. Second, it provides an opportunity to intervene proactively to prevent homelessness because the eviction data can be extracted monthly. Third, because eviction data covers all Veterans and not just those receiving VA care, it provides an opportunity for VA to proactively reach all enrolled Veterans, including non-VA users who might not be aware of the housing, health, and social assistance available to them at VA. Innovation and Impact: This is the first VA study to: carefully match evicted persons to non-evicted persons at the time of eviction to minimize risks of reverse causation and confounding; estimate the probability of homelessness following an eviction; comprehensively estimate the effect of evictions on health and healthcare costs; pilot-test a system to identify Veterans before they become housing insecure that does not rely on a Veteran having a healthcare visit with a housing screen; and use newly released data on the socioeconomic status of Veterans from the USVETS database. If successful, we will be able to proactively contact Veterans and refer them to VA housing services before they become homeless. We will also better understand the costs of evictions to Veterans and VHA. Specific Aims: 1. Aim 1: Estimate the effect of evictions on Veterans’ health, housing outcomes and costs. Hypotheses: a) Veterans who were evicted were more likely to experience subsequent homelessness, have increased need for physical and mental health services, and to generate more costs to the VA than Veterans who were not evicted.; b) Black and Hispanic Veterans were more likely to face eviction than were white Veterans. 2. Aim 2: Conduct a prospective survey of evicted and non-evicted Veterans to estimate the association between evictions and patient reported outcomes: Hypothesis: Veterans who were evicted will have less favorable patient reported outcomes than Veterans who were not evicted. 3. Aim 3: Design and pilot test an intervention to proactively reach out to Puget Sound Veterans with court fillings for eviction. Primary outcomes: a) requests for information on housing assistance from Veterans who received outreach, and b) acceptability of the pilot intervention by Veteran users and VA staff. Methodology: Aim 1 is retrospective statistical analyses of housing and health databases. Aim 2 conducts a survey of evicted and non-evicted Veterans. Aim 3 conducts qualitive interviews with newly evicted Veterans, holds a human centered design workshop to create the intervention, and pilot-tests the intervention. Next Steps/Implementation: We ultimately hope to widely implement the intervention(s) designed and pilot- tested in Aim 3 in order to better reach Veterans facing eviction and help prevent Veteran homelessness.

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DRA: Health Systems Science

DRE: TRL - Applied/Translational, Data Science

Keywords: Homeless, Knowledge Integration, Socioeconomic Factors

MeSH Terms: None at this time.