Homeless Management Research Articles

Center for Advanced Studies in Child Welfare, University of Minnesota

Objective and ApproachPrior research has found that experiences of homelessness are associated with an increased likelihood of child protection involvement, and vice-versa. However, it is not clear how involvement with the child welfare system may impact family housing stability during and after their involvement. The objective of this study was to more deeply understand the housing stability of families involved with child welfare over time. To examine this issue, we linked administrative data from Minnesota’s Homelessness Management Information System with social services data from the Department of Human Services (e.g., receipt of food support, childcare or housing assistance, child welfare), for families involved with child welfare in Minnesota between 2019 and 2021. ResultsApproximately a quarter of child welfare-involved families experienced homelessness during their involvement with the child welfare system. Rates of homelessness were similarly high in the two years prior to and following child welfare involvement. Although a large proportion of families experienced homelessness before and during their child welfare involvement, we saw no increase in the proportion of families receiving housing support after their involvement in the system. Conclusions and ImplicationsOur findings indicate that involvement with the child welfare system and the resources provided through this involvement do not have a significant impact on family’s experiences of homelessness. This suggests the need for closer collaboration between the child welfare system and housing services to identify more effective solutions for housing instability among families within the child welfare system.

Linkja: Open Source Privacy-Preserving Record Linkage Tool

ObjectiveTo introduce Linkja, an open-source, certified, Privacy-Preserving Record Linkage (PPRL) tool with the primary objective of facilitating secure and efficient record linkage across diverse datasets, while preserving individual privacy, providing a comprehensive and privacy-centric approach to program assessments. ApproachLinkja has been used to evaluate Chicago’s Flexible Housing Pool program by securely linking various datasets, including Homeless Management Information Systems (HMIS), Electronic Health Records, Jail records, Medical Examiner reports, and Public Health data. Data contributors used separate honest brokers for record linkage, and generation of salt and cryptography keys. ResultsLinkja enabled this multi-sector linkage by facilitating legal and data sharing agreements, avoided licensing fees and procurement processes for all parties, and provided a de-identified for analysis. The insights gleaned from the analysis motivated the FHP program to plan a follow-up evaluation that will add emergency serviced records from a separate City of Chicago department. The successful linkage provided a nuanced understanding of the association between stable housing and reduced healthcare utilization. ConclusionsLinkja's cryptographic certification ensures the highest standards of security during data linkage, safeguarding sensitive information. The matching rules, validated on hard-to-match populations, prove essential in maintaining accuracy and reliability in the linkage process. ImplicationsThe open-source nature of Linkja promotes transparency and collaboration in the development and enhancement of privacy-preserving record linkage techniques. This tool has broad implications for sectors dealing with sensitive data, fostering responsible data-sharing practices, and enabling secure collaborative research initiatives without compromising individual privacy.

The Implementation of Coordinated Access to End Homelessness in Ontario, Canada

To receive federal homelessness funding, cities in Canada must adhere to federal policy directives associated with the government of Canada’s Reaching Home program. These directives include the implementation of a homelessness management information system (HMIS) and a Coordinated Access process. In this article, we draw on 90 in-depth interviews and extensive policy and institutional analysis to assess the implementation of Coordinated Access in one Ontario city. Our findings suggest that none of the four pillars of Coordinated Access (access, assessment, prioritization, matching, and referral) work as intended. Structural and systemic challenges (e.g., related to housing stock, staff turnover, inaccessibility of shelters, criminalizing municipal bylaws, and the reliability of the assessment tool) undermine the efficacy of the process as a means of improving transparency, service coordination, and housing outcomes. Despite being an early adopter of the Coordinated Access process, this Ontario municipality continues to struggle with a growing housing affordability crisis and an unhoused population.

Short Interpregnancy Intervals Among Women Experiencing Homelessness in Colorado

Short interpregnancy intervals (SIPIs) are associated with increased risk of adverse maternal and neonatal outcomes. Disparities exist across socioeconomic status, but there is little information on SIPIs among women experiencing homelessness. To investigate (1) differences in rates and characteristics of SIPIs between women experiencing homelessness and domiciled women, (2) whether the association of homelessness with SIPIs differs across races and ethnicities, and (3) whether the association between SIPIs of less than 6 months (very short interpregnancy interval [VSIPIs]) and maternal and neonatal outcomes differs between participant groups. This cohort study used a Colorado statewide database linking the Colorado All Payer Claims Database, Homeless Management Information System, death records, and infant birth records. Participants included all women who gave birth between January 1, 2016, and December 31, 2021. Data were analyzed from September 1, 2022, to May 10, 2023. Homelessness and race and ethnicity. The primary outcome consisted of SIPI, a binary variable indicating whether the interval between delivery and conception of the subsequent pregnancy was shorter than 18 months. The association of VSIPI with maternal and neonatal outcomes was also tested. A total of 77 494 women (mean [SD] age, 30.7 [5.3] years) were included in the analyses, of whom 636 (0.8%) were women experiencing homelessness. The mean (SD) age was 29.5 (5.4) years for women experiencing homelessness and 30.7 (5.3) years for domiciled women. In terms of race and ethnicity, 39.3% were Hispanic, 7.3% were non-Hispanic Black, and 48.4% were non-Hispanic White. Associations between homelessness and higher odds of SIPI (adjusted odds ratio [AOR], 1.23 [95% CI, 1.04-1.46]) were found. Smaller associations between homelessness and SIPI were found among non-Hispanic Black (AOR, 0.59 [95% CI, 0.37-0.96]) and non-Hispanic White (AOR, 0.57 [95% CI, 0.39-0.84]) women compared with Hispanic women. A greater association of VSIPI with emergency department visits and low birth weight was found among women experiencing homelessness compared with domiciled women, although no significant differences were detected. In this cohort study of women who gave birth from 2016 to 2021, an association between homelessness and higher odds of SIPIs was found. These findings highlight the importance of conception management among women experiencing homelessness. Racial and ethnic disparities should be considered when designing interventions.

Service Use Differences Among Those Experiencing Homelessness: A Posthumous Analysis

Services play a crucial role in responding to homelessness, facilitating stable housing, and improving health outcomes. Yet people in need do not always access services and little is known about such individuals and groups. Using mortality data from the New Mexico Office of the Medical Investigator (OMI) that was cross-referenced with services records from Homelessness Management Information Systems (HMIS), this study identified and compared people affected by homelessness ( N = 1196) who died between 2014 and 2019 based on whether they had engaged with homelessness services ( n = 841) or who were unhoused without a record services engagement ( n = 355). Groups were compared by age, race, gender, region of the state, and leading causes of death. Approximately 30 percent of individuals found to be homeless were not engaged in homelessness services. There were statistically greater numbers of Native Americans among those who were unhoused without a record of homelessness services. There were also inequities across regions of the state. This supports the need for increased outreach in rural areas and removing barriers to service engagement. The leading causes of death were drug overdose, alcohol, and heart disease, thus reinforcing the need for harm reduction education and practices both within and outside of services.

Vaccine Effectiveness Against SARS-CoV-2 Related Hospitalizations in People who had Experienced Homelessness or Incarceration – Findings from the Minnesota EHR Consortium

COVID-19 disproportionately affects people experiencing homelessness or incarceration. While homelessness or incarceration alone may not impact vaccine effectiveness, medical comorbidities along with social conditions associated with homelessness or incarceration may impact estimated vaccine effectiveness. COVID-19 vaccines reduce rates of hospitalization and death; vaccine effectiveness (VE) against severe outcomes in people experiencing homelessness or incarceration is unknown. We conducted a retrospective, observational cohort study evaluating COVID-19 vaccine VE against SARS-CoV-2 related hospitalization (positive SARS-CoV-2 molecular test same week or within 3 weeks prior to hospital admission) among patients who had experienced homelessness or incarceration. We utilized data from 8 health systems in the Minnesota Electronic Health Record Consortium linked to data from Minnesota’s immunization information system, Homeless Management Information System, and Department of Corrections. We included patients 18 years and older with a history of experiencing homelessness or incarceration. VE and 95% Confidence Intervals (CI) against SARS-CoV-2 hospitalization were estimated for primary series and one booster dose from Cox proportional hazard models as 100*(1-Hazard Ratio) during August 26, 2021, through October 8, 2022 adjusting for patient age, sex, comorbid medical conditions, and race/ethnicity. We included 80,051 individuals who had experienced homelessness or incarceration. Adjusted VE was 52% (95% CI, 41–60%) among those 22 weeks or more since their primary series, 66% (95% CI, 53–75%) among those less than 22 weeks since their primary series, and 69% (95% CI: 60–76%) among those with one booster. VE estimates were consistently lower during the Omicron predominance period compared with the combined Omicron and Delta periods. Despite higher exposure risk, COVID-19 vaccines provided good effectiveness against SARS-CoV-2 related hospitalizations in persons who have experienced homelessness or incarceration.

Shelter Abolition and Housing First: Rethinking Dominant Discourses on Homeless Management

Shelter Abolition and Housing First: Rethinking Dominant Discourses on Homeless Management

Health & Housing in Delaware:: Matching Medicaid Claims and Encounters and the Community Management Information System Databases.

This study draws upon data from two databases: claims and encounters that were reimbursed by the state's Division of Medicaid and Medical Assistance (DMMA) and the Homeless Management Information System (HMIS) database that collects homeless services data on individuals experiencing homelessness. Records from both sets are matched to identify 838 adults who both experienced homelessness and were Medicaid eligible in 2019, and to select, through propensity score matching, an equal set of control observations who were similarly Medicaid-eligible but had no record of homelessness. Outcomes are compared based upon scores on the Charlson Elixhauser Comorbidity index, incidence of substance use disorder, inpatient, emergency department, and outpatient visits, and inpatient, emergency department, and outpatient costs. Using ordinary least squares regression models, we estimate homelessness (as indicated by use of homeless services) to be associated with excess costs of $4,611 (non-chronic homelessness) to $5,218 (chronic homelessness) per person over the course of 2019, compared to similar Medicaid enrollees who were housed.

The size and Census coverage of the U.S. homeless population

Fundamental questions about the size and characteristics of the homeless population are unresolved because it is unclear whether existing data are sufficiently complete and reliable. We examine these questions and the coverage of new microdata sources that are designed to be nationally representative. We compare two restricted data sources largely unused to study homelessness, the 2010 Census and American Community Survey (ACS), to restricted Homeless Management Information System (HMIS) data, HUD's public-use point-in-time (PIT) estimates, and the Housing Inventory Count (HIC) at the national and individual level. We also develop a new approach to estimating the size of the sheltered homeless population using linked Census and HMIS microdata. Our analyses suggest that on a given night there are about 400,000 people experiencing homelessness in shelters in the U.S. and about 200,000 people sleeping on the streets, with this latter estimate subject to greater uncertainty. More than 90 percent of those in shelters appear to be counted in the Census, although many are classified as housed or in other group quarters, due largely to ambiguity in the definition of a homeless shelter. This paper lays the foundation for pathbreaking future work with these data on the U.S. homeless population.

Developing an operational definition of housing instability and homelessness in Veterans Health Administration's medical records.

The main objective of this study was to examine how homelessness and housing instability is captured across data sources in the Veterans Health Administration (VHA). Data from 2021 were extracted from three data repositories, including the Corporate Data Warehouse (CDW), the Homeless Operations Management System (HOMES), and the Homeless Management Information System (HMIS). Using these three data sources, we identified the number of homeless and unstably housed veterans across a variety of indicators. The results showed that the use of diagnostic codes and clinic stop codes identified a large number of homeless and unstably housed veterans, but the use of HOMES and HMIS data identified additional homeless and unstably housed veterans to provide a complete count. A total of 290,431 unique veterans were identified as experiencing homelessness or housing instability in 2021 and there was regional variability in how homelessness and housing stability were captured across data sources, supporting the need for more uniform ways to operationalize these conditions. Together, these findings highlight the and encourage use of all available indicators and data sources to identify homelessness and housing instability in VHA. These methodologies applied to the largest healthcare system in the U.S. demonstrate their utility and possibilities for other healthcare systems. Transparent practices about data sources and indicators used to capture homelessness and housing instability should be shared to increase uniform use.

Who Counts? Educational Disadvantage among Children Identified as Homeless and Implications for the Systems That Serve Them

The Department of Education’s (ED) definition of homelessness includes any child who lacks a fixed, regular, and adequate nighttime residence, but the Department of Housing and Urban Development (HUD) uses a narrower definition that excludes doubled-up families. These definitions determine how resources are prioritized for families, yet we know very little about the differences in risks faced by children identified by these departments. We leverage a data linkage between public schools and homeless management information systems in Minnesota to provide novel evidence on the educational risks faced by children identified as homeless by ED and HUD. We find that ED-identified-homeless and HUD-identified-homeless children experience comparable increases in chronic absenteeism and school instability in the year they experience homelessness, challenging the popular conception that doubled-up families face lower educational risks. Using these findings, we discuss strategies to integrate homelessness data better, assess needs, and prioritize resources for children experiencing homelessness.

Evaluation of the Homeless Management Information System for COVID-19 Surveillance Among People Experiencing Homelessness.

Variable and incomplete reporting of housing status creates challenges in the surveillance of coronavirus disease 2019 (COVID-19) among the homeless population in Los Angeles County (LA County) and nationwide. We developed standard investigation procedures to assess the housing status of LA County COVID-19 patients. Using data sharing procedures, we matched COVID-19 patients to Homeless Management Information System (HMIS) client profiles and supplemented with additional data sources for contributory data points and to further housing status ascertainment. We identified 10 586 COVID-19 patients among people experiencing homelessness (PEH) between 30 March 2020 and 30 December 2021; 2801 (26.5%) patients were first identified from HMIS profile matches, 1877 (17.7%) from quarantine/isolation housing intake rosters, 573 (5.4%) from hospital records, 749 (7.1%) from case and contact interviews, 3659 (34.6%) directly from PEH medical and service providers, and 927 (8.8%) had unknown sources. Among COVID-19 patients matched to HMIS profiles, 5351 (42.5%) were confirmed to be PEH at the time of COVID-19 diagnosis. Interoperability between public health data, HMIS, and external partners have been critical components in evaluating the impact of COVID-19 among the LA County homeless population. No one data source was complete for COVID-19 surveillance in this population.

Continuum of Carcerality: How Liberal Urbanism Governs Homelessness

A distinctive regime of the spatial governance of poverty is underway in Los Angeles, one in which the criminalization of homelessness is yoked to placements in carceral shelter and framed as the right to the housing. In this essay, we uncover the state violence inherent in such liberal urbanism by showing how such placements insert the unhoused into a system of carcerality while promising that they are the path to permanent housing. Seeking to trouble and critique the dominant paradigm of U.S. homeless management, Continuum of Care, we conceptualize a continuum of carcerality that stretches from encampment sweeps to seeming housing solutions. We find that the placements are a ruse, reproducing housing insecurity through exclusion, expulsion, and waiting, a structural condition that we term permanent displaceability. By focusing on an emergent mercenary entity, Urban Alchemy, and its expanding contracts for displacement and security, we show that there is a distinctive political economy associated with the continuum of carcerality. Our analysis is rooted in an ethnographic research methodology that centers the radical praxis of unhoused comrades. To this end, we foreground the demands of a homeless union that formed during the COVID-19 pandemic, UTACH, Unhoused Tenants Against Carceral Housing, which uses the framework of “carceral housing” to hold the state accountable to its promise of housing while refusing the carceral contracts that accompany such a promise. We take up their critique as an example of the ongoing reinscription of the terms of tenancy under conditions of global racial capitalism.

Exploring the potential of homeless management information system data for understanding the mobility of people experiencing homelessness

ABSTRACT Previous research has found that people experiencing homelessness move from one location to another for a variety of reasons, including to improve access to services and supports. Understanding the mobility behavior of a community’s homeless population has direct implications for service and policy planning. Past research on homelessness and mobility has predominantly used self-report measures and qualitative methods. Incorporating more objective and administrative measures, such as Homeless Management Information System (HMIS) data, is far less common. Using HMIS data to study mobility has the added benefit of allowing Continuums of Care (CoCs) to routinely look at the mobility of services users. The current study uses HMIS data from 21 counties, representing 12 CoCs, in New York State – covering a large, geographically diverse region. The analysis focuses on examining service user characteristics associated with accessing a homeless service outside the county where a person was last housed. Findings reveal that the likelihood of accessing a homeless service outside the county of last residence is associated with several demographic, background, and service use factors. Considerations for using HMIS data to explore mobility and service use dynamics are discussed.

The Determinants of Length of Homeless Shelter Stays: Evidence-Based Regression Analyses.

Objective: To identify determinants that contribute to the length of homeless shelter stay. Methods: We utilized a unique dataset from the Homeless Management Information Systems from Boston, Massachusetts, United States, which contains 44,197 shelter stays for 17,070 adults between Jan. 2014 and May 2018. Results: Our statistical analyses and regression model analyses show that factors that contribute to the length of a homeless shelter stay include being female, senior, disability, being Hispanic, or being Asian or Black African. A significant fraction of homeless shelter stays (76%) are experienced by individuals with at least one of three disabilities: physical disability, mental health issues, or substance use disorder. Recidivism also contributes to longer homeless shelter stays. Conclusion: The results suggest possible program and policy implications. Several factors that contribute to longer homeless shelter stay, such as gender, age, disability, race, and ethnicity, may have funding implications. Age may point to the need for early interventions. Disability is developmental and may benefit from treatment and intervention. Finally, we find that length of stay and recidivism are not independent, and may form a vicious cycle that requires additional investigation.

Who Is Couch-Surfing and Who Is on the Streets? Disparities Among Racial and Sexual Minority Youth in Experiences of Homelessness

PurposeYouth experiencing homelessness (YEH) often engage in “couch-surfing,” or frequently moving from one tenuous living arrangement to another. Understanding the characteristics and risk factors associated with couch-surfing is necessary to designing adequate responses to youth homelessness. The present study aims to investigate factors associated with youth at risk of couch-surfing or sleeping on the streets relative to staying in a shelter. MethodsThe present study used Homeless Management Information System administrative data sourced from 16 communities across the U.S. between January 2015 and February 2017 (n = 9,417). Multinomial logistic regression models were used to explore correlates (e.g., demographics, homeless histories, risk and victimization, behavioral health, and self-sufficiency) of couch-surfing or sleeping on the streets relative to staying in an emergency shelter program. ResultsYEH identifying as female; Black or another non-Latinx youth of color; or as lesbian, gay, bisexual, questioning, or another sexual orientation (LGBQ+) were at greater risk of couch-surfing relative to staying in a shelter. YEH who threatened to harm themselves or others in the preceding 12 months or who attributed their homelessness to an abusive relationship were significantly more likely to either be couch-surfing or on the streets. DiscussionService providers must recognize and validate the vulnerabilities and risks experienced by couch-surfing YEH in order to help reduce barriers to accessing services faced by this population. Federal definitions of homelessness should be aligned to correct systemic biases and more accurately reflect the realities of how youth experience homelessness.

The Involvement of Business Elites in the Management of Homelessness: Towards a Privatization of Service Provision for Homeless People?

Although the influence of local urban elites on urban planning is well established in urban studies and geography, the ways in which business and property owners take part in the management of homelessness has received far less attention. This article focuses on Portland (OR) in the United States as a means of understanding the motivations that underlie the role of the private sector and its impact on public policies. To this end, I focus on the support by Portland's downtown Business Improvement District of homeless outreach programs, and on the funding of two homeless shelters by business elites / philanthropists. I argue that although public authorities have different views on the actions to be taken to end homelessness, business elites often manage to bring initially-reluctant public authorities to support their projects in what might be termed a forced-march cooperation. I also highlight the versatility of the private sector and business elites’ participation in homelessness management, given that the outreach programs they support and the homeless facilities they fund provide services for the homeless while simultaneously removing them from visible public space. In this sense, the involvement of business and property owners is also a way for them to protect their own interests.

Race and retention in permanent supportive housing: a secondary analysis of housing outcomes

ABSTRACT Despite the overrepresentation of People of Color among people experiencing homelessness and ongoing housing discrimination against racial and ethnic minorities, research has paid scant attention to the intersections of race and homelessness, including assessments of race-related outcomes of permanent supportive housing (PSH), a mainstay homeless assistance program in the U.S. The purpose of this study, therefore, framed by the Public Health Critical Race praxis, was to use secondary Homeless Management Information System (HMIS) data obtained from a Continuum of Care in North Texas to explore the intersections of race and PSH outcomes. Given the high representation of veterans of military service among the sample, and the parallel VA service system generally accessible to veterans, separate analyses examined housing loss among veterans and non-veterans. Findings show that, while race does predict housing loss for all participants or any race or veteran-based subgroup, race was associated with demographic identifiers, such as gender, disabling condition, domestic violence victimization, income, and access to benefits, but these factors were also largely insignificant predictors in regression models. The only demographic identifier predicting housing loss was the number of times an individual was homeless in the last three years, predicting housing loss for all service recipients, White service recipients, and non-veteran service recipients. The results of the study are discussed, including important between-group variations that inform recommendations for administrative policy and practice.

Changes in health and health care utilization following eviction from public housing.

This study sought to (1) determine the number of persons evicted from the Durham Housing Authority (DHA) over a 5-year period, (2) explore changes in the number of persons with various medical diagnoses and health care utilization patterns before and after eviction, and (3) examine how many persons evicted from DHA became literally homeless. This was a pre/post cross-sectional quantitative study. Heads of households evicted from DHA properties from January 1, 2013 through December 31, 2017 were included in the study. We matched people evicted by the DHA in a university health system electronic health record system to determine changes in diagnoses and health care utilization before and after eviction. We also matched the cohort in the homeless management information system to determine how many persons evicted became literally homeless. Findings indicate statistically significant increases in persons with medical diagnoses in five of ten categories, total hospital admissions, and emergency department visits after eviction. Of the 152 people included in the study, 34 (22%) became literally homeless. Health and health care utilization patterns were different before and after eviction. Implications for clinicians are explored.

Homeless Management During Movement Control Order Due To COVID-19 Pandemic: Experience from Federal Territory Kuala Lumpur, Malaysia

Malaysia has been hit by COVID-19 pandemic since 2020 and this problem also affects countries around the world. This COVID-19 infection does not distinguish age, gender, educational and financial status. Homeless people are also not exempt from being infected with COVID-19, especially when the government implements the Movement Control Order, particularly these people who have no permanent home. This article describes the activities carried out by the government agencies, especially from the Ministry of Health Malaysia, Department of Social Welfare, National Anti-Drugs Agency, Immigration Department of Malaysia, as well as other non-governmental agencies in the Federal Territory of Kuala Lumpur on homeless people during movement control orders. It is hoped that this shared experience can be a guide to government agencies, non-governmental organizations, private sectors and individuals in other states to manage this underprivileged group, especially during the ongoing COVID-19 pandemic