The homeless Coordinated Entry System
The VI-SPDAT and other predictors of establishing eligibility for services for single homeless adults
Bibliographic Data
| ID | 20408685 |
|---|---|
| Authors | Caroline Balagot (San Diego State University, corresponding author), Hector Lemus (0000-0001-5959-1560, San Diego State University), Megan Hartrick (Regional Task Force on the Homeless San Diego, San Diego, CA, USA), Tamera Kohler (Regional Task Force on the Homeless San Diego, San Diego, CA, USA), Suzanne Lindsay (San Diego State University), Suzanne P Lindsay (San Diego State University) |
| Year | 2019 |
| Volume | 28 |
| Issue | 2 |
| Pages | 149-157 |
| Publication date | 2019-07-03 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Social Distress and the Homeless (JOURNAL) |
| Journal identifiers | ISSN: 1053-0789 • E-ISSN: 1573-658X |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10530789.2019.1622858 |
| OpenAlex | W2946841489 |
| Language | EN |
| Citations received | 17 |
| References cited | 5 |
Despite the spectrum of available resources, homelessness is a persistent societal and public health challenge throughout the United States and in San Diego County. Beginning in January 2014, San Diego began the integration of a Coordinated Entry System into its homeless system-of-care. This historical prospective study examined the predictors of establishing eligibility for permanent housing resources among 15,042 single homeless adults enrolled in the Coordinated Entry System Multivariable logistic regression was conducted to assess the relationship between client vulnerability as measured by the triage tool VI-SPDAT and establishing client eligibility for permanent housing. Overall, being of moderate or high vulnerability was associated with establishing eligibility for a permanent housing resource. Veterans established eligibility faster and more frequently than others, regardless of their vulnerability score. However, the demand for services far outweighed the ability of the system to respond to those with moderate to high vulnerability. More housing navigators and fewer client “hand-offs” between housing professionals are recommended to increase the efficiency of the process. Additional research examining the second and third steps is also needed to more fully understand the factors that promote permanent housing solutions for those seeking services
Business · Computer security · Environmental health · Housing First · Logistic regression · Medical emergency · Mental health · Political science · Psychiatry · Supportive housing · Triage · Welfare · Welfare system · Computer Science · Food Security and Health in Diverse Populations · Homelessness and Social Issues · Housing, Finance, and Neoliberalism · Medicine · Psychology · Gerontology
The Modern Day Asylum
An Assessment of Racial Disparities in Pretrial Decision‐Making Using Misclassification Models
Expert Perspectives on Service User Transitions Within and From Homeless Service Programs
Assessing the Reliability of SPDAT Homelessness Vulnerability Tools and the Impact of Assessor Consistency and Changes to Homeless Vulnerability Over Time
Improving Safe Housing Access for Domestic Violence Survivors Through Systems Change
Coordinated Access and Coordinated Entry System Processes in the Housing and Homelessness Sector
“You Don’t See Them on the Streets of Your Town”
An Analysis of Safe Parking Programs
“Do You Have a Way, If I Become Feeble, That I Still Can Be Safe?”
Recordkeeping, logistics, and translation
Invisible intersectionality in measuring vulnerability among individuals experiencing homelessness – critically appraising the VI-SPDAT
“What benefits do homeless systems get from by-name data?”
Mobility-Related Barriers to Accessing Homeless Services
Navigating pathways from temporary hotel shelters to permanent housing during California’s Covid-19 response
Complexity among people experiencing homelessness
Placement of chronically homeless into different types of permanent supportive housing before and after a coordinated entry system
After automation
| Citations per year | 2.83 |
|---|---|
| Citation span | 2020 - 2026 (7) |
| Highly cited | No |