Predicting homelessness among individuals diagnosed with substance use disorders using local treatment records

Addict Behav. 2020 Mar:102:106160. doi: 10.1016/j.addbeh.2019.106160. Epub 2019 Oct 22.

Abstract

One in five homeless people in the United States has a substance use and/or a mental health disorder. Substance use disorders substantially impact the ability to obtain and retain appropriate housing. Professionals who provide substance use treatment are typically required to provide housing assistance by prioritizing clients according to their risk for becoming or remaining homeless; however, existing methods for prioritizing clients can be time-consuming and staff- and training-intensive. This study analyzed the potential use of variables from locally collected and readily available treatment admission records to prioritize clients needing housing assistance. This study analyzed county-level substance use treatment admission and discharge records of 1862 treatment episodes for 1642 clients in publicly funded treatment programs in Utah County, Utah. For at least one admission or discharge, 185 clients lived on the streets or in a homeless shelter. Approximately 55% of treatment episodes that ended in homelessness at discharge did not originally begin with clients being homeless, suggesting a gap in prioritizing individuals for housing assistance. Logistic regression showed statistically significant associations between eventually becoming homeless at the time of discharge and being originally homeless on admission; older age (45 years or older); methamphetamine as primary drug used; and a diagnosis of axis I/II psychiatric disorder besides substance use disorder. These findings suggest that local and routinely collected substance use treatment records may be predictive of homelessness and potentially useful in prioritizing clients for housing assistance.

Keywords: Case management; Homelessness; Housing assistance; Substance use; Treatment Episode Dataset (TEDS).

MeSH terms

  • Adolescent
  • Adult
  • Electronic Health Records*
  • Female
  • Housing*
  • Humans
  • Ill-Housed Persons*
  • Male
  • Middle Aged
  • Patient Admission / statistics & numerical data*
  • Patient Discharge / statistics & numerical data*
  • Substance Abuse Treatment Centers*
  • Substance-Related Disorders / therapy*
  • Utah / epidemiology
  • Vulnerable Populations
  • Young Adult