Development of a homelessness risk screening tool for emergency department patients. (20th October 2021)

• Record Type: Journal Article
• Authors: Doran, Kelly M.; Johns, Eileen; Zuiderveen, Sara; Shinn, Marybeth; Dinan, Kinsey; Schretzman, Maryanne; Gelberg, Lillian; Culhane, Dennis; Shelley, Donna; Mijanovich, Tod
• Is Part Of: Health services research. Volume 57:Number 2(2022)
• Page Start: 285
• Page End: 293
• Publication Date: 2021-10-20
• Subjects: delivery of health care -- emergency service -- homeless persons -- hospital -- housing -- social problems; Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.13886
• Languages: English
• ISSNs: 0017-9124

Abstract

Abstract: Objective: To develop a screening tool to identify emergency department (ED) patients at risk of entering a homeless shelter, which could inform targeting of interventions to prevent future homelessness episodes. Data sources: Linked data from (1) ED patient baseline questionnaires and (2) citywide administrative homeless shelter database. Study design: Stakeholder‐informed predictive modeling utilizing ED patient questionnaires linked with prospective shelter administrative data. The outcome was shelter entry documented in administrative data within 6 months following the baseline ED visit. Exposures were responses to questions on homelessness risk factors from baseline questionnaires. Data collection/extraction methods: Research assistants completed questionnaires with randomly sampled ED patients who were medically stable, not in police/prison custody, and spoke English or Spanish. Questionnaires were linked to administrative data using deterministic and probabilistic matching. Principal findings: Of 1993 ED patients who were not homeless at baseline, 5.6% entered a shelter in the next 6 months. A screening tool consisting of two measures of past shelter use and one of past criminal justice involvement had 83.0% sensitivity and 20.4% positive predictive value for future shelter entry. Conclusions: Our study demonstrates the potential of using cross‐sector data to improve hospital initiatives to address patients' social needs.