Addressing housing insecurity as a social determinant of health: A systematic review of interventions in healthcare settings
Bibliographic record
Abstract
BACKGROUND: Stable housing is a key social determinant of health. Those experiencing homelessness or housing insecurity are known to have increased healthcare utilization and yet worse healthcare outcomes compared to securely housed individuals. Housing interventions offered via healthcare settings provide an opportunity to reach this population. We conducted a systematic review to 1) identify interventions which address housing insecurity and engage healthcare settings; 2) determine effectiveness of these interventions; and 3) ascertain common characteristics of effective interventions to inform new ways to address housing insecurity within healthcare. METHODS: Twelve databases were searched for relevant studies published from January 1, 1990-January 3, 2025. We included intervention studies aimed at meeting patients' housing needs as a primary or secondary outcome and initiated by referrals from within the healthcare system. Titles, abstracts and full-text articles were reviewed by two independent reviewers. Data were extracted relevant to study design, population, and intervention details. Quality appraisals were conducted using JBI critical appraisal tools. Discrepancies at each stage were resolved through reviewer or team discussions. RESULTS: We identified 19 studies from 12,483 unique citations. Most were randomized controlled trials and of moderate quality. Studies primarily addressed the housing needs of adults with mental health or substance use issues (n = 9; 47 %). We identified three common characteristics of housing interventions with positively-associated outcomes active community referrals (i.e. connection to a professional social worker or case manager instead of sharing passive information), incorporating multi-component interventions to address housing and additional health needs, and utilizing case management or assertive community treatment approaches. CONCLUSIONS: Interventions to address housing insecurity can be successfully situated within healthcare settings, although more research is required to examine the cost-effectiveness of such interventions. The characteristics of the interventions identified can be used to inform new housing interventions in healthcare settings to address this critical social determinant of health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".