The Effect of a Housing First Intervention on Acute Health Care Utilization among Homeless Adults with Mental Illness: Long-term Outcomes of the At Home/Chez-Soi Randomized Pragmatic Trial
Bibliographic record
Abstract
We assessed the effects of the Toronto Site Housing First (HF) intervention on hospitalizations and emergency department (ED) visits among homeless adults with mental illness over 7 years of follow-up. The Toronto Site is part of an unblinded multi-site randomized pragmatic trial of HF for homeless adults with mental illness in Canada, which followed participants up to 7 years. Five hundred seventy-five participants were recruited and classified as having high (HN) or moderate need (MN) for mental health support services. Each group was randomized into intervention (HF) and treatment as usual groups, and 567 (98.6%) consented to link their data to health administrative databases. HF participants received a monthly rent supplement of $600 (Canadian) and assertive community treatment (ACT) support or intensive care management (ICM) support based on need level. Treatment as usual (TAU) participants had access to social, housing, and health services generally available in the community. Outcomes included all-cause and mental health-specific hospitalization, number of days in hospital, and ED visit. We used GEE models to estimate ratio of rate ratios (RRR). The results showed HF with ACT had no significant effect on hospitalization rates among HN participants, but reduced the number of days in hospital (RRR = 0.32, 95% CI 0.16-0.63) and number of ED visits (RRR = 0.57, 95% CI 0.34-0.95). HF with ICM resulted in an increase in the number of hospitalizations (RRR = 1.69, 95% CI 1.09-2.60) and ED visit rates (RRR = 1.42, 95% CI 1.01-2.01) but had no effect in days in hospital for MN participants. Addressing the health needs of this population and reducing acute care utilization remain system priorities. Trial registration: http://www.isrctn.com/identifier: ISRCTN42520374.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".