Continuity of Care among People Experiencing Homelessness and Mental Illness: Does Community Follow‐up Reduce Rehospitalization?
Bibliographic record
Abstract
OBJECTIVE: To examine whether timely outpatient follow-up after hospital discharge reduces the risk of subsequent rehospitalization among people experiencing homelessness and mental illness. DATA SOURCES: Comprehensive linked administrative data including hospital admissions, laboratory services, and community medical services. STUDY DESIGN: Participants were recruited to the Vancouver At Home study based on a-priori criteria for homelessness and mental illness (n = 497). Logistic regression analysis was used to assess the relationship between outpatient care within 7 days postdischarge and subsequent rehospitalization over a 1-year period. DATA EXTRACTION: Data were extracted for a consenting subsample of participants (n = 433) spanning 5 years prior to study enrollment. PRINCIPAL FINDINGS: More than half of the eligible sample (53 percent; n = 128) were rehospitalized within 1 year following an index hospital discharge. Neither outpatient medical services nor laboratory services within 7 days following discharge were associated with a significantly reduced likelihood of rehospitalization within 2 months (AOR = 1.17 [CI = 0.94, 1.46]), 6 months (AOR = 1.00 [CI = 0.82, 1.23]) or 12 months (AOR = 1.24 [CI = 1.02, 1.52]). CONCLUSIONS: In contrast to evidence from nonhomeless samples, we found no association between timely outpatient follow-up and the likelihood of rehospitalization in our homeless, mentally ill cohort. Our findings indicate a need to address housing as an essential component of discharge planning alongside outpatient care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".