Contextualizing the Crisis in the Hospital Discharge Process for People Experiencing Homelessness in Toronto, Canada: “Danger and Opportunity”
Bibliographic record
Abstract
Canadian scholarship shows higher rates of hospital readmission among homeless than housed populations, signaling that their health needs are not being met post-discharge. The discharge process is meant to ensure patients’ care is transitioned to the community and is recognized by communities and homelessness researchers as a critical point of transition; yet little research has examined this process from acute physical care services. This exploratory qualitative study aimed to characterize the hospital discharge process for people experiencing homelessness when discharged from general medicine in Toronto, Canada. Informed by critical realism, it explains how and why discharging homeless patients remains a challenge. Semi-structured in-depth interviews were held with 16 hospital workers involved in the discharge process from three urban hospitals, six shelter workers who receive discharged patients, and 11 key informants with expertise in homelessness and healthcare. Results broadly characterize the process, situating inadequate discharges as a consequence of the failure of multiple systems on which the discharge process relies: barriers to publicly-funded systems, and silos and gaps between these systems. Further findings shed light on contextual influences of two features of the discharge process. First, finding an appropriate discharge destination was challenged by historical and contemporary social and economic contexts that triggered the adoption of efficiency and accountability measures in hospitals, and eligibility and exclusion criteria in shelters. Second, within the legal context of health information protection in Ontario, knowledge sharing between hospitals and shelters was complicated by the concept of circle of care that excludes shelter workers from the discharge process. Certain geographic and organizational contexts have activated the development of institutional- and individual-level relationships between some hospitals and shelters or their workers, which improved knowledge sharing. Despite the agency exhibited by our participants, the discharge process was marred by uneven power dynamics between hospitals and shelters and a service gap where neither hospitals nor shelters are responsible for the wellbeing of homeless patients post-discharge. Future research should centre the voices of people experiencing homelessness who go through the discharge process and adopt an intersectional analysis to better understand how the discharge process is shaped by patients’ intersecting social locations.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.036 | 0.023 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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".