Health supports needed for homeless persons transitioning from hospitals
Bibliographic record
Abstract
Being homeless has a negative effect on health and the health needs of individuals experiencing homelessness are complex and challenging to address. As a result of limited access to and use of primary healthcare, the main point of entry into the healthcare system for individuals experiencing homelessness is often hospitals and emergency departments. Persons experiencing homelessness are commonly discharged from hospital settings to locations that do not support recovery or access to follow-up care (e.g. shelters or the street). This can be costly to both the healthcare system and to individuals' health and quality of life. We conducted a scoping review of the literature published between 2007 and 2017 to identify the types of health supports needed for persons experiencing homelessness who are discharged from the hospital. Thirteen literature sources met inclusion criteria and thematic data analyses by two researchers resulted in the identification of six themes related to the types of health supports needed for persons experiencing homelessness who are transitioning (i.e. being discharged) from the hospital. Using a community consultation approach, the scoping review themes were validated with 23 health and shelter service providers and included in our integrated findings. Themes included: (a) a respectful and understanding approach to care, (b) housing assessments, (c) communication/coordination/navigation, (d) supports for after-care, (e) complex medical care and medication management, and (f) basic needs and transportation. These themes were found to resonate with participants of the community consultation workshop. Recommendations for trauma-informed care and patient- or client-centred care approaches are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".