Exploring the Barriers and Facilitators Experienced by Palliative Health Care Providers Working with Patients Experiencing Homelessness during the COVID-19 Pandemic
Bibliographic record
Abstract
Background: Patients experiencing homelessness not only have higher rates of medical complexity, comorbidity, and mortality, but also face barriers to accessing palliative care services. In structurally vulnerable populations with palliative care needs, these barriers are compounded, creating significant challenges for both patients and providers that have important health equity implications. Objective: The aim is to explore the experiences of palliative care providers working with patients experiencing homelessness during the COVID-19 pandemic and understand the barriers they faced in providing care, as well as facilitators that aided in the success of their teams. Methods: Seven health care providers from two Canadian palliative outreach teams involved in delivering palliative care services to patients experiencing homelessness during the COVID-19 pandemic participated in audio-recorded and transcribed videoconferencing interviews. Analysis was completed using generic descriptive thematic analysis. Results: Five key themes were identified: (1) factors negatively impacting patient health, (2) use of technology, (3) care provider emotions, (4) care provider education and advocacy, and (5) outreach team factors. Conclusion: Identified barriers during the pandemic included worsening of existing patient vulnerabilities, as well as challenges incorporating technology into care. Providers faced increased emotional burden, with a rise in workload, stress, fear, and grief. However, several facilitators allowed teams to provide high-quality care to this vulnerable population, including team support, interprofessional collaboration, and advocacy and education initiatives. The outreach model also proved to be a highly flexible, resilient, and adaptable model for providing care during the COVID-19 pandemic.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".