‘I’m only dealing with the acute issues’: How medical ward ‘busyness’ constrains care of the dying
Bibliographic record
Abstract
Acute hospital units are a common location of death. Curative characteristics of the acute medical setting make it difficult to provide adequate palliative care; these characteristics include an orientation to life-prolonging treatment, an emphasis on routine or task-oriented care and a lack of priority on emotional engagement with patients. Indeed, research shows that dying patients in acute medical units often experience unmet needs at the end of life, including uncontrolled symptoms (e.g. pain, breathlessness), inadequate emotional support and poor communication. A focused ethnography was conducted on an acute medical ward in Canada to better understand how this curative/life-prolonging care environment shapes the care of dying patients. Fieldwork was conducted over a period of 10 months and included participant-observation and interviews with patients, family members and staff. On the acute medical ward, a 'logic of care' driven by discourses of limited resources and the demanding medical unit created a context of busyness. Staff experienced an overwhelming workload and felt compelled to create priorities, which reflected taken-for-granted values regarding the importance of curative/life-prolonging care over palliative care. This could be seen through the way staff prioritized life-prolonging practices and rationalized inconsistent and less attentive care for dying patients. These values influenced care of the dying through delaying a palliative approach to care, limiting palliative care to those with cancer and providing highly interventive end-of-life care. Awareness of these taken-for-granted values compels a reflective and critical approach to current practice and how to stimulate change.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.036 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".