Palliative Care for Cancer Patients Near End of Life in Acute-Care Hospitals across Canada: A Look at the Inpatient Palliative Care Code
Bibliographic record
Abstract
Hospitals play an important role in the care of patients with advanced cancer: nearly half of all cancer deaths occur in acute-care settings. The need for increasing access to palliative care and related support services for patients with cancer in acute-care hospitals is therefore growing. Here, we examine how often and how early in their illness patients with cancer might be receiving palliative care services in the 2 years before their death in an acute-care hospital in Canada. The palliative care code from inpatient administrative databases was used as a proxy for receiving, or being referred for, palliative care. Currently, the palliative care code is the only data element routinely collected from patient charts that allows for the tracking of palliative care activity at a pan-Canadian level. Our findings suggest that most patients with cancer who die in an acute-care hospital receive a palliative designation; however, many of those patients are identified as palliative only in their final admission before death. Of the patients who received a palliative designation before their final admission, nearly half were identified as palliative less than 2 months before death. Findings signal that delivery of services within and between jurisdictions is not consistent, that the palliative care needs of some patients are being missed by physicians, and that palliative care is still largely seen as end-of-life care and is not recognized as an integral component of cancer care. Measuring the provision of system-wide palliative care remains a challenge because comprehensive national data about palliative care are not currently reported from all sectors. To advance measurement and reporting of palliative care in Canada, attention should be focused on collecting comparable data from regional and provincial palliative care programs that individually capture data about palliative care delivery in all health care sectors.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".