Developing Palliative Care Surveillance in Canada: Results of a Pilot Study
Bibliographic record
Abstract
OBJECTIVE: A pilot study compiled data from six palliative care centres across Canada to assess the feasibility of developing a national surveillance system. METHODS: Data provided for the three-year period between 1993-1997 were combined into a comparative minimum data set. Analyses included 6,369 care episodes from five centres, plus 948 patients from one centre. RESULTS: Care was provided in various settings including acute care wards, dedicated palliative care units, tertiary care, chronic care, and at home. Palliative care patients comprised equal numbers of men and women, with a median age of 69 years; 92% had cancer diagnoses. Median length of stay (LOS) for each care episode was 13 days, increasing to 40-43 days for a patient's entire time in care. LOS varied greatly, by care setting, from seven days (dedicated unit), to 19 days (tertiary unit), 37 days (home), and 54 days (chronic care). Our findings are similar to those reported from national surveys in Australia and the United Kingdom. SUMMARY: This study generated useful baseline data and identified key issues requiring resolution before establishing a national surveillance system, including the need to track patients across care settings.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".