Family Physician Continuity of Care in End-of-Life Homecare Cancer Patients and its Association with Acute Care Services Use
Bibliographic record
Abstract
Background and Objectives: Previous research has examined the effect of family physician continuity of care within end-of-life care cancer patients and its association with reduced use of acute care services. However, such research has not been examined in the end of life homecare cancer population. Objectives: To investigate the association of family physician continuity with location of death, hospital and emergency room (ER) visits in the last 2 weeks of life in end of life homecare cancer patients. Research Design: Retrospective study involving secondary data analysis of 7 linked databases. Subjects: All those who died of cancer between January 1, 2006 to December 31, 2006 in Ontario who had at least 1 visit to a family physician and enrolled in homecare for at least 2 weeks. Methods: The relationship of family physician continuity of care and location of death, and hospital and ER visits in the last 2 weeks of life was examined using logistic regression. Results: The Usual Provider of Care (UPC) measure demonstrated a dose response relationship with increasing continuity resulting in decreased odds of dying in the hospital and visiting the hospital and ER in the last 2 weeks of life. The Family Physician visits per week measure demonstrated a threshold effect relationship with location of death and hospital visits and dose response relationship with ER visits in the last 2 weeks of life. Conclusions: These results demonstrate an association between family physician continuity of care and location of death and visits to the hospital and ER in the last 2 weeks of life. This indicates the need for more involvement of family physicians in end of life cancer care.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".