Physician continuity of care in the last year of life in community-dwelling adults: retrospective population-based study
Bibliographic record
Abstract
OBJECTIVE: To describe the timing of involvement of various physician specialties over the last year of life across different levels of primary care physician continuity for differing causes of death. METHODS: We conducted a retrospective cohort study of adults who died in Ontario, Canada, between 1 January 2013 and 31 December 2018, using linked population level health administrative data. Outcomes were median days between death and first and last outpatient palliative care specialist encounter, last outpatient encounter with other specialists and with the usual primary care physician. These were calculated by tertile of score on the Usual Provider Continuity Index, defined as the proportion of outpatient physician encounters with the patient's primary care physician. RESULTS: Patients' (n=395 839) mean age at death was 76 years. With increasing category of usual primary care physician continuity, a larger proportion were palliative care generalists, palliative care specialist involvement decreased in duration and was concentrated closer to death, the primary care physician was involved closer to death, and other specialist physicians ceased involvement earlier. For patients with cancer, palliative care specialist involvement was longer than for other patients. CONCLUSIONS: Compared with patients with lower continuity, those with higher usual provider continuity were more likely to have a primary care physician involved closer to death providing generalist palliative 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".