Physician home visits to rostered patients during their last year of life: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Physician home visits are associated with better health outcomes, yet most patients near the end of life never receive such a visit. Our objectives were to describe the receipt of physician home visits during the last year of life after a referral to home care - an indication that the patient can no longer live independently - and to measure associations between patient characteristics and receipt of a home visit. METHODS: We conducted a retrospective cohort study using linked population-based health administrative databases housed at ICES. We identified adult (aged ≥ 18 yr) decedents in Ontario who died between Mar. 31, 2013, and Mar. 31, 2018, who were receiving primary care and were referred to publicly funded home care services. We described the provision of physician home visits, office visits and telephone management. We used multinomial logistic regression to calculate the odds of receiving home visits from a rostered primary care physician, controlling for referral during the last year of life, age, sex, income quintile, rurality, recent immigrant status, referral by rostered physician, referral during hospital stay, number of chronic conditions and disease trajectory based on the cause of death. RESULTS: Of the 58 753 decedents referred in their last year of life, 3125 (5.3%) received a home visit from their family physician. Patient characteristics associated with higher odds of receiving home visits compared to office-based or telephone-based care were being female (adjusted odds ratio [OR] 1.28, 95% confidence interval [CI] 1.21-1.35), being 85 years of age or older (adjusted OR 2.42, 95% CI 1.80-3.26) and living in a rural area (adjusted OR 1.09, 95% CI 1.00-1.18). Increased odds were associated with home care referrals by the patient's primary care physician (adjusted OR 1.49, 95% CI 1.39-1.58) and referrals occurring during a hospital stay (adjusted OR 1.20, 95% CI 1.13-1.28). INTERPRETATION: A small proportion of patients near the end of life received home-based physician care, and patient characteristics did not explain the low visit rates. Future work on system- and provider-level factors may be critical to improve access to home-based end-of-life primary 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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".