Rates of health services use among residents of retirement homes in Ontario: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Because there are no standardized reporting systems specific to residents of retirement homes in North America, little is known about the health of this distinct population of older adults. We evaluated rates of health services use by residents of retirement homes relative to those of residents of long-term care homes and other populations of older adults. METHODS: We conducted a retrospective cohort study using population health administrative data from 2018 on adults 65 years or older in Ontario. We matched the postal codes of individuals to those of licensed retirement homes to identify residents of retirement homes. Outcomes included rates of hospital-based care and physician visits. RESULTS: We identified 54 733 residents of 757 retirement homes (mean age 86.7 years, 69.0% female) and 2 354 385 residents of other settings. Compared to residents of long-term care homes, residents of retirement homes had significantly higher rates per 1000 person months of emergency department visits (10.62 v. 4.48, adjusted relative rate [RR] 2.61, 95% confidence interval [CI] 2.55 to 2.67), hospital admissions (5.42 v. 2.08, adjusted RR 2.77, 95% CI 2.71 to 2.82), alternate level of care (ALC) days (6.01 v. 2.96, adjusted RR 1.51, 95% CI 1.48 to 1.54), and specialist physician visits (6.27 v. 3.21, adjusted RR 1.64, 95% CI 1.61 to 1.68), but a significantly lower rate of primary care visits (16.71 v. 108.47, adjusted RR 0.13, 95% CI 0.13 to 0.14). INTERPRETATION: Residents of retirement homes are a distinct population with higher rates of hospital-based care. Our findings can help to inform policy debates about the need for more coordinated primary and supportive health care in privately operated congregate care homes.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".