Medical Care Provider Involvement in Ontario Assisted Living Homes: A Descriptive Cross-Sectional Survey Analysis
Bibliographic record
Abstract
OBJECTIVES: Assisted living is growing in Ontario. Medical services are not regulated in Ontario, resulting in variability of physician involvement. We described medical service provider involvement and practice characteristics in assisted living homes. DESIGN: Descriptive cross-sectional study. SETTING AND PARTICIPANTS: A total of 88 assisted living homes in Ontario, Canada, which responded to a survey in 2023. METHODS: Administrators responded to questions on recruiting various health professionals, their involvement in the retirement home, support available, documentation in the home, and availability of palliative care. We reported absolute and relative proportions for survey items. We used regression analysis to assess if there is a statistically significant difference in the proportion of patients accessing care from the community in homes with and without a recruited medical service provider. RESULTS: Fifty-four (61.4%) of homes had a medical service provider, primarily an attending medical doctor. Attending medical doctors cared for more than 50 patients in 36% of homes, and 46% visited homes weekly. Administrators reported that medical providers spent most of the time providing appointments, responding to phone calls and faxes, conducting medication reviews, and discussing with residents' families. Nearly two-thirds of homes had nurses accompany physicians on rounds and provided medical service providers with clinic space and equipment. Two-thirds of homes provided residents with palliative care, primarily through community support. Residents of homes with a recruited medical service provider had 76% lower odds of seeking care from their physician in the community than those without a recruited provider (P < .001). CONCLUSIONS AND IMPLICATIONS: Our findings describe high variability in recruiting medical service providers in assisted living homes and their practice characteristics. Residents may benefit from on-site accessible and patient-centered medical care. This study provides contextual information to inform future research on assisted living in Ontario and enables policy comparisons to other provinces and countries.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".