The association of facility ownership with COVID-19 outbreaks in long-term care homes in British Columbia, Canada: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Long-term care (LTC) in Canada is delivered by a mix of government-, for-profit- and nonprofit-owned facilities that receive public funding to provide care, and were sites of major outbreaks during the early stages of the COVID-19 pandemic. We sought to assess whether facility ownership was associated with COVID-19 outbreaks among LTC facilities in British Columbia, Canada. METHODS: We conducted a retrospective observational study in which we linked LTC facility data, collected annually by the Office of the Seniors Advocate BC, with public health data on outbreaks. A facility outbreak was recorded when 1 or more residents tested positive for SARS-CoV-2 between Mar. 1, 2020, and Jan. 31, 2021. We used the Cox proportional hazards method to calculate the adjusted hazard ratio (HR) of the association between risk of COVID-19 outbreak and facility ownership, controlling for community incidence of COVID-19 and other facility characteristics. RESULTS: Overall, 94 outbreaks involved residents in 80 of 293 facilities. Compared with health authority-owned facilities, for-profit and nonprofit facilities had higher risks of COVID-19 outbreaks (adjusted HR 1.99, 95% confidence interval [CI] 1.12-3.52 and adjusted HR 1.84, 95% CI 1.00-3.36, respectively). The model adjusted for community incidence of infection (adjusted HR 1.12, 95% CI 1.07-1.17), total nursing hours per resident-day (adjusted HR 0.84, 95% CI 0.33-2.14), facility age (adjusted HR 1.01, 95% CI 1.00-1.02), number of facility beds (adjusted HR 1.20, 95% CI 1.12-1.30) and facilities with beds in shared rooms (adjusted HR 1.16, 95% CI 0.73-1.85). INTERPRETATION: Findings suggest that ownership of LTC facilities by health authorities in BC offered some protection against COVID-19 outbreaks. Further study is needed to unpack the underlying pathways behind this observed association.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".