An environmental scan of visitation policies in Canadian intensive care units during the first wave of the COVID-19 pandemic
Bibliographic record
Abstract
PURPOSE: In response to the rapid spread of SARS-CoV-2, hospitals in Canada enacted temporary visitor restrictions to limit the spread of COVID-19 and preserve personal protective equipment supplies. This study describes the extent, variation, and fluctuation of Canadian adult intensive care unit (ICU) visitation policies before and during the first wave of the COVID-19 pandemic. METHODS: We conducted an environmental scan of Canadian hospital visitation policies throughout the first wave of the pandemic. We conducted a two-phased study analyzing both quantitative and qualitative data. RESULTS: We collected 257 documents with reference to visitation policies (preCOVID, 101 [39%]; midCOVID, 71 [28%]; and lateCOVID, 85 [33%]). Of these 257 documents, 38 (15%) were ICU-specific and 70 (27%) referenced the ICU. Most policies during the midCOVID/lateCOVID pandemic period allowed no visitors with specific exceptions (e.g., end-of-life). Framework analysis revealed five overarching themes: 1) reasons for restricted visitation policies; 2) visitation policies and expectations; 3) exceptions to visitation policy; 4) patient and family-centred care; and 5) communication and transparency. CONCLUSIONS: During the first wave of the COVID-19 pandemic, most Canadian hospitals had public-facing visitor restriction policies with specific exception categories, most commonly for patients at end-of-life, patients requiring assistance, or COVID-19 positive patients (varying from not allowed to case-by-case). Further studies are needed to understand the consistency with which visitation policies were operationalized and how they may have impacted patient- and family-centred 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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".