Environmental scan of infection prevention and control practices for containment of hospital-acquired infectious disease outbreaks in acute care hospital settings across Canada
Bibliographic record
Abstract
BACKGROUND: Ward closure is a method of controlling hospital-acquired infectious diseases outbreaks and is often coupled with other practices. However, the value and efficacy of ward closures remains uncertain. PURPOSE: To understand the current practices and perceptions with respect to ward closure for hospital-acquired infectious disease outbreaks in acute care hospital settings across Canada. METHODS: A Web-based environmental scan survey was developed by a team of infection prevention and control (IPC) experts and distributed to 235 IPC professionals at acute care sites across Canada. Data were analyzed using a mixed-methods approach of descriptive statistics and thematic analysis. RESULTS: A total of 110 completed responses showed that 70% of sites reported at least 1 outbreak during 2013, 44% of these sites reported the use of ward closure. Ward closure was considered an "appropriate," "sometimes appropriate," or "not appropriate" strategy to control outbreaks by 50%, 45%, and 5% of participants, respectively. System capacity issues and overall risk assessment were main factors influencing the decision to close hospital wards following an outbreak. DISCUSSION: Results suggest the use of ward closure for containment of hospital-acquired infectious disease outbreaks in Canadian acute care health settings is mixed, with outbreak control methods varying. The successful implementation of ward closure was dependent on overall support for the IPC team within hospital administration.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".