Use of ward closure to control outbreaks among hospitalized patients in acute care settings: a systematic review
Bibliographic record
Abstract
BACKGROUND: Though often used to control outbreaks, the efficacy of ward closure is unclear. This systematic review sought to identify studies defining and describing ward closure in outbreak control and to determine impact of ward closure as an intervention on outbreak containment. METHODS: We searched these databases with no language restrictions: MEDLINE, 1946 to 7 July 2014; EMBASE, 1974 to 7 July 2014; CINAHL, 1937 to 8 July 2014; and Cochrane Database of Systematic Reviews, 2005 to May 2014. We also searched the following: IndMED; LILACS; reference lists from retrieved articles; conference proceedings; and websites of the CDCP, the ICID, and the WHO. We included studies of patients hospitalized in acute care facilities; used ward closure as a control measure; used other control measures; and discussed control of the outbreak(s) under investigation. A component approach was used to assess study quality. RESULTS: We included 97 English and non-English observational studies. None included a controlled comparison between ward closure and other interventions. We found that ward closure was often used as part of a bundle of interventions but could not determine its direct impact separate from all the other interventions whether used in parallel or in sequence with other interventions. We also found no universal definition of ward closure which was widely accepted. CONCLUSIONS: With no published controlled studies identified, ward closure for control of outbreaks remains an intervention that is not evidence based and healthcare personnel will need to continue to balance the competing risks associated with its use, taking into consideration the nature of the outbreak, the type of pathogen and its virulence, mode of transmission, and the setting in which it occurs. Our review has identified a major research gap in this area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.037 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".