Economic evaluation of vancomycin-resistant enterococci (VRE) control practices: a systematic review
Bibliographic record
Abstract
Preventing vancomycin-resistant enterococci (VRE) infection is a healthcare priority. However, the cost-effectiveness of VRE control interventions is unclear. The aim of this study was to synthesize evidence on economic evaluation of VRE control practices such as screening, contact precautions, patient cohorting, and others. The literature was searched from January 1985 to June 2018, and included economic evaluations of VRE control practices in hospital settings, published in English. A total of 4711 articles were screened; nine primary studies met our criteria. All studies evaluated some form of VRE screening and contact precautions, in populations ranging from single hospital wards (or select patient groups) to multiple healthcare facilities. There was significant variability in the interventions and comparisons used. Most studies (N = 7) conducted a cost-effectiveness analysis; two studies were cost-consequence studies. All economic evaluations were from the hospital perspective. Four studies found implementing enhanced VRE-specific control practices to be cost-effective/cost-saving and two studies found that discontinuing VRE-specific control practices was not cost-effective. Three studies found decreasing VRE-specific control practices to be cost-effective/cost-saving. The quality of the included studies was generally low according to the Joanna Briggs Institute (JBI) checklist for economic evaluations; major limitations included risks of bias in intervention effect estimates, and a lack of sensitivity analyses. Most studies show that some form of VRE screening and use of Contact Precautions is cost-effective. The low study quality and heterogeneity of interventions and comparators precludes definitive conclusions about the cost effectiveness of specific VRE control interventions. Additional high-quality economic evaluations are needed to strengthen the available evidence.
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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 | 0.014 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".