Vancomycin-resistant enterococci (VRE) screening and isolation in the general medicine ward: a cost-effectiveness analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Vancomycin-resistant enterococci (VRE) are a serious antimicrobial resistant threat in the healthcare setting. We assessed the cost-effectiveness of VRE screening and isolation for patients at high-risk for colonisation on a general medicine ward compared to no VRE screening and isolation from the healthcare payer perspective. Methods: We developed a microsimulation model using local data and VRE literature, to simulate a 20-bed general medicine ward at a tertiary-care hospital with up to 1000 admissions, approximating 1 year. Primary outcomes were accrued over the patient's lifetime, discounted at 1.5%, and included expected health outcomes (VRE colonisations, VRE infections, VRE-related bacteremia, and deaths subsequent to VRE infection), quality-adjusted life years (QALYs), healthcare costs, and incremental cost-effectiveness ratio (ICER). Probabilistic sensitivity analysis (PSA) and scenario analyses were conducted to assess parameter uncertainty. Results: In our base-case analysis, VRE screening and isolation prevented six healthcare-associated VRE colonisations per 1000 admissions (6/1000), 0.6/1000 VRE-related infections, 0.2/1000 VRE-related bacteremia, and 0.1/1000 deaths subsequent to VRE infection. VRE screening and isolation accrued 0.0142 incremental QALYs at an incremental cost of $112, affording an ICER of $7850 per QALY. VRE screening and isolation practice was more likely to be cost-effective (> 50%) at a cost-effectiveness threshold of $50,000/QALY. Stochasticity (randomness) had a significant impact on the cost-effectiveness. Conclusion: VRE screening and isolation can be cost-effective in majority of model simulations at commonly used cost-effectiveness thresholds, and is likely economically attractive in general medicine settings. Our findings strengthen the understanding of VRE prevention strategies and are of importance to hospital program planners and infection prevention and control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it