Implementation of Staphylococcus aureus decolonization in cardiac surgery
Bibliographic record
Abstract
Objective: (SA) screening and decolonization is a guideline-recommended treatment for the prevention of surgical site infections in cardiac surgery. This study aimed to formally assess the barriers and facilitators associated with its implementation. Methods: Targeted SA screening and decolonization started at our institution in November 2022. To assess barriers and facilitators to implementation, we conducted focus group interviews informed by the Consolidated Framework for Implementation Research at approximately 6 months after initiation of the intervention. We also regularly collected quantitative data on missed screening and/or decolonization to address gaps in uptake. This was reviewed at 6-month and 1-year time points. Adjustments to implementation were regularly made to address barriers. Results: At 1 year, 563 nonurgent inpatients and 232 outpatients were consulted to cardiac surgery. Ninety-five percent of the inpatients and 91% of the outpatients considered for cardiac surgery were screened appropriately. Of the patients accepted for cardiac surgery, 50% of positive inpatients underwent decolonization in the first 6 months prior to focus groups compared to 67% in the subsequent 6 months. For outpatients, 77% were decolonized in the first 6 months, compared to 79% in the subsequent 6 months. Major barriers to implementation included delays in receiving screening results, difficulty meeting screening and decolonization timelines, and staffing turnover. Conclusions: SA screening and decolonization was successfully implemented as a standard of care at our institution with the aid of an implementation science framework. By engaging care partners and healthcare staff throughout the implementation process and regularly addressing barriers, we developed a sustainable SA screening and decolonization program. Adjustments are ongoing to increase and sustain decolonization uptake.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".