Barriers and Facilitators to the Implementation of a Decolonization Strategy for Staphylococcus aureus prior to Hip and Knee Arthroplasty in Alberta, Canada: A multi-methods study
Bibliographic record
Abstract
Alberta recently implemented a decolonization strategy as part of the clinical care pathway prior to hip and knee replacements. The decolonization strategy includes three days of chlorohexidine gluconate (CHG) sponge baths and five days of mupirocin ointment (MO) intranasally twice daily leading up to surgery. Preoperative decolonization prior to hip and knee replacements reduces the incidence of surgical site infections (SSIs), but the effectiveness in Alberta is unknown. For a decolonization strategy to be effective, patients and clinic staff should adhere to the protocol and there should be no negative outcomes. We used multi-methods to assess the barriers and facilitators with a decolonization strategy by assessing patients and clinic staff compliance, and baseline prevalence of antimicrobial resistance (AMR) to topical antibiotics. Using qualitative methods, semi-structured interviews and focus groups were used to understand clinic adherence with decolonization. Knowledge and understanding were central to implementation. When present, knowledge and understanding acted as a facilitator, when absent or inconsistent, it was a barrier to implementation. Using descriptive surveys, we analysed patient compliance with proportions of compliance, differences with compliance in urban versus rural clinics using logistic regression, and reasons for non-compliance with frequency counts. In our analysis, CHG sponges had a greater proportion of compliance compared to MO but not when CHG sponges and MO were used together. Patients in rural clinics had increased odds of compliance with three CHG sponges than urban clinics and males had increased odds of compliance with MO in urban locations. Common reasons for non-compliance included sponges not provided, patient forgot, and surgery date moved. To assess AMR to topical antibiotics, specimens from SSIs following hip or knee arthroplasty were collected (n=81) and 43 specimens were Staphylococcus-positive. Among these specimens, coagulase-negative staphylococci isolates carried resistance genes associated with CHG (n=10) and mupirocin (n=6). Our results indicate that while a decolonization strategy in Alberta has been successfully implemented, it could benefit from improvements with clinic and patient compliance. Furthermore, the prevalence of AMR to topical antibiotics will need to be continuously monitored for changes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".