Embracing Handshake Stewardship: Utility of Collaborative, Prospective Audit and Feedback Rounds in an Intensive Care Unit at Royal University Hospital, Saskatoon, Saskatchewan
Bibliographic record
Abstract
Up to 50% of antimicrobial use in hospitals has been shown to be inappropriate and is associated with the development of antimicrobial resistance, prolonged hospital stay, as well as increased rates of Clostridium difficile infection and patient mortality. Prospective audit and feedback is a core strategy of antimicrobial stewardship programs (ASP) with relevance in intensive care units given large volumes of antimicrobial use and higher proportion of broad-spectrum antimicrobial usage. Introduction of collaborative, prospective audit and feedback rounds as part of a novel antimicrobial stewardship program can be used to optimize antimicrobial usage and quality of patient care. Collaborative, prospective audit and feedback rounds were performed three times per week in a 17-bed intensive care unit at Royal University Hospital, Saskatoon, Saskatchewan. Antimicrobial utilization was collected in monthly intervals during baseline and intervention periods and reported in daily defined doses per thousand patient days; antimicrobials were categorized on a five-point ordinal scale according to agent spectrum. ASP recommendations were recorded prospectively in themed categories. An anonymous survey of intensivists was also performed to determine their attitudes and perceptions towards ASP. One hundred seventy-eight patients were reviewed by ASP during a five-month intervention period. The most common recommendations included duration optimization (27.7%), de-escalation of therapy (25.9%) and discontinuation of therapy (17.0%), with an overall acceptance rate of 92.0%. While there was no significant change in overall antimicrobial usage, broad-spectrum antimicrobial usage decreased by 28.6% (P = 0.05) and narrow-spectrum antimicrobial usage increased by 50.0% (P < 0.001). Implementation of collaborative, prospective audit and feedback rounds was widely accepted amongst intensivists as an effective strategy to improve quality of patient care. Collaborative, prospective audit and feedback rounds are an effective ASP strategy that encourages bi-directional exchange of information and education to optimize antimicrobial usage in an intensive care unit. All authors: No reported disclosures.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".