Evaluating a pilot, structured, face-to-face, antimicrobial stewardship, prospective audit-and-feedback program in emergency general surgery service in a community hospital
Bibliographic record
Abstract
Abstract Background: Prospective audit and feedback (PAF) is an established practice in critical care settings but not in surgical populations. We pilot-tested a structured face-to-face PAF program for our acute-care surgery (ACS) service. Methods: This was a mixed-methods study. For the quantitative analysis, the structured PAF period was from August 1, 2017, to April 30, 2019. The ad hoc PAF period was from May 1, 2019, to January 31, 2021. Interrupted time-series segmented negative binomial regression analysis was used to evaluate change in antimicrobial usage measured in days of therapy per 1,000 patient days for all systemic and targeted antimicrobials. Secondary outcomes included C. difficile infections, length of stay and readmission within 30 days. Each secondary outcome was analyzed using a logistic regression or negative binomial regression model. For the qualitative analyses, all ACS surgeons and trainees from November 23, 2015, to April 30, 2019, were invited to participate in an email-based anonymous survey developed using implementation science principles. Responses were measured using counts. Results: In total, 776 ACS patients were included in the structured PAF period and 783 patients were included in the in ad hoc PAF period. No significant changes in level or trend for antimicrobial usage were detected for all and targeted antimicrobials. Similarly, no significant differences were detected for secondary outcomes. The survey response rate was 25% (n = 10). Moreover, 50% agreed that PAF provided them with skills to use antimicrobials more judiciously, and 80% agreed that PAF improved the quality of antimicrobial treatment for their patients. Conclusion: Structured PAF showed clinical outcomes similar to ad hoc PAF. Structured PAF was well received and was perceived as beneficial by surgical staff.
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.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".