117. How Does Antimicrobial Stewardship Provider Role Affect Prospective Audit and Feedback Acceptance by the Attending Physician?
Bibliographic record
Abstract
Abstract Background Antimicrobial stewardship (AMS) teams are commonly multidisciplinary. The effect of AMS provider role on prospective audit and feedback (PAF) acceptance has previously been investigated with mixed results. PAF of restricted antimicrobials (carbapenems, linezolid, daptomycin, and tigecycline) in adult inpatients at our large Canadian academic centre has been performed since 2018. Actionable feedback is communicated via chart note plus one of a phone call, direct message, or in-person discussion with the most responsible physician of the attending team in order to optimize the prescription if deemed necessary. The objective of this study was to assess the effect of AMS provider role on PAF acceptance. Methods A 3 year retrospective review of all PAF events was undertaken. All audited prescriptions were included. Logistic regression was used to determine odds ratios for acceptance for individual AMS provider roles of pharmacist, physician, and supervised post-graduate physician trainee. Results Out of 1896 prescriptions audited, actionable feedback was provided to the most responsible physician in 731 (39%) cases. 677/731 (93%) of audited antibiotics were carbapenems. The overall acceptance rate was 82% (598/731). Acceptance rate and odds of acceptance based on AMS provider role were as follows: pharmacist alone 171/208 (82%), OR 1.04, 95% CI 0.70-1.59, physician alone 141/160 (88%), OR 1.85, 95% CI 1.12-3.20, pharmacist-physician duo 211/268 (79%), OR 0.73, 95% CI 0.50-1.07, and supervised post-graduate physician trainee 75/95 (79%), OR 0.81, 95% CI 0.48-1.41. Conclusion The overall acceptance rate was high. There was a higher odds of acceptance if an AMS physician was providing PAF alone, highlighting the importance of physician involvement. Disclosures Dima Kabbani, MD, AVIR Pharma (Grant/Research Support, Other Financial or Material Support, Speaker)Edesa Biotech (Scientific Research Study Investigator)Merck (Scientific Research Study Investigator)
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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 | 0.001 | 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".