Multifaceted intervention to optimize antibiotic use for intra-abdominal infections
Bibliographic record
Abstract
OBJECTIVES: Implementing evidence-based practice guidelines is challenging. We used a multifaceted, continuous educational approach to disseminate an up-to-date internal guideline adapted from published guidelines for management of intra-abdominal infections (IAI). PATIENTS AND METHODS: The intervention consisted of continuing educational sessions, internal guideline pocket cards and posters with collaboration among all key stakeholders starting in December 2010. We emphasized risk stratification and the use of ceftriaxone/metronidazole for treatment of low-risk IAI, and discouraged the use of fluoroquinolones due to the high local resistance rates. We then compared patients with IAI before the intervention (April-November 2010) to those after implementation of the guideline (April-November 2011) in a surgical unit at a tertiary care teaching hospital in Hamilton, Ontario, Canada. Antibiotic use was measured in in-hospital days of antibiotic therapy (DOT) per 1000 patient days (PD). RESULTS: 152 and 145 patients with IAI were included in the pre- and post-intervention periods, respectively. There was a significant reduction in the proportion of patients who received ciprofloxacin therapy from 74% to 34% (OR 0.18, 95% CI 0.11-0.31) and in DOT/1000 PD from 221 to 74 (OR 0.3, 95% CI 0.2-0.3). Also, a reduction in the DOT/1000 PD for piperacillin/tazobactam was seen (from 116 to 67; OR 0.6, 95% CI 0.5-0.7). There was an increase in the use of ceftriaxone from 1.3% to 53% of patients (OR 85, 95% CI 20-515) and from 6 to 92 DOT/1000 PD (OR 17, 95% CI 10-25). This change in practice was sustained over >2 years since the end of the active intervention, as shown in the unit-wide antimicrobial utilization data. CONCLUSIONS: A multifaceted intervention aimed at all key stakeholders resulted in a high adherence to evidence-based treatment guidelines for IAI and has initiated a sustained culture change in prescribing of antibiotics.
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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".