Exploring obstacles to proper timing of prophylactic antibiotics for surgical site infections
Bibliographic record
Abstract
BACKGROUND: Surgical site infections remain one of the leading types of nosocomial infections. The administration of prophylactic antibiotics within a specific interval has been shown to reduce the burden of surgical site infections, but adherence to proper timing guidelines remains problematic. This study examined perceived obstacles to the use of evidence-based guidelines for the timely administration of prophylactic antibiotics to prevent surgical site infections. METHODS: 27 semi-structured interviews were conducted with anesthesiologists (n = 12), surgeons (n = 11), and perioperative administrators (n = 4) in two large academic hospitals to elicit their perceptions of the factors that prevent the timely administration of prophylactic antibiotics. Using a grounded theory approach, transcripts were analyzed for recurrent themes. RESULTS: Despite having knowledge of guidelines, participants perceived consistent failure in the proper timing of antibiotic administration. Thematic analysis revealed a number of obstacles to the observance of guidelines including: (1) low priority, (2) inconvenience, (3) workflow, (4) organizational communication, and (5) role perception. Workflow and role perception were the dominant obstacles. CONCLUSION: This study suggests that proper antibiotic timing is thwarted by significant obstacles. The gap between evidence-based guidelines and practice is populated by individual values, professional conflicts, and organizational conflicts which must be addressed in order to achieve optimal practice in this domain. Using group interviews to reveal these factors to team members and managers may be a first step to resolving the gap and reducing surgical site infections.
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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 | 0.001 | 0.001 |
| 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".