<em>Clostridium difficile</em> Outbreak: A Small Group of Pharmacists Makes a Big Impact
Bibliographic record
Abstract
INTRODUCTIONHospitals all over Canada are realizing that Clostridium difficile can kill. The Royal Victoria Hospital in Barrie, Ontario, declared a C. difficile outbreak on February 23, 2007, after 39 new cases of C. difficile–associated disease (CDAD) were identified since the start of the year. Before this period, the baseline monthly incidence of hospital-acquired CDAD at this institution had been about 8. A subsequent external chart audit of 31 cases from September 2006 to February 2007 concluded that C. difficile had hastened or had been the primary factor in the deaths of 7 patients at the hospital and had been a contributing factor in 11 more deaths.1 In response to the outbreak, the Royal Victoria Hospital implemented a 50-point action plan, which included increasing infection control measures, such as enhancing cleaning practices, hand hygiene, and isolation precautions; extensive staff and patient education; and intensive review of antibiotic therapy for all patients at high risk of CDAD. The purpose of this paper is to describe how the pharmacy department at the Royal Victoria Hospital responded to the challenge of the outbreak, in particular by developing a program to help reduce the rate of CDAD within the hospital. Despite a reduced complement of pharmacists and minimal clinical presence on the patient care units, the pharmacy department designed and implemented clinical decision support tools, provided education, and promoted antibiotic stewardship to minimize the risk of CDAD. The leadership and clinical expertise of the pharmacy department contributed to a reduction in new cases of nosocomial CDAD at the hospital and raised awareness about the pressing nature of C. difficile infection.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".