Using positive deviance (PD) to reduce antibiotic resistant organisms: the Canadian PD project
Bibliographic record
Abstract
Four-month HA-ARO rates, the volume of alcohol hand rub and soap used, and the number of gowns and gloves used, were collected at baseline and then for 12 months prospectively. Social network mapping was conducted at the project start and end. Qualitative staff interviews were conducted at the project end. The percent change from baseline in quarterly HA-ARO rates were measured from September 2009 to December 2010. Process measures were collected and measured in a similar fashion. Of the 6 sites, 5 implemented PD as planned, while one was unable to, largely due to organizational restructuring. Three of the 5 sites sustained decreases in HA-AROs of 25%, 41.2% and 63.9%. Rates at the 4 site were unchanged, while the fifth site had a VRE outbreak, which resulted in a large increase in the overall HA-ARO rate. HA-MRSA decreased by 100% at 2 hospital sites; HA-VRE decreased by 100% at 2 sites; and HA- C. difficile decreased at 3 sites by 53%, 51.9% and 23%. The 1 site that measured hand hygiene compliance had a 53.2% rate increase. Interestingly, decreasing HA-ARO rates did not clearly correlate with the process indicators. PD has been successfully used in a number of settings facing complex problems. We have shown it to be successful in reducing HA-AROs in Canadian acute care facilities where the organizational climate allowed it to be implemented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".