The life cycle of infection prevention and antimicrobial stewardship projects and interventions: the dynamic interplay of implementation and de-implementation science (Part I of II)
Bibliographic record
Abstract
Abstract In Antimicrobial Stewardship and Infection Prevention and Control, programmatic goals often strive to achieve clinical benefit by practice change in the direction of doing less. Practically, this may include reducing the number of tests ordered, encouraging shorter and more narrow courses of antimicrobials, or discontinuing practices that are no longer contextually appropriate. Because promoting practice change in the direction of doing less is a critical aspect of day-to-day operations in Antimicrobial Stewardship and Infection Prevention and Control, the goals of this Society for Healthcare Epidemiology Research Committee White Paper are to provide a roadmap and framework for leveraging principles of implementation and de-implementation science in day-to-day practice. Part II of this series focuses on some practical case studies, including real-world examples of applied de-implementation science to promote discontinuation of practices that are ineffective, overused, or no longer effective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.003 |
| 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 | 0.001 |
| 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".