Beat Those Bugs! Implementing contact precautions in community dialysis units for closer-to-home care.
Bibliographic record
Abstract
"Beat Those Bugs!" was the call to action for the Providence Health Care Renal and Infection Prevention and Control programs to provide closer-to-home care in community dialysis units, for hemodialysis patients positive for the antibiotic-resistant organisms, Methicillin-Resistant Staphylococcus aureus and Vancomycin-Resistant Enterococcus. The initiative assessed barriers and facilitators to: implementing Contact Precautions; developing practice standards for nurses and renal technicians to enact Contact Precautions care; providing staff and patient education essential to implementing these standards; and, securing environmental and equipment supports required for Contact Precautions care. Through the "Beat Those Bugs!" initiative, all six Providence Health Care Community Dialysis Units have the capacity to provide Standard/ Routine as well as Contact Precautions care enabling patients to receive closer-to-home care in their home communities regardless of their antibiotic-resistant microorganism status. Program evaluation (based on annual screening) demonstrates that the "Beat Those Bugs!" program is an effective model for safe, evidence-based and ethical care in the hemodialysis setting.
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 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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.005 |
| 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".