Improving infection prevention practices through a novel safety coaches program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Healthcare-associated infections (HAIs) contribute to extended hospital stays and heightened in-hospital mortality rates. Effective infection prevention and control (IPAC) strategies are crucial for curtailing infection rates. The COVID-19 pandemic amplified disease burdens, compelling rigorous preventative measures. Mackenzie Health introduced the IPAC Safety Coaches Program to bolster adherence to IPAC guidelines and mitigate HAIs. Methods: IPAC Safety Coach training transpired over three iterative cohorts of educational sessions. Each session comprised a review of new learning material, discussion of key topics, and mandatory action items. Primary outcomes focused on hand hygiene and proper donning/doffing of personal protective equipment (PPE). Secondary outcomes focused on Clostridioides difficile (C. difficile) and central line associated bloodstream infection (CLABSI) rates. Data were collected using a standardized audit reporting form. Results: Across three training cohorts, improvements were noted in key compliance metrics: hand hygiene compliance improved by 9%, approaching statistical significance. Significant improvements were observed in PPE donning (19%), and PPE doffing (17%) compliance. Secondary outcomes demonstrated substantial reductions in C. difficile (55%) and CLABSI (57%) rates across the three cohorts. Conclusion: The novel IPAC Safety Coach Program led to improvements in hand hygiene, PPE donning and doffing compliance, and contributed to reduced C. difficile and CLABSI infection rates.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it