Assessment of Fever Advisory Cards (FACs) as an Initiative to Improve Febrile Neutropenia Management in a Regional Cancer Center Emergency Department
Bibliographic record
Abstract
PURPOSE: We aimed to improve the time to antibiotics (TTA) for patients treated with chemotherapy who present to the emergency department (ED) with febrile neutropenia (FN) by using standardized fever advisory cards (FACs). METHODS: Patients treated with chemotherapy who visited the ED at the Peel Regional Cancer Center in Ontario, Canada, with suspected FN were identified, before (April 2012 to March 2013) and after (October 2013 to March 2014) FAC implementation. The primary outcome of interest was TTA. Additional process measures included Canadian Triage and Acuity Scale score, time to physician assessment, and FAC compliance. Outcomes were analyzed with descriptive statistics and control charts to determine whether the change in primary measures were within statistical control over time. RESULTS: Between the pre-FAC cohort (n = 239) and post-FAC cohort (n = 69), TTA did not change significantly post-FACs (195 v 244 min, P = .09), with monthly averages demonstrating normal variation by statistical process control methodology. The introduction of FACs increased the percentage of patients with correctly assigned Canadian Triage and Acuity Scale scores (87% v 100%) but did not affect time to physician assessment. Compliance with FACs among patients was not ideal, with only 62.5% using them as intended. CONCLUSION: The distribution of FACs was associated with an improved incidence of correct FN triaging but did not demonstrate a meaningful improvement in the quality of FN management. This may be explained by FAC use among patients not being ideal. Next steps in the continued effort toward high-quality FN care include redesign of FACs, reinforcement of provider and patient education, and ED outreach.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".