Patient needs and resource intensity weighting in the ambulatory care unit
Bibliographic record
Abstract
Across British Columbia Cancer (BC Cancer), oncology nurses work as part of an interdisciplinary team in the outpatient ambulatory care unit (ACU) and support patients across the trajectory of their cancer journey. Previous initiatives, which focused on identifying patient needs and nursing role optimization work, have enhanced role clarity, enabling nurses to articulate their scope of practice and specialty competencies required to best meet the needs of patients and families. However, while the patient needs and fundamental practice elements have been identified to optimize the ACU nursing role, a gap still exists in quantifying the staffing resources required to operationalize the current model of care. To address this gap, a quality improvement project was initiated to develop an internally validated ACU Nursing Resource Intensity Weighting (RIW) tool for projecting baseline staffing requirements. The tool can be utilized to inform strategic and operational planning discussions focused on improving the outpatient model of care in oncology.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".