Expanding the role of clinical pharmacists in community oncology practice results of implementation at the Jack ady Cancer Clinic
Bibliographic record
Abstract
Increasing demand for cancer care services in the community setting is putting pressure on ambulatory cancer clinics to become more productive and efficient. Limited numbers of medical oncologists means that other healthcare professionals must work to their full scope of practice to enable oncologists to focus on activities only they can undertake. Oncology pharmacists have the potential to assume a greater role in patient care as part of multidisciplinary teams in the community setting. This study evaluates a pilot project undertaken at the Jack Ady Cancer Clinic (JACC) in Alberta to implement an expanded pharmacist role that included direct interaction with patients and greater integration into the care team. The primary objective was to improve use and results of antiemetics for patients undergoing cancer chemotherapy. One-year results of the nonrandomized study found that the new pharmacist role had a positive impact on the incidence and severity of chemotherapy-induced nausea and vomiting (CINV). The acceptability and sustainability of the increased pharmacist role were further assessed through workload analysis, as well as team member and patient surveys, and showed overwhelmingly positive reception of the new role by clinicians and patients. Results strongly support the benefits of an expanded role for clinical pharmacy services. Further research is needed on the impact of the expanded clinical pharmacist role on specific patient outcomes, continuity of care and costeffectiveness. 1,2,3
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".