Prescribing practices of oncology pharmacists working in ambulatory cancer centers in Alberta
Bibliographic record
Abstract
OBJECTIVE: To describe and quantify independent prescribing of oncology pharmacists working in adult, ambulatory cancer centers in Alberta, Canada. METHODS: was conducted. Prescriptions from January 1, 2018 to June 30, 2018 were analyzed. Descriptive statistics were used to quantify prescription volume and class of medications prescribed. A cross-sectional analysis was then performed on a random sample to determine the type of prescription intervention and evaluate pharmacist documentation. RESULTS: Over 6 months, 3474 prescriptions were ordered by 33 clinically deployed pharmacists. The median number of medications prescribed was 7 per month (interquartile range: 1.50-27.00; Range: 0.17-79.5). When prescribing was standardized by pharmacist's time clinically deployed, the median was 21.67 (interquartile range: 5.00-79.67; range: 0.67-216.67) prescriptions per month per full-time equivalent. The most prescribed class of medication was antiemetic (24.1%). From a sample of 346 prescriptions, 172 (50%) were new medications initiated, 160 (46%) were the continuation of existing prescriptions and 14 (4%) were prescription dosage adjustments. Adherence to the specified documentation standards was 47%. CONCLUSIONS: Oncology pharmacists utilize their independent prescribing to initiate and continue supportive care medications for cancer patients. The prescribing volume varied greatly among pharmacists. Opportunities exist to further engage pharmacist prescribing.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".