Developing recommendations for the safe handling of oral anti-cancer drugs in community pharmacies: A pan-Canadian consensus approach
Bibliographic record
Abstract
PURPOSE: To create a set of consensus-based and evidence-informed recommendations to provide guidance around the safe dispensing and handling of oral anti-cancer drugs in low-volume settings unique to the community pharmacy setting. METHODS: A review of published and grey literature (published in non-commercial domains such as national organizations and associations) documents and nine key informant interviews were conducted and a modified Delphi approach was taken to achieve consensus. The final list of 47 candidate recommendations was reviewed by a task force and validated by multi-disciplinary stakeholders. A draft of the statements was circulated broadly within the community pharmacy community in an effort to assess relevance and implementation feasibility. RESULTS: The final report included 44 recommendations that addressed 11 key areas germane to the safe handling of oral anti-cancer drugs in community pharmacies. Mean agreement increased from 70% to 95%. Early feedback from community pharmacy leaders during the external review suggests that many of the proposed recommendations can be feasibly implemented within a reasonable timeframe when released with appropriate education and resource materials. CONCLUSIONS: A modified-Delphi approach supplemented by key informant interviews and a comprehensive external review resulted in a set of evidence-informed, community-driven recommendations for community pharmacies. The recommendations address a gap in existing literature to improve understanding of the risks associated with handling and dispensing oral anti-cancer drugs for both community pharmacy staff and management and offer mitigating strategies to reduce those risks. Incorporating feasibility assessment actions early (through the key informant interviews) and late (through the external review) ensures recommendations are grounded in practicality and support broad and early knowledge translation strategies.
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.
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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".