Global oncology pharmacy response to COVID-19 pandemic: Medication access and safety
Bibliographic record
Abstract
Response, action, and adaptation of the way health services are delivered will impact our ability to provide optimized and continuity of care while acting within resource constraints imposed by COVID-19. Care for patients with cancer is particularly important given increased infection rates and worse outcomes from COVID-19 in this patient population, as well as potential adverse outcomes if treatment pathways need to be compromised. In this commentary, we provide a global oncology pharmacy perspective (including both developed and developing nations) on how COVID-19 has impacted access to and delivery of cancer therapies. This perspective was prepared by the International Society of Oncology Pharmacy Practitioners, with input from national and regional oncology pharmacy practice groups (42 practice leaders from 28 countries and regions) who contributed to a snapshot survey between 10 and 22 April 2020. Specifically, we highlight challenges related to safe handling of hazardous drugs and maintaining high-quality medication safety standards that have impacted various stakeholders.
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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 | 0.007 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".