Oncology medication safety: A 3D status report 2008
Bibliographic record
Abstract
BACKGROUND: The safe use of medications is a major concern in oncology practice. Three organizations collaborated on a survey to determine if practitioners had implemented current recommended safe practices for IV vincristine administration, general oncology safe practices, and safe practices for oral chemotherapy. METHODS: A survey was distributed to members of the Hematology Oncology Pharmacy Association (HOPA) and the International Society of Pharmacy Practitioners (ISOPP) using Survey Monkey. The Institute of Safe Medication Practices (ISMP) also solicited readers of its Medication Safety Alert! to respond to the survey. A comparison to results from a survey conducted by ISMP in 2006 on safe practices for IV vincristine was also conducted. RESULTS: The majority of respondents were aware of the WHO recommendations for IV vincristine, although the rate of implementation of the guidelines ranged from 24.1 to 53.6%. When compared to the ISMP 2006 survey there was a 25.8-37.4% improvement in following many of the safe practice guidelines. Administering IV vincristine via a minibag showed the lowest rate of adoption (less than 40%). Of the 35 survey items on general chemotherapy safety strategies, 80% of respondents had implemented at least 21 items in the survey. Overall 32.4% of respondents did not consider oral chemotherapy as requiring the same safety concerns as parenteral therapy. CONCLUSIONS: The results of this survey will provide a new baseline for the adoption rate of safe medication practice recommendations related to oncology. Further work on addressing barriers in adopting identified safe practice recommendations needs to be conducted.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.019 |
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".