Patient-Specific Blister Packaging of Medications in the Oncology Camp Setting: Optimizing Medication Safety and Dispensing Processes
Bibliographic record
Abstract
Background: Safe medication delivery is an essential component of medical care in the overnight summer camp setting, especially for children with cancer and medical complexity. Blister packaging of medications is a method that may improve safety in this setting. Method: In this quality improvement project, we implemented and evaluated a system of on-site blister packaging of medications with the goal of optimizing the safety and efficiency of medication delivery at a large overnight summer camp for children with cancer. Data for the number and types of medications delivered and medication errors were described in the summer sessions prior to and post this implementation. Quantitative and qualitative clinician feedback was collected. Results: In the summer of 2023, there were 551 campers, 342 (62%) of whom received at least one medication and with the number of medications per child ranging from 0 to 18. There were 70/551 (20%) of campers who received high-risk medications defined as oral antineoplastic therapy and controlled substances. The frequency of medication errors was very low across all summer sessions. The mean number of errors in the preimplementation period was 1/1,000 errors per medication dispensed (0.1%), whereas in the postimplementation period, it was 0.4/1,000 (0.04%). In postcamp survey, qualitative responses from medical staff described that they perceived blister packaging of medications to improve safety and decrease workload. Discussion: The implementation of on-site blister packaging of medications is a feasible system for optimizing medication safety and delivery in an overnight camp for children with cancer.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".