United States Pharmacopeia (USP) <800> Standards: Increasing Compliance of Safe Handling and Proper Administration of USP General Chapter <800> Drugs
Bibliographic record
Abstract
Problem: United States Pharmacopeia (USP) developed a set of standards to minimize exposure risks to patients, healthcare workers, and the environment when preparing, handling, and administering hazardous drugs (HDs) known as USP <800> HDs. The guidelines became effective December 1, 2019, but additional information is needed to ensure healthcare personnel are complying with the standards. Context: Two medical surgical units from Hospital A were included in this project. Currently mandatory online modules about USP <800> standards are provided annually to every healthcare worker, but it is unknown if the policies and procedures are being followed appropriately. Interventions: Active and passive observations as well as inspections were used to compile data regarding the compliance of USP <800> standards of both healthcare workers and within the hospital setting. Surveys were conducted through informal ‘elbow-to-elbow’ interviews with hospital employees, primarily nurses, to collect subjective evidence. Measures: The measures can be divided into two categories: personnel and atmosphere compliance. Measures to determine personnel compliance include determining a current level of knowledge and comfortability, collecting self-reported compliance to the standards, and observing personal protective equipment (PPE) donning and doffing techniques. Atmosphere compliances are measured by calculating the total number of patients taking USP <800> HDs, evaluating the accuracy and efficiency of notifications in the electronic health record (EHR), documenting the frequency of correctly displayed signage on patient doors, and assessing supplies located on USP <800> carts. Results: Nurses self-reported a high level of knowledge and comfortability regarding safe handling and administration practices of USP <800> HDs. However, despite over a quarter of the patients being on at least one USP <800> drug, compliance with proper PPE recommendations, signage, and accessibility of supplies was low. Conclusions: This project determined that healthcare employees at Hospital A are not consistently following the recommended USP <800> standards. It also provided a baseline knowledge for future education to ensure safety of patients, healthcare employees, and the environment.
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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 | 0.017 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".