Systematic evaluation of errors occurring during the preparation of intravenous medication
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Errors in the concentration of intravenous medications are not uncommon. We evaluated steps in the infusion-preparation process to identify factors associated with preventable medication errors. METHODS: We included 118 health care professionals who would be involved in the preparation of intravenous medication infusions as part of their regular clinical activities. Participants performed 5 infusion-preparation tasks (drug-volume calculation, rounding, volume measurement, dose-volume calculation, mixing) and prepared 4 morphine infusions to specified concentrations. The primary outcome was the occurrence of error (deviation of > 5% for volume measurement and > 10% for other measures). The secondary outcome was the magnitude of error. RESULTS: Participants performed 1180 drug-volume calculations, 1180 rounding calculations and made 1767 syringe-volume measurements, and they prepared 464 morphine infusions. We detected errors in 58 (4.9%, 95% confidence interval [CI] 3.7% to 6.2%) drug-volume calculations, 30 (2.5%, 95% CI 1.6% to 3.4%) rounding calculations and 29 (1.6%, 95% CI 1.1% to 2.2%) volume measurements. We found 7 errors (1.6%, 95% CI 0.4% to 2.7%) in drug mixing. Of the 464 infusion preparations, 161 (34.7%, 95% CI 30.4% to 39%) contained concentration errors. Calculator use was associated with fewer errors in dose-volume calculations (4% v. 10%, p = 0.001). Four factors were positively associated with the occurrence of a concentration error: fewer infusions prepared in the previous week (p = 0.007), increased number of years of professional experience (p = 0.01), the use of the more concentrated stock solution (p < 0.001) and the preparation of smaller dose volumes (p < 0.001). Larger magnitude errors were associated with fewer hours of sleep in the previous 24 hours (p = 0.02), the use of more concentrated solutions (p < 0.001) and preparation of smaller infusion doses (p < 0.001). INTERPRETATION: Our data suggest that the reduction of provider fatigue and production of pediatric-strength solutions or industry-prepared infusions may reduce medication errors.
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.
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 | 0.030 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it