Incidence and type of voluntary reported perianesthetic medication errors in community veterinary clinics in Calgary, Canada
Bibliographic record
Abstract
OBJECTIVE: To collect medication error (ME) data during the perianesthetic period from small animal clinics. SAMPLE: 6 small animal general practice veterinary clinics. METHODS: Small animal general practice veterinary clinics were recruited in this prospective observational study, with staff given a presentation on medical errors and instructed on how to submit medication error reports to an online reporting system. Errors were classified according to type and timing. RESULTS: A total of 2,728 general anesthesia or sedation procedures were performed, with 49 ME reports submitted. One duplicated report of the same error was excluded, resulting in a ME rate of 1.8%. Most reports (69% [33/48]) were near misses. The remaining 31% were MEs that reached the patient but did not cause harm. Wrong dose errors were the most common type (63% [30/48]), of which 80% (24/30) were calculation errors. Premedication/sedation and maintenance were the most reported stages, at 47% (20/43) and 23% (10/43), respectively. None of the MEs reported resulted in an adverse event, with an approximately 2:1 ratio of near-miss to no-harm MEs. The observed patterns of MEs reported, including type and timing, represent a target for further education. CLINICAL RELEVANCE: These results quantify the ME rate in general practice veterinary clinics, providing an initial benchmark for MEs during the perianesthetic period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".