Medication administration errors during general anesthesia – a systematic review of prospective studies
Bibliographic record
Abstract
Abstract Introduction The incidence of medication error in anesthesia can be variable among different studies likely due to recall bias in retrospective studies. In prospective survey studies, questionnaires are sent to anesthesia care providers to facilitate self-reports of medication errors during a pre-planned follow-up period. This systematic review investigates all prospective survey studies of medication errors in adult patients undergoing general anesthesia. Our objective is to identify the incidence and characteristics of the common medication errors during general anesthesia. We also want to determine the contributing factors and outcomes of these errors. Methods We conducted database searches of Embase and Medline for medication errors in anesthesia between 1980 to 2019 and 2020 to 2021. Ten prospective survey studies detailing medication errors involving adult patients under general anesthesia were included. Data on response rate, incidence of errors, types of error and medications, patient outcomes, and contributing factors were collected. Results Ten studies were included of which six studies provided a response rate ranging from 53% to 97.5%. The incidence of medication errors ranged from 0.02% to 1.12% or 1 in every 90 to 5000 anesthetics. A total of 1,676 medication errors during general anesthesia were analyzed. The most reported error was the substitution error (31.6% [530/1676]), followed by incorrect dose (28.4% [476/1676]). The class of medication most associated with administration errors were muscle relaxants, opioids, and antibiotics. Most patient outcomes were of no harm. Inexperience of the anesthesiologist, nurse or student was the most reported contributing factor, followed by haste or pressure to proceed, and communication problems. Conclusion The incidence of medication errors during general anesthesia were as high as 1.12% and the most common errors were substitution error and incorrect dose. Inexperience, time pressure, and communication problems were contributing factors. This information can be used to inform safety practices in anesthesia.
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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 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.021 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".