Drug shortages in Canadian anesthesia: a national survey Penuries de medicaments pour l'anesthesie au Canada: une enquete de pratique nationale
Bibliographic record
Abstract
Background Canadian physicians are faced with an increasing frequency of drug shortages. We hypothesized that drug shortages have a clinical impact on anesthesia care in Canada. Methods We conducted a self-administered survey of anesthesiologists in Canada using the membership list of the Canadian Anesthesiologists’ Society. For survey development, we identified key domains, including types of drug shortages, impact on the ability of anesthesia practitioners to provide general anesthesia care, and impact on patient outcomes. We undertook assessments of face validity, clinical sensibility, and content validity. Respondents were surveyed from January-April 2012. Results Completed valid questionnaires were submitted by 1,187 respondents (61.4%), and 779 (65.7%) of respondents described a shortage of one or more anesthesia or critical care drugs. Changes in anesthesia practice resulting from drug shortages were common; 586 (49%) respondents thought they had given an inferior anesthetic, and 361 (30%) reported administering medications with which they were unfamiliar. Respondents also reported that drug shortages were, at times, responsible for changes in the conduct of patient care, with 28 (2.4%) noting cancellation or postponement of surgery and 92 (7.8%) witnessing a drug error. One hundred sixty-five (13.9%) respondents regarded drug shortages as having prolonged recovery from anesthesia, and 124 (10.5%) viewed drug shortages as resulting in an increased number of postoperative complications, such as postoperative nausea and vomiting. Interpretation Drug shortages are common in anesthetic practice in Canada. This state of affairs may have a negative effect on how anesthesiologists practice anesthesia and may be associated with adverse patient outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".