Undocumented drug utilization and drug waste increase costs of pediatric anesthesia care
Bibliographic record
Abstract
The present study was performed in order to identify the cost of drugs used without documenting them in the patients' file and the wastage of drugs in a pediatric anesthesiology ward. In a prospective, blinded, observational design, drug utilization of 610 consecutive patients, undergoing an elective or emergency surgical procedure was evaluated. The number of undocumented drugs per 100 requested units and the number of wasted drugs per 100 requested units were computed and multiplied by its corresponding unitary cost. The median undocumented cost was 92.4 US dollars (95% CI 17.2-216.6 dollars) per 100 requested units. Succinylcholine (40 mg/2 mL) was the main undocumented drug; its use was not documented in approximately 50% cases in which this neuromuscular blocking agent was requested. However, rocuronium and nalbuphine had the highest unjustified cost, 770.6 dollars and 847.0 dollars per 100 requested units, respectively. Ketorolac, diclofenac, metamizol, furosemide, methylprednisolone, sodium bicarbonate, and cisatracurium were requested and documented. The median cost of wasted drug was 141.8 dollars (95% CI 55.8-448.2 dollars) per 100 requested drugs. More than 80% of adrenaline, naloxone, flunitrazepam, ephedrine, and cisatracurium were wasted. However, the highest cost of wasted drugs was for ondansetron, cisatracurium, methylprednisolone, and rocuronium. The uncontrolled availability and use of drugs may represent an important amount of resources wasted without any awareness of the staff in a department of pediatric 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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".