A modified Delphi to define drug dosing errors in pediatric critical care
Bibliographic record
Abstract
BACKGROUND: There is no globally accepted definition for dosing error in adult or pediatric practice. The definition of pediatric dosing error varies greatly in the literature. The objective of this study was to develop a framework, informed by a set of principles, for a clinician-based definition of drug dosing errors in critically ill children, and to identify the range that practitioners agree is a dosing error for different drug classes and clinical scenarios. METHODS: We conducted a nationwide three staged modified Delphi from May to December 2019. Expert clinicians included Canadian pediatric intensive care unit (PICU) physicians, pharmacists and nurses, with a least 5 years' experience. Outcomes were underlying principles of drug dosing, and error thresholds, as defined by proportion above and below reference range, for common PICU medications and clinical scenarios. RESULTS: Forty-four participants met eligibility, and response rates were 95, 86 and 84% for all three rounds respectively. Consensus was achieved for 13 of 15 principles, and 23 of 30 error thresholds. An over-dosed drug that is intercepted, an under-dose of a possibly life-saving medication, dosing 50% above or below target range and not adjusting for a drug interaction were agreed principles of dosing error. Altough there remained much uncertainty in defining dosing error, expert clinicians agreed that, for most medication categories and clinical scenarios, dosing over or below 10% of reference range was considered an error threshold. CONCLUSION: Dosing principles and threshold are complex in pediatric critical care, and expert clinicians were uncertain about whether many scenarios were considered in error. For most intermittent medications, dosing over 10% below or above reference range was considered a dosing error, although this was largely influenced by clinical context and drug properties. This consensus driven error threshold will help guide routine clinical dosing practice, standardized reporting and drug quality improvement in pediatric critical care.
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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 | 0.134 | 0.109 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".