Improving Pediatric Drug Safety in Prehospital Emergency Care—10 Years on
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: The Pediatric Emergency Ruler (PaedER) is a height-based drug dose recommendation tool that was reported to reduce life-threatening medication errors by 90%. The PaedER was introduced into the Cologne Emergency Medical Service (EMS) in 2008 along with educational measures, publications, and lectures for pediatric drug safety. We reviewed the impact of these continuously ongoing measures on medication errors after 10 years. METHODS: The PaedER was introduced and distributed to all 14 emergency ambulances and 2 helicopters staffed with emergency physicians in the city of Cologne in November 2008. Electronic records and medical protocols of the Cologne EMS over two 20-month periods from March 2007 to October 2008 and March 2018 to October 2019 data sets were retrieved. The administered doses of either intravenous, intraosseous, intranasal, or buccal fentanyl, midazolam, ketamine, or epinephrine were recorded. Primary outcome measure was the rate of severe drug dosing errors with a deviation from the recommended dose of greater than 300%. RESULTS: A total of 59 and 443 drug administrations were analyzed for 2007/08 and 2018/19, respectively. The overall rate of drug dosing errors decreased from 22.0% to 9.9% (P = 0.014; relative risk reduction, 55%). Four of 5 severe dosing errors for epinephrine were avoided (P < 0.021; relative risk reduction, 78%). Documentation of patient's weight increased from 3.2% in 2007/08 to 30.5% in 2018/19 (P < 0.001). CONCLUSIONS: The distribution of the PaedER combined by educational measures significantly reduced the rates of life-threatening medication errors in a large EMS. Those results should motivate further initiatives on pediatric drug safety in prehospital emergency care.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it