Implementation of a Computerized Provider Order Entry System in a Pediatric Hospital in Canada
Bibliographic record
Abstract
The Centre Hospitalier Universitaire Sainte-Justine (Montreal, Canada) is a pediatric academic tertiary hospital that has begun the implementation of a commercial computerized provider order entry system (CPOE) in October 2019. The objectives of this paper are 1) to estimate the impact of the CPOE system on medication errors, and 2) to identify vulnerability issues related to the configuration of the CPOE system's design. Using a pre-post implementation methodology measuring medication errors captured by clinical pharmacists revealed that the implementation of a CPOE has eliminated all prescription conformity (e.g., missing fields) and legibility errors. Pharmacists have continued to detect medication errors, especially inappropriate dosing instructions, and to intervene in similar clinical situations (medication reconciliation, deprescribing, adjusting orders). Additionally, the vulnerability analysis, based on typical clinical order test cases in an inpatient pediatric setting, highlighted the need to configure a clinical decision support system that can identify inappropriate dosing instructions for pediatric patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".