Proof of Concept and Pilot Study on the Development and Implementation of an Electronic Medication Administration Record
Bibliographic record
Abstract
Abstract : The main objective is to describe the phases of electronic medication administration record development and implementation. The secondary objective is to compare dose information using medication administration record and electronic medication administration record. : Nursing daily work planning is usually done with the use of a medication administration record printed daily based on the information available in the Pharmacy Information System. : We identified six guiding principles. A profile compared to medication administration record and electronic medication administration record, revealed 19 parameters related to drug registration doses. Regarding the development phase, a total of 150 pharmacist hours and 150 nursing hours have been carried out on optimization of electronic medication administration record. During the preparatory pilot phase, voluntary nurses have been invited to identify problems associated with the electronic version. During the pilot phase, a training program was set up. We implemented the electronic medication administration record on 26 November 2014. The pilot study demonstrates that electronic medication administration record has been successfully implemented in a university hospital. : To our knowledge, this is the first pilot study conducted in Quebec that describes electronic medication administration record development and implementation. Our pilot study shows that we were able to face these challenges through the employment of human, financial and material resources.
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".