PS-056 How do you review a medication order? a FRANCE–QUEBEC comparison
Bibliographic record
Abstract
Background Medication order review is a fundamental pharmacist activity. Several guidelines from different countries specify the validation elements required for medication order review in general but none of specify the optimal order to consider for these elements and taking into account its applicability in the hospital pharmacy. Purpose The objective was to identify and justify similarities and differences between the medication order review processes in France and Quebec. Material and methods This was a descriptive prospective study. 22 validation elements for medication order review were selected and sequenced from guidelines. An online survey was developed in three parts: (A) selection of validation elements in three scenarios—(1) centralised validation, (2) decentralised validation and (3) centralised validation by a pharmacist with a decentralised pharmacist present in patient care areas; (B) sequence of the 22 validation elements; and (C) level of agreement about medication order review statements. The survey was sent to hospital pharmacists at 2 teaching hospitals in Quebec and France. Results The response rate was 60% (45/75: 23 in France; 22 in Quebec). For scenario (1), there was a significant difference between France and Quebec for 10 validation elements, 8 of these being more supported by Quebec respondents. For scenario (2), there was only 1 significant difference between France and Quebec. For scenario (3), nine elements were significantly different between France and Quebec, 5 of these being more supported by French respondents. These differences can be explained by local drug use process organisation and tools, current practices and personal prioritisation. For instance, a computerised prescriber order entry was used in the French hospital, but not in the Quebec one. Quebec pharmacists are used to having decentralised clinical pharmacists in patient care programmes but exposure of French pharmacists to this practice model is only emerging. Medication reconciliation has been required in Canada since 2008, while it has only started to be implemented in France. Conclusion Medication order review practices are different between France and Quebec, in terms of validation elements considered by hospital pharmacists and their optimal sequence. Such differences can be explained by numerous factors, including tools used to prescribe and validate drug order and the presence of pharmacists in patient care areas. No conflict of interest
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".