Evaluation of a professional development course for pharmacists on laboratory values: can practice change?
Bibliographic record
Abstract
OBJECTIVES: The practice environment in Alberta has emerged as the most unique in North America, including access to laboratory values, a province-wide electronic health record and legislation to support additional prescribing authority for qualified pharmacists. A course to help pharmacists integrate laboratory values in their medication management of patients was introduced to prepare pharmacists for these changes. The purpose of this study was to evaluate pharmacists' experience with a continuing professional development (CPD) course and its impact on pharmacists' knowledge, confidence and change in practice. METHODS: A 12-week CPD course for pharmacists on interpreting laboratory values was delivered as a 2-day interactive workshop followed by three distance-learning sessions. The evaluation explored pharmacists' knowledge and confidence using laboratory values in practice, changes in practice and effectiveness of course delivery through pre- and post-course surveys and interviews. KEY FINDINGS: Pharmacists' knowledge about laboratory tests and confidence discussing and using laboratory values in practice significantly improved after course completion. The blended delivery format was viewed positively by course participants. Pharmacists were able to implement learning and make changes in their practice following the course. CONCLUSIONS: A CPD course for pharmacists on integrating laboratory values improved pharmacists' knowledge and confidence and produced changes in practice.
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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 | 0.018 | 0.037 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".