Impact of an educational training program on pharmacists’ documentation practice at a teaching hospital
Bibliographic record
Abstract
OBJECTIVES: This study aims to determine the impact of an educational training program on the quantity and quality of the pharmacists' documentation practice at the Winchester District Memorial Hospital. METHODS: This study is a part of an evaluation for continuous quality improvement, performed applying a pre- and post-test model. The primary endpoint was the number of Pharmacists' Patient-Care Records in patient charts with the listed action codes. Charts of 80 patients were surveyed at three points (two months before and one and three months after the sessions) for 240 charts. Additionally, a pre- and post-educational questionnaire was administered using case scenarios and the Pharmacists' Patient-Care Record code system. RESULTS: The number of charts containing Pharmacists' Patient-Care Records with Action Codes listed is 70%, 73%, and 64% in the first, second, and third chart review rounds, respectively. According to the pre- and post-educational session questionnaire, the average score per pharmacist is 47% and 73%, respectively. CONCLUSION: The initial estimate of the documentation practice is 50% or less, which is an underestimation. Furthermore, the quantity of pharmacists' documentation is not significantly affected by the educational sessions; however, the quality is improved.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".