Redesigning the clinical pharmacy practice model at a psychiatric hospital
Bibliographic record
Abstract
Introduction: Integrated, patient-centered clinical pharmacy services have been shown to improve patient outcomes in a variety of settings, including mental health. In this article, we describe and report the impact of a restructured clinical practice model that incorporated direct patient care by pharmacists implemented at a psychiatric facility in Edmonton, Canada. The purpose of redesigning the clinical pharmacy program was to deliver proactive pharmacist care through integrated clinical pharmacy services and to better align pharmacists' activities with those that have been reported to have a positive impact on patient outcomes. Methods: Pharmacists' documentation notes in medical records for patients admitted and discharged from the hospital at four different time periods were reviewed. For each time period, the number, type, and documentation rate were measured and compared using a Student t test with correction for unequal variances. Significant change was defined as P < .05. Documentation rates were also compared for short-stay versus long-stay patients. Results: A consistent and statistically significant increase was found in pharmacists' clinical notes per chart from 0.15 to 1.5 (P < .001) after implementation of the redesigned clinical practice model. The proportion of clinical notes also increased from 22% in the preimplementation period to up to 68% in the current period. This indicates that pharmacists were spending proportionally more time on proactive versus reactive care. Documentation rates also increased regardless of the patients' length of stay. Discussion: The redesigned clinical practice model enabled a successful transition of the pharmacists' role, from being predominantly reactive to becoming more proactive and integrated.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".