Unique pharmacist competency program at community-based, teaching hospitals
Bibliographic record
Abstract
Background: The pharmacy profession continues to evolve and shape itself with increasing complexity. With this escalating complexity, pharmacist clinical competency needs to be addressed within each healthcare practice setting. The objectives of this study were to describe a unique pharmacist competency program and evaluate its satisfaction at two community hospitals. Methods: Long Beach Memorial and Miller Children’s Hospital of Long Beach are tertiary community hospitals with 308 total beds for Millers Children’s Hospital and 462 total beds for Long Beach Memorial. A unique and intensive pharmacist competency program has been established at these hospitals for over 20 years. The content of this program was assessed and a survey was conducted in March 2011 to ascertain pharmacist satisfaction. Results: The unique pharmacist competency program was structured in the form of age-related, hospital-wide and unit specific modules, pharmacy-regulated therapies (PRT), and a Pharmacy Skills Day that provide updates on PRT and other pharmacy-related topics. Forty-two of 61 (69%) pharmacists responded to the survey. Mean age of pharmacists was 38.8 ± 11.5 years, 36% were male, 86% completed residency training, and 12% were board-certified pharmacotherapy specialists. Over 80% of pharmacists agreed that the program was informative and supportive of their daily patient care activities. Although the program was well-received by the pharmacists, there were facets of the program that needed improvement, including resources for continuing education opportunities and additional modules for competency. Conclusion: A unique pharmacist competency program at two community hospitals was described. The program was well-received by the pharmacists, and, more importantly, ensured continuous professional development in pharmacy 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".