Multihospital collaborative orientation program for new pharmacy employees
Bibliographic record
Abstract
From 1998 to 2005, nine hospital pharmacies in Winnipeg, Manitoba, Canada, had annual pharmacist vacancy rates ranging from 3.4% to 67%. Despite the implementation of very successful recruitment initiatives citywide from 2002 to 2004, most pharmacies had difficulty retaining new pharmacist recruits. During exit interviews and new recruit focus group sessions conducted in 2003 and 2004, pharmacists said that their orientation and initial training left them feeling unprepared to practice safely in their new job. Further investigation revealed that prolonged staffing shortfalls, along with changes in key supervisory personnel and the departure of many experienced pharmacists, had left new employee training processes in disarray at most hospital pharmacies. At the time this initiative was undertaken, the two long-term-care, five community, and two tertiary care publicly funded hospitals operated as separate corporations working in alliance with a regional health authority (population catchments, 800,000). The hospitals ranged in size from 185 to 745 acute care beds, approximating 2,000 beds citywide. Each hospital had pharmacy total staff numbers ranging from 13 to 121 full-time-equivalents (FTEs) (an estimated 150 FTE pharmacists across nine hospitals). The hospitals differed markedly in their drug distribution and pharmacy information systems; however, all pharmacies adhered to a common formulary and were implementing a common set of clinical practice expectations.1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".