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Record W2147401963 · doi:10.2146/ajhp080487

Multihospital collaborative orientation program for new pharmacy employees

2010· article· en· W2147401963 on OpenAlexaffabout
Donna M M Woloschuk, Colette B. Raymond

Bibliographic record

VenueAmerican Journal of Health-System Pharmacy · 2010
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsHealth Sciences CentreWinnipeg Regional Health Authority
Fundersnot available
KeywordsPharmacyPharmacistLibrary scienceManagementSociologyPolitical scienceMedicineNursingComputer science

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.483
Teacher spread0.397 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Health-System PharmacySame topicPharmaceutical Practices and Patient OutcomesFrench-language works237,207