Evaluating the Labour Costs Associated with Pharmacy Adaptation Services in British Columbia
Bibliographic record
Abstract
BACKGROUND: Pharmacists' scope of practice has been steadily expanding across Canada to encompass clinical activities. In January 2009, pharmacists in British Columbia (BC) were given the authority to adapt prescriptions for renewals; change in dose, formulation or regimen; and therapeutic substitutions. This study evaluated the labour costs associated with pharmacy adaptation services in BC. > METHODS: Ten high-adapting pharmacies participated in the study. Through workflow observations, we measured the time incurred for adapted and nonadapted prescriptions. RESULTS: We observed 91 adapted prescriptions and 1081 nonadapted prescriptions. The total average time to provide adapted prescriptions was 6:43 minutes (SD 3:50) longer than to provide nonadapted prescriptions. The total average cost of an adapted prescription was $6.10 greater than a nonadapted prescription. Renewals took the least amount of time to complete, and therapeutic substitutions took the most time to complete. DISCUSSION: Through workflow observations, it was determined that 10 stages of activity occur when adapting a prescription, with the most time being expended during the documentation and processing phases. Labour costs associated with adapted prescriptions were higher than for nonadapted prescriptions.
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 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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".