Community Pharmacists' Expectations of a Pharmacy Network: A Baseline Evaluation
Bibliographic record
Abstract
Background: The Newfoundland and Labrador Centre for Health Information has been mandated to build a provincial Health Information Network (HIN). Phase I, Unique Personal Identifier/Client Registry, is complete. Phase II, the Newfoundland and Labrador Pharmacy Network (Pharmacy Network), will provide integration among community and institutional pharmacies, the Newfoundland and Labrador Prescription Drug Program, hospital emergency rooms, and physician offices. This study was carried out to determine community pharmacists' perceived value of a pharmacy network pre-implementation. Methods: A four-part questionnaire was designed using a literature review and a pilot study. In December 2002, questionnaires were mailed to all 435 community pharmacists in the province. Results: Overall, 90.3% of community pharmacists agreed that drug utilization review would be an important function of the Pharmacy Network. The perceived value of computerized physician order entry was high. Removing problems with illegible handwriting received the strongest support (97.2%). Payment for providing various levels of pharmaceutical care also received strong support. The perceived value of a pharmacy network differed among community pharmacists with respect to age, sex, education, years in practice, and place of business. Conclusions: The results contributed important baseline information about community pharmacists' expectations pre-implementation. They also provided benchmarks for future comparative studies that measure perceived value after implementation of the Pharmacy Network.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".