The Ontario Pharmacy Evidence Network Interactive Atlas of Professional Pharmacist Services
Bibliographic record
Abstract
Over the past few decades, the role and scope of pharmacists in Canada has broadened to provide a more effective platform upon which to contribute to outcomes-driven medication management.1 Community pharmacists are among the most accessible health care providers within the community-based health care system and have offered a growing list of professional pharmacy services as a consequence of professional evolution.1,2 Since 2007, the government of Ontario has leveraged community pharmacist expertise in medication management by introducing and remunerating community pharmacies for the following professional pharmacist services: medication reviews through MedsCheck programs (Annual, Diabetes, Home, Long-Term Care),3-6 communicating with prescribers regarding drug therapy-related problems (Pharmaceutical Opinion program),7,8 providing smoking cessation counselling services (pharmacy smoking cessation program)9 and administering influenza immunizations10,11 (Figure 1). Pharmacies submit claims to the Ontario government through the Ontario Drug Benefit program for renumeration for each service (Table 1). We received funding from the Government of Ontario as part of the Ontario Pharmacy Evidence Network (OPEN) program peer-reviewed Health Service Research Fund to complete descriptive analyses of professional pharmacy services delivery across the province. These analyses are introduced here as the OPEN Interactive Atlas of Professional Pharmacist Services (Box 1).12 This research brief provides an overview with technical detail to support the Atlas.12 Future briefs will summarize each service separately.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.019 | 0.035 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 0.011 |
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".