A needs assessment of community pharmacists for pharmacist specialization in Canada
Bibliographic record
Abstract
OBJECTIVES: Pharmacists are increasingly providing specialized services. However, no process exists for specialist certification in Canada. The aim of this study was to determine the extent to which Canadian community pharmacists support the development of a certification system for specialization. METHODS: This study utilized a cross-sectional online survey of licensed Canadian pharmacists identified through the member databases of national and regional pharmacy associations. A questionnaire was developed (in French and English) and distributed via email, on behalf of the researchers, by multiple pharmacy organizations in January 2015. Multivariate logistic regressions were conducted to identify which sub-groups of respondents supported the creation of a certification system and which supported mandatory certification. KEY FINDINGS: A total of 770 responses were received. Many respondents were practising specialists (30.0%, 205/683) and the most commonly reported specialty areas were diabetes, smoking cessation and geriatrics. Almost 85% (n = 653/770) supported creation of a Canadian certification process and 68.5% (n = 447/653) felt certification should be mandatory. Respondents believed that the primary benefit of a certification system was greater public confidence in pharmacist specialist skills. They also felt that the most important factor in the development of the system is to create national definitions for specialty practice. The main barrier was the lack of reimbursement for specialty services in Canada. CONCLUSIONS: The majority of Canadian community pharmacist respondents support the creation of a certification process for pharmacist specialization. Future study is required to confirm this finding in a larger sample and to determine the optimal model and the financial feasibility of a national system in Canada.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 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) | 0.002 | 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".