Trends in Clinical Pharmacist Integration in Family Medicine Residency Programs in North America
Bibliographic record
Abstract
(1) Objective: To determine the change in prevalence of clinical pharmacists as clinician educators within family medicine residency programs (FMRPs) in North America and to describe their clinical, educational and administrative scope over time. (2) Methods: A systematic review of the literature was performed starting with an electronic search of PubMed and Embase for articles published between January 1980 and December 2019. Studies were included if they surveyed clinical pharmacists regarding their clinical, educational, or other roles in FMRPs in the United States or Canada. The primary outcome was the change in prevalence of clinical pharmacists in North America. Secondary outcomes included: demographic information of clinical pharmacists, change in the prevalence in Canada and United States, and descriptions of clinical services, educational roles, and other activities of clinical pharmacists within FMRPs. (3) Results: Of the 65 articles identified, six articles met the inclusion criteria. The prevalence of clinical pharmacists as clinician educators in FMRPs in North America has grown from 24% to 53% in the United States (U.S.) and from 14% to 47% in Canada over the study period. The clinical and educational roles are similar including: the direct patient care, clinical education, and interprofessional education and practice. (4) Conclusion: The prevalence of clinical pharmacists in FMRPs is growing across North America. Clinical pharmacists are highly educated and trained to support these clinician educator positions. While educational roles are consistent, clinical pharmacists’ patient care roles are unique to their clinical site and growing.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".