Geographic distribution of Ontario pharmacists: A focus on rural and northern communities
Bibliographic record
Abstract
Introduction: Canadians living in rural and northern communities face particular health needs and challenges in accessing primary care services. Ontario pharmacists are increasingly able to optimize patient care with a broadening scope of practice; this was highlighted during the COVID-19 pandemic. This study explores the geographic distribution of pharmacists to evaluate their potential to deliver health care in rural and northern Ontario communities. Methods: A secondary analysis of the Ontario College of Pharmacists' registry data was undertaken, with all Part A pharmacists who had at least 1 patient care practice site included in the analysis. Full-time equivalent (FTE) hours worked at each practice site were calculated and compared with the population distribution. Ratios of FTEs per 1000 residents by census subdivision (which represents communities) were calculated and compared by geography, north vs south and urban vs rural (further subdivided by metropolitan-influenced zones). Results: The greatest availability of pharmacist FTEs was found in urban communities (with slightly better availability in the north), whereas the lowest availability was found in the most rural communities. A more granular observation revealed that northern communities were more likely to have no local pharmacist access (72%) compared with southern communities (24%). Discussion: Rural and northern communities are underserved. Novel approaches to overcoming the rural pharmacist care gap include rural practice incentives, targeted enrollment of rural students, increased rural exposure in pharmacy schools and the utilization of new technologies such as telepharmacy and drone medication deliveries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".