The geographic accessibility of pharmacies in Nova Scotia
Bibliographic record
Abstract
INTRODUCTION: Geographic proximity is an important component of access to primary care and the pharmaceutical services of community pharmacies. Variations in access to primary care have been found between rural and urban areas in Canadian and international jurisdictions. We studied access to community pharmacies in the province of Nova Scotia. METHODS: We used information on the locations of 297 community pharmacies operating in Nova Scotia in June 2011. Population estimates at the census block level and network analysis were used to study the number of Nova Scotia residents living within 800 m (walking) and 2 km and 5 km (driving) distances of a pharmacy. We then simulated the impact of pharmacy closures on geographic access in urban and rural areas. RESULTS: We found that 40.3% of Nova Scotia residents lived within walking distance of a pharmacy; 62.6% and 78.8% lived within 2 km and 5 km, respectively. Differences between urban and rural areas were pronounced: 99.2% of urban residents lived within 5 km of a pharmacy compared with 53.3% of rural residents. Simulated pharmacy closures had a greater impact on geographic access to community pharmacies in rural areas than urban areas. CONCLUSION: The majority of Nova Scotia residents lived within walking or short driving distance of at least 1 community pharmacy. While overall geographic access appears to be lower than in the province of Ontario, the difference appears to be largely driven by the higher proportion of rural dwellers in Nova Scotia. Further studies should examine how geographic proximity to pharmacies influences patients' access to traditional and specialized pharmacy services, as well as health outcomes and adherence to therapy. Can Pharm J 2013;146:39-46.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".