Comparative Analysis of Geographic Accessibility of Dentists, Physiotherapists and Family Physicians in an Urban Centre: A Case Study of Saskatoon, Canada.
Bibliographic record
Abstract
BACKGROUND: The spatial arrangement of primary health care (PHC) services is influenced by many factors and varies across provider types. In Canada, unlike physician services, certain PHC services (i.e., dentistry, physiotherapy) are not fully funded under the health care system. As a result, one might expect the arrangement of these services to differ by neighbourhood, even in dense metropolitan areas. OBJECTIVE: This study examines the intra-urban variability of geographic access to dental (DS) and physiotherapy (PT) services in relation to family physician (FP) services in an urban area and identifies underserviced neighbourhoods. METHODS: Practice location information was gathered from publicly available and routinely updated provincial sources (physician, physiotherapy and dentistry regulatory colleges). A neighbourhood accessibility score for all 3 PHC services was calculated using a GIS-based, 3-step floating catchment area method. A set of parameters, such as catchment type (road network buffer), size (3 km radius) and census centroids (dissemination areas), was used. RESULTS: The overall access scores for FP, PT and DS services (based on the 281 FPs, 226 PTs, and 152 DSs) were 1.45 (SD 0.94), 1.18 (SD 0.81) and 0.79 (SD 0.53) providers/1000 population, respectively. Spatial comparison of the accessibility scores indicated a greater proportion of the Saskatoon population has lower access scores (< 0.5/1000 population) for both physiotherapy (n = 79 450) and dental (n = 101 270) services compared with family physician services (n = 64 420). Exploration of the relation between PHC service arrangement and key sociodemographic variables (e.g. low income, education levels) showed that a considerable proportion of those in each sociodemographic group has poor PT and DS access. CONCLUSION: This research has identified accessibility gaps and serves to inform the development of health policies focused on equitable distribution and funding of PHC services based on population health needs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 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".