Characteristics of walk-in clinic physicians and patients in Ontario
Bibliographic record
Abstract
OBJECTIVE: To describe family physicians who primarily practise in a walk-in clinic setting and compare them with family physicians who provide longitudinal care. DESIGN: A cross-sectional study that linked results from a 2019 physician survey to provincial administrative health care data in Ontario. The characteristics, practice patterns, and patients of physicians primarily working in a walk-in clinic setting were compared with those of family physicians providing longitudinal care. SETTING: Ontario. PARTICIPANTS: Physicians who primarily worked in a walk-in clinic setting in 2019, as indicated by an annual physician survey. MAIN OUTCOME MEASURES: Physician demographic and practice characteristics, as well as their patients' demographic and health care utilization characteristics, were reported according to whether the physician was a walk-in clinic physician or a family physician who provided longitudinal care. RESULTS: Compared with the 9137 family physicians providing longitudinal care, the 597 physicians who self-identified as practising primarily in walk-in clinics were more frequently male (67% vs 49%) and more likely to speak a language other than English or French (43% vs 32%). Walk-in clinic physicians tended to have more encounters with patients who were younger (mean 37 vs 47 years), who had lower levels of prior health care utilization (15% vs 19% in highest band), who resided in large urban areas (87% vs 77%), and who lived in highly ethnically diverse neighbourhoods (45% vs 35%). Walk-in clinic physicians tended to have more encounters with unattached patients (33% vs 17%) and with patients attached to another physician outside their group (54% vs 18%). CONCLUSION: Physicians who primarily work in walk-in clinics saw many patients from historically underserved groups and many patients who were attached to another family physician.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".