Walk-in clinic patient characteristics and utilization patterns in Ontario, Canada: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Walk-in clinics are common in North America and are designed to provide acute episodic care without an appointment. We sought to describe a sample of walk-in clinic patients in Ontario, Canada, which is a setting with high levels of primary care attachment. METHODS: We performed a cross-sectional study using health administrative data from 2019. We compared the sociodemographic characteristics and health care utilization patterns of patients attending 1 of 72 walk-in clinics with those of the general Ontario population. We examined the subset of patients who were enrolled with a family physician and compared walk-in clinic visits to family physician visits. RESULTS: Our study found that 562 781 patients made 1 148 151 visits to the included walk-in clinics. Most (70%) patients who attended a walk-in clinic had an enrolling family physician. Walk-in clinic patients were younger (mean age 36 yr v. 41 yr, standardized mean difference [SMD] 0.24), yet had greater health care utilization (moderate and high use group 74% v. 65%, SMD 0.20) than the general Ontario population. Among enrolled Ontarians, walk-in patients had more comorbidities (moderate and high count 50% v. 45%, SMD 0.10), lived farther from their enrolling physician (median 8 km v. 6 km, SMD 0.21) and saw their enrolling physician less in the previous year (any visit 67% v. 80%, SMD 0.30). Walk-in encounters happened more often after hours (16% v. 9%, SMD 0.20) and on weekends (18% v. 5%, SMD 0.45). Walk-in clinics were more often within 3 km of patients' homes than enrolling physicians' offices (0 to < 3 km: 32% v. 22%, SMD 0.21). INTERPRETATION: Our findings suggest that proximity of walk-in clinics and after-hours access may be contributing to walk-in clinic use among patients enrolled with a family physician. These findings have implications for policy development to improve the integration of walk-in clinics and longitudinal primary care.
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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) | 0.000 | 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) | 0.002 | 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 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".