Up-to-date on cancer screening among Ontario patients seen by walk-in clinic physicians: A retrospective cohort study
Bibliographic record
Abstract
Walk-in clinics are typically viewed as high-volume locations for managing acute issues but also may serve as a location for primary care, including cancer screening, for patients without a family physician. In this population-based cohort study, we compared breast, cervical and colorectal cancer screening up-to-date status for people living in the Canadian province of Ontario who were formally enrolled to a family physician versus those not enrolled but who had at least one encounter with a walk-in clinic physician in the previous year. Using provincial administrative databases, we created two mutually exclusive groups: i) those who were formally enrolled to a family physician, ii) those who were not enrolled but had at least one visit with a walk-in clinic physician from April 1, 2019 to March 31, 2020. We compared up to date status for three cancer screenings as of April 1, 2020 among screen-eligible people. We found that people who were not enrolled and had seen a walk-in clinic physician in the previous year consistently were less likely to be up to date on cancer screening than Ontarians who were formally enrolled with a family physician (46.1% vs. 67.4% for breast, 45.8% vs. 67.4% for cervical, 49.5% vs. 73.1% for colorectal). They were also more likely to be foreign-born and to live in structurally marginalized neighbourhoods. New methods are needed to enable screening for people who are reliant on walk-in clinics and to address the urgent need in Ontario for more primary care providers who deliver comprehensive, longitudinal care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".