Family physician access to and wait times for cancer diagnostic investigations: Regional differences among 3 provinces.
Bibliographic record
Abstract
OBJECTIVE: To examine provincial and regional differences in FPs' direct access to cancer diagnostic investigations and advice from other specialists regarding investigations and referrals, and to explore FPs' perceptions about wait times for diagnostic investigations and receipt of results. DESIGN: A cross-sectional, online survey. SETTING: British Columbia, Manitoba, and Ontario. PARTICIPANTS: A sample of FPs from participating provinces. MAIN OUTCOME MEASURES: Direct FP access to various diagnostic investigations and advice from other specialists regarding investigations and referrals; FPs' perceptions about wait times for diagnostic investigations ordered directly; and FPs' perceptions about wait times for results. RESULTS: A total of 1054 surveys were completed by FPs from British Columbia (n = 229), Manitoba (n = 228), and Ontario (n = 597). Distance from a cancer centre was not significantly associated with direct access to or wait times for diagnostic investigations for most of the investigations studied; however, provincial differences were observed. Family physicians in Manitoba and British Columbia were 30% to 45% less likely to report having direct access to endoscopy and some imaging investigations compared with FPs in Ontario. Family physicians in Manitoba and British Columbia were also at increased odds of waiting longer than 12 weeks for endoscopy investigations and longer than 4 weeks for imaging investigations compared with FPs in Ontario. Most FPs reported wait times of less than 2 weeks for imaging results; however, the proportion of FPs who waited longer than 2 weeks for colonoscopy results ranged from 15% in Ontario to 96% in British Columbia. CONCLUSION: Given the disparities observed among provinces, there is an opportunity for provinces to learn from one another to improve direct access to and shorten wait times for diagnostic investigations. This in turn has the potential to shorten the primary care interval for cancer diagnostic assessment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".