Barriers to colonoscopy in remote northern Canada: an analysis of cancellations
Bibliographic record
Abstract
Background: Colonoscopy is a critical diagnostic and therapeutic procedure that is challenging to access in northern Canada. In part, this is due to frequent cancellations. We sought to understand the trends and reasons for colonoscopy cancellations in the Northwest Territories (NWT).Methods: A retrospective review of colonoscopy cancellations January, 2018 to May, 2019 was conducted at Stanton Territorial Hospital, NWT. Cancellation details and rationale were captured from the endoscopy cancellation logs. Thematic analysis was used to group cancellation reasons. Descriptive statistics were generated, and trends were analysed using run chart.Results: Of the scheduled colonoscopies, 368(28%) were cancelled during the 16 month period, and cancellations occurred, on average, 27 days after booking. Cancellation reasons were grouped into 15 themes, encompassing personal, social, geographic and health system factors. The most frequently cited theme was work/other commitments (69 respondents; 24%). Cancellations due to travel and accommodation issues occurred more frequently in the winter.Conclusion: Over one in four booked colonoscopies were cancelled and the reasons for cancellations were complex. Initiatives focusing on communication and support for patients with personal or occupational obligations could dramatically reduce cancellations. Ongoing collaborative efforts are needed to inform and optimise access to colonoscopy in this region.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".