CT and MRI Services in Urban, Rural, and Remote Settings: 24-Hour and Weekend Operations
Bibliographic record
Abstract
What Is the Issue Canada’s Drug Agency received a request to identify facilities that provide 24-hour and weekend CT and MRI services across Canada. Access to imaging services with extended-hours differs across regions, reflecting the variations in local capacity and resource availability. CT and MRI services offered 24 hours and on weekends may help reduce diagnostic wait times, improve emergency department patient flow, maximize use of imaging equipment, and enhance access for patients in rural and remote communities. What Did We Do In response to the request, Canada’s Drug Agency leveraged data from the Canadian Medical Imaging Inventory (CMII) 2022–2023 National Survey. This comprehensive survey gathered detailed, site-level data, including information on 24-hour and weekend operations from sites with CT and MRI units. The aim was to assess the availability of these services in urban, rural, and remote settings in each province and territory with capacity. What Did We Find The analysis revealed the following key findings: Urban facilities reported the highest availability of 24-hour CT and MRI services, while rural and remote sites had more limited access. Weekend availability was generally greater than 24-hour availability, with urban facilities leading in weekend CT and MRI services, and rural and remote sites offering fewer weekend operations. Compared with CT, far fewer sites with MRI — even in urban centres — offered 24-hour or weekend services. Across Canada, 24-hour and weekend CT and MRI services vary considerably by jurisdiction and facility. Facilities offering 24-hour services are also likely to provide weekend services, suggesting that once extended-hour infrastructure is in place, it can support broader service availability. What Does This Mean These findings provide valuable insights into the availability of 24-hour and weekend for CT and MRI services across Canada, which can guide decision-making in several ways: The data can support evidence-based policies to extend imaging hours — particularly for urgent and emergency care — by identifying where increased access could have the greatest impact. While expanding service availability within existing infrastructure may improve patient outcomes, such efforts must be balanced against practical constraints, including funding, equipment, and staffing. Sites that do not have after-hours imaging access may signal opportunities where investments in staffing and infrastructure may be most beneficial. Rather than expanding services uniformly, decision-makers may prioritize high-need regions to support equitable, efficient use of limited resources. Expanding 24-hour and weekend services in rural and remote locations may reduce travel burden and help ease pressure on urban imaging centres, ultimately shortening wait times and improving access to timely care. Understanding where continuous coverage is limited can guide recruitment and retention efforts.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".