How were Wait Times for Priority Procedures in Canada Impacted during the First Six Months of the COVID-19 Pandemic?
Bibliographic record
Abstract
In 2020, health systems across Canada responded to the COVID-19 pandemic by making rapid changes to reduce the risk of exposure for patients and staff and to allocate resources toward the treatment of COVID-19 patients. This included postponing surgical and diagnostic procedures. Data collected by the Canadian Institute for Health Information show that these interventions resulted in longer wait times across all provinces in April-September 2020 for scheduled surgical procedures, such as hip and knee replacements and cataract surgeries. The impact on wait times for cancer surgeries and diagnostic imaging varied by type of procedure and jurisdiction, while the wait times for hip fracture repair and radiation therapy were not impacted. Subsequent waves of the COVID-19 pandemic added to the initial backlog of procedures, and it will take time to assess the long-term impact of surgical and diagnostic imaging delays on patient outcomes and wait times.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".