Improving Measures of Hip Fracture Wait Times: A Focus on Ontario
Bibliographic record
Abstract
In 2009-2010, a "time of surgery" data element was added to CIHI's Discharge Abstract Database enabling a more precise calculation of patient wait times for hip fracture repair, measured in hours rather than days.Using an Ontario sample, we explored this more precise calculation for the first three quarters of 2009-2010 (April to December), and the impact of adding wait times in the emergency department (ED) to the total wait.When we linked emergency department and in-patient care wait times, the percent of patients meeting the benchmark of 48 hours dropped from 78% (when the start time was admission to an acute care bed) to 71%.Longwoods journals are published in partnership with our readers, our editors, our advisory boards, our authors as well as healthcare organizations and their suppliers of solutions and services.We value this participation in and dedication to leadership and knowledge.They enable us to present new ideas, policies and best practices essential to healthcare management, practice, education, research and innovation.It is a measure of their support for learning.Nothing can be more fundamental to the progress of healthcare.Longwoods.com
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".