Utility of the Vascular Quality Initiative in improving quality of care in Canadian patients undergoing vascular surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Vascular Quality Initiative (VQI) is a national cooperative quality-improvement initiative designed to evaluate processes of care and outcomes in vascular surgery. The purpose of this report is to show the utility of such a database to provide insight into the standard of care provided, to highlight areas of local quality improvement, to benchmark our data against local, regional and national trends, and to ultimately improve safety in Canadian patients undergoing vascular surgery. We present the history of the database, its spread in the Canadian health care system and examples of quality improvements achieved from analyses of data recorded and retrieved from the VQI. Using the VQI, our institution was able to decrease the length of stay after endovascular aneurysm repair, decrease the contrast volume in endovascular aneurysm repair, save on costs, and provide medium-term outcome data on peripheral vascular interventions and smoking cessation strategies. The VQI is a powerful tool to improve patient safety and quality in vascular surgery. Its ability to create local regional improvement groups fosters a quality-focused culture and is important for Canadian patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it