Provincial Door-to-Needle Improvement Initiative Results in Improved Patient Outcomes Across an Entire Population
Bibliographic record
Abstract
Background and Purpose: Improving door-to-needle times (DNTs) for thrombolysis of acute ischemic stroke patients improves outcomes, but participation in DNT improvement initiatives has been mostly limited to larger, academic medical centers with an existing interest in stroke quality improvement. It is not known whether quality improvement initiatives can improve DNT at a population level, including smaller community hospitals. This study aims to determine the effect of a provincial improvement collaborative intervention on improvement of DNT and patient outcomes. Methods: A pre post cohort study was conducted over 10 years in the Canadian province of Alberta with 17 designated stroke centers. All ischemic stroke patients who received thrombolysis in the Canadian province of Alberta were included in the study. The quality improvement intervention was an improvement collaborative that involved creation of interdisciplinary teams from each stroke center, participation in 3 workshops and closing celebration, site visits, webinars, and data audit and feedback. Results: Two thousand four hundred eighty-eight ischemic stroke patients received thrombolysis in the pre- and postintervention periods (630 in the post period). The mean age was 71 years (SD, 14.6 years), and 46% were women. DNTs were reduced from a median of 70.0 minutes (interquartile range, 51–93) to 39.0 minutes (interquartile range, 27–58) for patients treated per guideline ( P <0.0001). The percentage of patients discharged home from acute care increased from 45.6% to 59.5% ( P <0.0001); the median 90-day home time increased from 43.3 days (interquartile range, 27.3–55.8) to 53.6 days (interquartile range, 36.8–64.6) ( P =0.0015); and the in-hospital mortality decreased from 14.5% to 10.5% ( P =0.0990). Conclusions: The improvement collaborative was likely the key contributing factor in reducing DNTs and improving outcomes for ischemic stroke patients across Alberta.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".