Resetting The Dtn Clock : a Community Hospital Experience
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
BackgroundLakeridge Health Oshawa is a District Stroke Centre that provides hyper-acute stroke care for the Durham Region. For three fiscal years the annual Door-To-Needle (DTN) times exceeded 65 minutes. The District Stroke Centre was forced to take a fresh look at the process.MethodAn environmental scan was conducted in an attempt to identify delays in treatment. This was followed by a literature review and poll of Stroke Centres across Ontario to examine what had been successfully implemented in other organizations. A working group was formed with representatives from all internal and external partners. Representatives shared drafts and solicited feedback from staff in their areas. Following several revisions a live simulation was conducted. A debrief followed and the final algorithm was completed on November 28, 2017. ED staff was engaged in the month preceding and following the go live date to review the new protocol and to provide feedback. The protocol went live on December 4, 2017. The CNS attended code strokes to offer support and education. ResultsThe recreated protocol included an overhead Stroke Alert prior to patient arrival, assessment of patient and transfer to CT on EMS stretcher, and delivery of tPA on the CT table. These changes have significantly decreased the DTN times. Three months following implementation DTN times have reduced by 30 minutes and continue to trend downward. The six-month data will be presented at Congress. ConclusionsSignificant improvements have occurred through thoughtful implementation strategies and staff commitment to improve patient outcome.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.023 | 0.027 |
| Open science | 0.051 | 0.055 |
| Research integrity | 0.002 | 0.011 |
| Insufficient payload (model declined to judge) | 0.021 | 0.022 |
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