Abstract 28: Virginia Stroke Coordinators Successfully Collaborate to Improve Door to Needle Times and EMS Relationships
Bibliographic record
Abstract
Background and Issues: The Virginia Stroke Coordinators Consortium (VSCC) was founded in 2009 with a stated goal of striving for high-level evidence based stroke care for all Virginians. Purpose: In CY2015, the VSCC set two specific goals, to improve arrival to IV TPA administration (“Door to Needle”-DTN) times in Virginia and to improve our stroke team relationships with EMS. DTN Time Methods: We shared the Target Stroke Phase 2information and best practices, we regularly shared our own best practices at our monthly meetings (one live meeting per quarter) through formal presentations and informal discussion, we reviewed current journal publications related to decreasing DTN times and we shared information about and encouraged participation in nationally offered webinars on improving arrival to CT and DTN times. DTN Time Results: 29 of the 60 hospitals represented within the VSCC participate in Get with the Guidelines so we used that data as a sample of our work. To measure our success, we compared CY2014 Target Stroke Honor Roll reports to CY2015 for the state of Virginia and saw improvement (beyond the level of improvement seen at the national level) in every measure including percent of ischemic strokes that received thrombolysis, percent of patients with a DTN time of 60m or less and percent of patients with a DTN time of 45m or less (including and excluding patients with documented reasons for delay.) EMS Methods: Again, shared Target Stroke and our own best practices, shared EMS feedback methods and standardized feedback forms, included EMS in our meetings and presentations, encouraged communication with local EMS providers, worked with state wide EMS to develop template for post TPA transport. EMS Results: The VSCC was surveyed in April of 2014(n-34) and again in April 2015(n-31). We saw that the number of coordinators interacting with EMS increased to 100% of respondents, frequency of EMS interaction increased, those with monthly interaction doubled, EMS feedback increased and 48% of respondents felt their relationships with EMS had improved. (43% already felt they had a good relationship.) Conclusion: Working together, Stroke Coordinators can significantly lower door to IV TPA times and improve stroke team relationships with EMS throughout the state.
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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 | 0.023 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".