Emergency Department Adult Asthma Care Pathway
Bibliographic record
Abstract
Clinical pathways provide an outline for evidence-based care and can reduce variation of care across many healthcare settings including the emergency department (ED). The purpose of this study was to examine healthcare providers' perceptions of an ED Asthma Care Pathway (EDACP) and identify barriers to implementation. Following a 6-month pilot implementation of the EDACP, healthcare providers (physicians, nurses, respiratory therapists, and administrators) at 5 Ontario EDs were surveyed about the content, format, and usefulness of the pathway, as well as barriers to implementation. A focus group was convened to further explore these factors. In total, 207 of 338 mailed surveys were returned. Approximately 60% of respondents felt that the pathway was a useful tool, which enabled adherence with asthma guidelines (81%), decreased variation in patient care (79%), decreased uncertainty in patient management (73%), and increased their knowledge of best practice (87%). Time constraints and length of the pathway were common barriers. Healthcare providers perceive the EDACP to be a useful knowledge translation and guideline implementation tool, which promotes best practices. Although barriers to adoption of the tool have been identified, these may guide content revisions and inform the process for a successful provincial implementation strategy.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".