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Record W2047291535 · doi:10.1097/tme.0b013e3181946f76

Emergency Department Adult Asthma Care Pathway

2009· review· en· W2047291535 on OpenAlexaffabout
Jennifer Olajos-Clow, Kim Szpiro, Brianna Julien, Janice P. Minard, M. Diane Lougheed

Bibliographic record

VenueAdvanced Emergency Nursing Journal · 2009
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsEmergency departmentMedicineKnowledge translationHealth careGuidelineCare pathwayBest practiceClinical pathwayFocus groupAsthmaNursingFamily medicineMedical emergencyKnowledge management

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.140
GPT teacher head0.508
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2009
Admission routes2
Has abstractyes

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