UK Survey of emergency physicians’ priorities for clinical decision rules
Bibliographic record
Abstract
One of the first stages in the development of new clinical decision rules (CDRs) is determination of perceived need because this is the most important predictor of ultimate adoption. This study examined the current use of two common CDRs and the clinical priorities of UK emergency physicians (EPs) for the development of future CDRs. Methods: The authors administered an e-mail and postal survey to a random sample of 350 members of the British Association of Emergency Medicine (total membership n=1700). Results: The total response rate was 44.5% (155/350). The respondents were predominantly male (67.7%), with a mean age of 44.0 years (SD +/- 10), and a mean of 10.8 years experience (SD +/- 7). Regarding the two pre-existing Canadian C-spine and CT head rules, 62% of responders were aware of these rules. Regarding a proposed acute headache CDR, 94.6% of those surveyed indicated that they would consider using a highly sensitive and well-validated decision rule if it was developed. The top priorities in the four main categories were admission with anterior chest pain (42.8%), imaging for suspected transient ischaemic attack (34.5%), management of serious vertigo (29.7%) and investigation of febrile child <36 months (40.6%), respectively. Discussion: This UK survey identified the sampled emergency physicians’ priorities for the future development of CDRs. The top priority was investigation of the febrile child < 36 months. These results will be valuable to researchers for future development of CDRs in emergency medicine in the UK.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".