Low-acuity presentations to the emergency department in Canada: exploring the alternative attempts to avoid presentation
Bibliographic record
Abstract
OBJECTIVE: ED visits have been rising year on year worldwide. It has been suggested that some of these visits could be avoided if low-acuity patients had better primary care access. This study explored patients' efforts to avoid ED presentation and alternative care sought prior to presentation. METHODS: Consecutive adult patients presenting to three urban EDs in Edmonton, Canada, completed a questionnaire collecting demographics, actions attempted to avoid presentation and reasons for presentation. Survey data were cross-referenced to a minimal patient dataset containing ED and demographic information. RESULTS: A total of 1402 patients (66.5%) completed the survey. Although 89.3% of the patients felt that the ED was their best care option, the majority of patients (60.1%) sought alternative care or advice prior to presentation. Men, individuals who presented with injury only, and individuals with less than a high school education were all less likely to seek alternative care. Alternative care actions included visiting a physician (54.1%) or an alternative healthcare professional (eg, chiropractor, physiotherapist, etc; 21.2%), calling physician offices (47%) or the regional health information line (13%). Of those who called their physicians, the majority received advice to present to the ED (67.5%). CONCLUSIONS: Most low-acuity patients attempt to avoid ED presentation by seeking alternative care. This analysis identifies groups of individuals in the study region who are less likely to seek alternative care first and may benefit from targeted interventions/education. Other regions may wish to complete a similar profile to determine which patients are less likely to seek alternative care first.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".