Bibliographic record
Abstract
INTRODUCTION: This study serves to identify the reasons for unscheduled return visits to the emergency department (ED), paying particular attention to system, physician and patient factors. Its purpose is to highlight inadequacies and plan strategies to reduce re-attendance. METHODS: All patients returning to the ED within 72 hours of initial visit were identified between January 2005 and June 2005. 842 cases were reviewed to identify reasons for unscheduled returns. RESULTS: Unscheduled return visits accounted for two percent of patient encounters with the younger mobile group of patients contributing the largest number. Patients presenting with abdominal pain constituted a quarter of unscheduled returns, where more than half were admitted. Possible causes were lack of rehydration and lack of proper discharge advice to these patients. The assessment and disposition of abdominal pain patients with uncertain aetiology was a major category and 68.7 percent of missed diagnosis came from this group. There was a significant difference in the unscheduled return rates between the senior and junior doctors. There was minimal morbidity and no mortality among patients who returned to the ED for the second time. CONCLUSION: A proposed strategy to reduce the number of unscheduled returns would be to target patients with abdominal pain with more liberal hydration strategies. Discharge advice with information about expected prognosis and specific signs and symptoms to look out for should be included. Educational sessions and better supervision of junior staff emphasising acute abdominal conditions should be actively incorporated to avoid associated morbidities with a missed diagnosis.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".