Do elective surgical and medical admissions impact emergency department length of stay measurements?
Bibliographic record
Abstract
BACKGROUND: Emergency department access block is a growing problem in emergency departments across Canada. Access block is defined as hospital occupancy >85% causing emergency department overcrowding. Hospital overcrowding leads to prolonged emergency department wait times, and delays in the transfer of admitted patients from the emergency department to inpatient beds. The relationship between elective admissions to hospital and emergency department wait times has not been adequately assessed. We undertook a simple linear regression analysis of the impact of elective admissions to hospital on emergency department length of stay. METHODS: Linear regression analysis of the number of daily elective admissions to adult acute care beds in the Calgary Health Region in the year 2004 and the daily median emergency department length of stay was done to establish the relationship between elective admissions and Emergency Department length of stay. RESULTS: 37,007 patients were admitted to adult acute care beds via the emergency department and 46,020 patients were admitted to adult acute care beds by all other routes. Regression analysis determined that there was no relationship between daily emergency department length of stay and the number of elective admissions per day. CONCLUSION: For the year 2004, in the Calgary Health Region, elective acute care admissions to hospital had no relationship to emergency department length of stay for patients admitted via the emergency department. Further study is required to determine causative factors that prolong Emergency Department length of stay. Emergency departments across Canada continue to struggle with the demands of providing high quality care with diminishing resources.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".