U TILIZATION AND I MPACT OF A MBULANCE D IVERSION AT THE C OMMUNITY L EVEL
Bibliographic record
Abstract
OBJECTIVE: To evaluate the utilization and impact of ambulance diversion in the metropolitan area of Syracuse, New York. METHODS: This was a retrospective review of the ambulance diversion system operated by the hospitals of Syracuse, New York. This system allows each emergency department to divert incoming ambulances during periods of extreme overcrowding. Data collected included numbers of hours on ambulance diversion by hospital, numbers of hours when all four hospitals were on diversion simultaneously, and numbers of ambulances received while the hospitals were on and off diversion. RESULTS: For three of the five years evaluated, ambulance diversion hours were most numerous during the period between January and March. For the most recent year studied (2000), ambulance diversion hours did not decline after the first quarter. During periods of diversion, hospital emergency departments received 30%-50% fewer ambulances than they did while open. CONCLUSION: This study demonstrated that, in Syracuse, New York, ambulance diversion was once a seasonal phenomenon, but is increasingly occurring throughout the year because of staff and resource limitations. It also demonstrated that ambulance diversion can be employed to reduce numbers of incoming transports.
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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 | 0.009 |
| 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 | 0.000 | 0.000 |
| 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".