Impact of emergency department surge and end of shift on patient workup and treatment prior to referral to internal medicine: a health records review
Bibliographic record
Abstract
BACKGROUND: The goal of this study was to determine if ED surge and end-of-shift assessment of patients affect the extent of diagnostic tests, therapeutic interventions and accuracy of diagnosis prior to referral to internal medicine. METHODS: This study was a health records review of consecutive patients referred to the internal medicine service with an ED diagnosis of heart failure, chronic obstructive pulmonary disease (COPD) or sepsis starting 1 December 2013 until 100 cases for each condition had been obtained. We developed a scoring system in consultation with emergency and internal medicine physicians to uniformly assess the completeness of treatments and investigations performed. These scores, expressed as percentage of possible points, were compared at high and low surge levels and at middle and end of shift at time of patient referral. End of shift was defined as 7:30-8:30, 15:30-16:30 and 23:30-00:30 as our shift changes occur at 8:00, 16:00 and 24:00. Rate of admission, diversion to other services and diagnosis disagreements were also assessed. RESULTS: We included 308 patients (101 heart failure, 101 COPD, 106 sepsis) with a mean age of 74.7. Comparing middle of shift to end of shift, the mean scores were 91.9% versus 91.8% (difference 0.1% (95% CI -2.4 to 3.0)) for investigations and 73.0% versus 70.4% (difference 2.6% (95% CI -1.8 to 7.4)) for treatments. Comparing low to high surge times, the mean scores were 92.1% versus 91.7% (difference 0.4% (95% CI -1.2 to 2.4)) for investigations and 71.4% versus 73.6% (difference -2.2% (95% CI -5.6 to 1.3)) for treatments. We found low rates of diversion to alternate services (8.9% heart failure, 0% COPD, 6.6% sepsis) and low rates of diagnosis disagreement (4.0% heart failure, 10.9% COPD, 8.5% sepsis). CONCLUSIONS: We found no evidence that surge levels and end of shift impact the extent of investigations and treatments provided to patients diagnosed in the ED with heart failure, COPD or sepsis and referred to internal medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 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 teacher head, 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".