Impact of 24/7/365 Attending Radiologist Coverage on the Turnaround Time of Trauma-Related Imaging Studies Being Finalized Within 48 Hours in an Emergency Radiology Department, Offering a Perspective from a Tertiary Care Hospital
Bibliographic record
Abstract
OBJECTIVE: To offer an evidence-based account of the effect of 24/7/365 attending radiologist coverage on the turnaround time (TAT) of trauma-related radiographs finalized within 48 hours of exam completion, drawing data from an emergency radiology department of a tertiary care hospital in Vancouver, British Columbia. MATERIALS AND METHODS: This was a retrospective chart review, where TATs of imaging studies for a sample of trauma patients, who had visited the emergency department of the Vancouver General Hospital between two time periods, January 1 to September 30, 2013, and January 1 to September 30, 2017, were noted. RESULTS: In models adjusted for patient's age, sex, and seasonality, the 24/7/365 attending radiologist coverage was associated with an average of 19.1 (95% confidence interval [CI]: 18.7-19.4) hours of reduction in time from exam completion to report finalization by an attending radiologist. Approximately 11.3 (95% CI: 18.7-19.4) hours was due to reduction in time from exam completion to preliminary diagnosis of reports. When the impact of the increased number of radiology staff in 2017 was removed in the analysis, the overall TAT was reduced by 13.3 (95% CI: 13.0-13.6) hours and the time from exam completion to preliminary report was reduced by 7.8 (95% CI: 7.6-8.1) hours. LIMITATION: Since we have used a simple random sample (SRS) for this research, this study does not describe the burden of reports that are finalized in the emergency and trauma radiology department during the given time periods. CONCLUSION: Our pilot study demonstrates that the implementation of 24/7/365 attending radiology coverage significantly reduces TAT for finalized radiology reports of all modalities of trauma imaging studies in an emergency and trauma radiology department. POLICY IMPLICATION: This research serves the contemporary health-care administration, policymaking information needs by providing the evidence for significantly reduced TAT of finalized radiology reports from a Canadian perspective.
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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 | 0.006 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".