Evaluating Radiology Result Communication in the Emergency Department
Bibliographic record
Abstract
PURPOSE: To assess the pattern of result communication that occurs between radiologists and referring physicians in the emergency department setting. METHODS: An institutional review board-approved prospective study was performed at a large academic medical center with 24/7 emergency radiology cover. Emergency radiologists logged information regarding all result-reporting communication events that occurred over a 168-hour period. RESULTS: A total of 286 independent result communication events occurred during the study period, the vast majority of which occurred via telephone (232/286). Emergency radiologists spent 10% of their working time communicating results. Similar amounts of time were spent discussing negative and positive cross-sectional imaging examinations. In a small minority of communication events, additional information was gathered through communication that resulted in a change of interpretation from a normal to an abnormal study. CONCLUSIONS: Effective and efficient result communication is critical to care delivery in the emergency department setting. Discussion regarding abnormal cases, both in person and over the phone, is encouraged. However, in the emergency setting, time spent on routine direct communication of negative examination results in advance of the final report may lead to increased disruptions, longer turnaround times, and negatively impact patient care. In very few instances, does the additional information gained from the communication event result in a change of interpretation?
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".