Evaluation of Radiology Reports by the Emergency Department Clinical Providers: A Message to Radiologists
Bibliographic record
Abstract
OBJECTIVES: This study is an evaluation of the emergency department (ED) satisfaction with the current radiologic reporting system used at a major Northeastern academic medical center. The radiology reports are the main form of communication and usually the final product of any radiological investigation delivered to clinicians. The aim of this study was to improve current radiology reporting practices and to better tailor reports to match the needs and expectations of ED clinicians. METHODS: A 9-question online survey was sent to ED residents, fellows, faculty, and nurse practitioners/advanced practice providers at a major Northeastern academic medical center in the United States. For the open-ended section, coding and emergent theme categorization was conducted for quantification of responses. The survey was designed to evaluate the attitudes toward the structure, style, form, and wording used in reports. RESULTS: The response rate was 48.6% (68/140). The ED respondents were generally satisfied with radiology reports, their language, vocabulary, and clarity. They preferred the impression section to be before the findings in simple examinations and to stratify the reports according to emergency status for complex examinations. They did not like extended differential, hedge terms, and delayed reporting. Additionally, ED respondents recommended focused, fast reporting with considerable changes toward a more standardized report. CONCLUSIONS: This evaluation delivered a list of actionable recommendations. The top recommendation is to standardize reporting structure, style, and lexicon, in addition to being focused, timely, and brief.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.123 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".