Classification and Communication of Critical Findings in Emergency Radiology: A Scoping Review
Bibliographic record
Abstract
PURPOSE: To identify the published standards for the classification and communication of critical actionable findings in emergency radiology and the associated facilitators and barriers to communication and message management or dissemination of such findings. MATERIALS AND METHODS: Search terms for resources pertaining to critical findings (CFs) in emergency radiology were applied to two databases (PubMed, Embase). Screening of hits using the following pre-established inclusion and exclusion criteria were performed by three analysts with subsequent consensus discussion for discrepancies: (1) the resources include any standards for the classification and communication of imaging findings as critical, or (2) the resource discusses any facilitators to the communication of CFs, or (3) the resource discusses any barriers to the communication of CFs. Resources with explicit focus on a pediatric population or predominant focus on artificial intelligence or natural language processing were omitted. Accompanying gray literature search was used to expand included resources. Data extraction included year, country, resource type, scope or purpose, participants, context, standards to identifying or communicating CFs, facilitators and barriers, method type, recommendations, applicability, and disclosures. RESULTS: Seventy-six resources were included in the final analysis, including 16 societal or commission guidelines. Among the guidelines, no standardized list of CFs was identified, with typical recommendations suggesting application of a local policy. Communication standards included direct closed-loop communication for high acuity findings, with more flexible communication channels for less acute findings. Applied interventions for CFs management most frequently fell into four categories: electronic (n = 10), hybrid (ie, electronic or administrative) (n = 3), feedback or education (n = 5), and administrative (n = 4). CONCLUSION: There are published standards, policies, and interventions for the management of CFs in emergency radiology. Three-tier stratification (eg, critical, urgent, incidental) based on time sensitivity and severity is most common with most CFs necessitating closed-loop communication. Awareness of systemic facilitators and barriers should inform local policy development. Electronic and administrative communication pathways are useful adjuncts. Further research should offer comparative analyses of different CF interventions with regard to cost-effectiveness, notification time, and user feedback.
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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 | 0.009 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".