Assigning responsibility to close the loop on radiology test results
Bibliographic record
Abstract
Failure to follow-up on test results represents a serious breakdown point in the diagnostic process which can lead to missed or delayed diagnoses and patient harm. Amidst discussions to ensure fail-safe test result follow-up, an important, yet under-discussed question emerges: how do we determine who is ultimately responsible for initiating follow-up action on the tests that are ordered? This seemingly simple question belies its true complexity. Although many of these complexities are also applicable to other diagnostic specialities, the field of medical imaging provides an ideal context to discuss the challenges of attributing responsibility of test result follow-up. In this review, we summarize several key concepts and challenges in the context of critical results, wet reads, and incidental findings to stimulate further discussion on responsibility issues in radiology. These discussions could help establish reliable closed-loop communication to ensure that every test result is sent, received, acknowledged and acted upon without failure.
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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 | 0.086 | 0.289 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".