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Record W3022477662 · doi:10.1186/s13244-020-00864-9

Enhancing clinician and patient understanding of radiology reports: a scoping review of international guidelines

2020· review· en· W3022477662 on OpenAlexaboutno aff
Caitlin Farmer, Allison Bourne, Denise O’Connor, Jeffrey G. Jarvik, Rachelle Buchbinder

Bibliographic record

VenueInsights into Imaging · 2020
Typereview
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Health and Medical Research CouncilMedical Research CouncilNational Institutes of Health
KeywordsInterventional radiologyMedicineNeuroradiologyMedical physicsRadiologyNeurology

Abstract

fetched live from OpenAlex

Imaging reports are the primary method of communicating diagnostic imaging findings between the radiologist and the referring clinician. Guidelines produced by professional bodies provide guidance on content and format of imaging reports, but the extent to which they consider comprehensibility for referring clinicians and their patients is unclear. The objective of this review was to determine the extent to which radiology reporting guidelines consider comprehensibility of imaging reports for referring clinicians and patients.We performed a scoping review of English-language diagnostic imaging reporting guidelines. We searched electronic databases (OVID MEDLINE, Embase) and websites of radiological professional organisations to identify guidelines. The extent to which the guidelines recommended essential report features such as technical information, content, format and language, as well as features to enhance comprehensibility, such as lay language summaries, was recorded.Six guidelines from professional bodies representing radiologists from the USA, Canada, Australia and New Zealand, Hong Kong, the UK and Europe were identified from the search. Inconsistencies exist between guidelines in their recommendations, and they rarely consider that patients may read the report. No guideline made recommendations about the reporting of results considering the clinical context, and none recommended features preferred by patients such as lay language summaries. This review identifies an opportunity for future radiology reporting guidelines to give greater consideration to referring clinician and patient preferences.

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 imitation

Not 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.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.159
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.159
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0180.017
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.158
GPT teacher head0.464
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainReporting
GenreReview

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".

Quick stats

Citations36
Published2020
Admission routes1
Has abstractyes

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