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Record W3007242194 · doi:10.1177/0846537119899268

Evaluating Radiology Result Communication in the Emergency Department

2020· article· en· W3007242194 on OpenAlexaff
Siobhan B. O’ Neill, Arvind Vijayasarathi, Savvas Nicolaou, Frances Walstra, Noriko Salamon, Peter L. Munk, Faisal Khosa

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineEmergency departmentMedical emergencyPhoneTurnaround timeEmergency medicineNursingOperations management

Abstract

fetched live from OpenAlex

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?

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.101
GPT teacher head0.390
Teacher spread0.289 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2020
Admission routes1
Has abstractyes

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