Literature DB >> 20648424

Radiological report: expectations of clinicians.

Nurullah Doğan1, Zeynep Nigar Varlibaş, Ozge Petek Erpolat.   

Abstract

PURPOSE: Although there have been many publications on composing an accurate radiological report, they usually do not include an assessment of the clinicians' expectations from a radiological report. In this study, we aimed to assess the clinicians' expectations and preferences in terms of radiology report style and content.
MATERIALS AND METHODS: A multiple-choice questionnaire, containing 19 questions, was formed. Two-hundreds clinicians, working either in a university hospital or a public hospital, were allocated into 4 groups which included equal number of clinicians from surgery and internal medicine departments. Questionnaire was applied to participants by face-to-face interview. Results were analyzed for each group using Pearson chi-square test.
RESULTS: No statistically significant difference was found among four groups except for the 16th question which was about the image format pertaining to the report (CD/DVD or negative film). It has been determined that clinicians preferred detailed, standardized radiological reports with complete sections (i.e., clinical information, technique, findings, conclusion, recommendations).
CONCLUSION: This study provided essential data for radiologists to write more effective reports.

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Year:  2010        PMID: 20648424     DOI: 10.4261/1305-3825.DIR.2820-09.1

Source DB:  PubMed          Journal:  Diagn Interv Radiol        ISSN: 1305-3825            Impact factor:   2.630


  4 in total

1.  Influence of radiology report format on reading time and comprehension.

Authors:  Elizabeth A Krupinski; E Tyler Hall; Stacy Jaw; Bruce Reiner; Eliot Siegel
Journal:  J Digit Imaging       Date:  2012-02       Impact factor: 4.056

2.  Structured reporting: a fusion reactor hungry for fuel.

Authors:  Jan M L Bosmans; Emanuele Neri; Osman Ratib; Charles E Kahn
Journal:  Insights Imaging       Date:  2014-12-05

Review 3.  Big data, artificial intelligence, and structured reporting.

Authors:  Daniel Pinto Dos Santos; Bettina Baeßler
Journal:  Eur Radiol Exp       Date:  2018-12-05

4.  Structured report data can be used to develop deep learning algorithms: a proof of concept in ankle radiographs.

Authors:  Daniel Pinto Dos Santos; Sebastian Brodehl; Bettina Baeßler; Gordon Arnhold; Thomas Dratsch; Seung-Hun Chon; Peter Mildenberger; Florian Jungmann
Journal:  Insights Imaging       Date:  2019-09-23
  4 in total

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