Literature DB >> 24809319

Preferences for structured reporting of measurement data: an institutional survey of medical oncologists, oncology registrars, and radiologists.

Adam R Travis1, Merlijn Sevenster2, Rajiv Ganesh3, Joost F Peters4, Paul J Chang5.   

Abstract

RATIONALE AND
OBJECTIVES: The aim of this study was to determine whether key radiology report "consumers" in our institution prefer structured measurement reporting in a dedicated report section over the current practice of embedding measurements throughout the "Findings" section, given the availability of new tools for quantitative imaging interpretation that enable automated structured reporting of measurement data.
MATERIALS AND METHODS: Oncologic clinicians and radiologists at our institution were surveyed regarding their preferences for a standard report versus three reports each having uniquely formatted dedicated "Measurements" sections and regarding their impressions of various characteristics of report quality demonstrated by these reports. The online survey was completed by 25 radiologists, 16 oncologists, and 17 oncology nurses and research assistants (registrars).
RESULTS: Aggregation of respondents' preferences by group into single orderings using the Kemeny-Young method revealed that both oncology groups preferred all proposed reports to the standard report but that radiologists only preferred two of the proposed reports to the standard report. All preferences for proposed reports in the two oncology groups were statistically significant based on Wilcoxon tests, but the preference for only one of the proposed reports was significant for radiologists. Additional results suggest that these preferences are driven by respondent favor for the readability of and confidence conveyed by the proposed reports compared to the standard report.
CONCLUSIONS: Oncologic clinicians responding to our survey preferred communication of lesion measurements in a separate report section to the current practice of embedding measurements throughout the "Findings" section, based on their assessments of reports containing simulated measurement sections assembled from a single sample report using standardized formatting.
Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Keywords:  AIM; Annotation and Image Markup; RECIST; Structured reporting; quantitative imaging

Mesh:

Year:  2014        PMID: 24809319     DOI: 10.1016/j.acra.2014.02.008

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  12 in total

1.  Quantitative Radiology Reporting in Oncology: Survey of Oncologists and Radiologists.

Authors:  Les R Folio; Chelsye J Nelson; Menashe Benjamin; Ayelet Ran; Guy Engelhard; David A Bluemke
Journal:  AJR Am J Roentgenol       Date:  2015-09       Impact factor: 3.959

Review 2.  Natural Language Processing Technologies in Radiology Research and Clinical Applications.

Authors:  Tianrun Cai; Andreas A Giannopoulos; Sheng Yu; Tatiana Kelil; Beth Ripley; Kanako K Kumamaru; Frank J Rybicki; Dimitrios Mitsouras
Journal:  Radiographics       Date:  2016 Jan-Feb       Impact factor: 5.333

3.  Survey of radiologists and emergency department providers after implementation of a global radiology report categorization system.

Authors:  Eric L Tung; Elizabeth H Dibble; Gaurav Jindal; Jonathan S Movson; David W Swenson
Journal:  Emerg Radiol       Date:  2020-07-28

Review 4.  Multimedia-enhanced Radiology Reports: Concept, Components, and Challenges.

Authors:  Les R Folio; Laura B Machado; Andrew J Dwyer
Journal:  Radiographics       Date:  2018 Mar-Apr       Impact factor: 5.333

5.  Improvement of radiology reporting in a clinical cancer network: impact of an optimised multidisciplinary workflow.

Authors:  A W Olthof; J Borstlap; W W Roeloffzen; P M C Callenbach; P M A van Ooijen
Journal:  Eur Radiol       Date:  2018-04-20       Impact factor: 5.315

6.  Adnexal mass staging CT with a disease-specific structured report compared to simple structured report.

Authors:  Andrea Franconeri; Johannes Boos; Jieming Fang; Anuradha Shenoy-Bhangle; Michelle Perillo; Catherine J Wei; Leslie Garrett; Katharine Esselen; Liu Fong; Olga R Brook
Journal:  Eur Radiol       Date:  2019-02-28       Impact factor: 5.315

7.  Radiology Reports With Hyperlinks Improve Target Lesion Selection and Measurement Concordance in Cancer Trials.

Authors:  Laura B Machado; Andrea B Apolo; Seth M Steinberg; Les R Folio
Journal:  AJR Am J Roentgenol       Date:  2017-02       Impact factor: 3.959

8.  Usage of structured reporting in radiological practice: results from an Italian online survey.

Authors:  Lorenzo Faggioni; Francesca Coppola; Riccardo Ferrari; Emanuele Neri; Daniele Regge
Journal:  Eur Radiol       Date:  2016-08-29       Impact factor: 5.315

Review 9.  Methods and challenges in quantitative imaging biomarker development.

Authors:  Richard G Abramson; Kirsteen R Burton; John-Paul J Yu; Ernest M Scalzetti; Thomas E Yankeelov; Andrew B Rosenkrantz; Mishal Mendiratta-Lala; Brian J Bartholmai; Dhakshinamoorthy Ganeshan; Leon Lenchik; Rathan M Subramaniam
Journal:  Acad Radiol       Date:  2015-01       Impact factor: 3.173

10.  Structured reports of pelvic magnetic resonance imaging in primary endometrial cancer: Potential benefits for clinical decision-making.

Authors:  Yi Liu; Zonghao Feng; Shengtang Qin; Jiejin Yang; Chao Han; Xiaoying Wang
Journal:  PLoS One       Date:  2019-03-25       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.