Literature DB >> 17467614

Radiology reporting, past, present, and future: the radiologist's perspective.

Bruce I Reiner1, Nancy Knight, Eliot L Siegel.   

Abstract

Although imaging technologies have undergone dramatic evolution over the past century, radiology reporting has remained largely static, in both content and structure. Existing free-text (prose) reports have been criticized for a number of inherent deficiencies, including inconsistencies in content, structure, organization, and nomenclature. A number of new initiatives and technologies now present the radiology community with the unique opportunity to fundamentally change the radiology report from free to structured text. These new developments include a standardized nomenclature (RadLex), automated information technologies (picture archiving and communications systems and electronic medical records), and automated data tracking and analysis software (natural-language processing). Despite the increasing availability of these tools and technologies for revolutionizing reporting, clinical, psychologic, legal, and economic challenges have collectively limited structured reporting to mammography. These challenges are most evident in the current environment of heightened expectations for improved quality, timeliness, and communication, along with increasing stress, fatigue, and malpractice concerns. In conclusion, the authors present an alternative to traditional reporting that attempts to address some of these diverse challenges while incorporating the aforementioned initiatives and technologic developments. This approach uses a graphical symbol language that is directly mapped to a standardized lexicon (RadLex) and is automatically converted into a structured hierarchical text report, which can then be much more easily searched and analyzed.

Entities:  

Mesh:

Year:  2007        PMID: 17467614     DOI: 10.1016/j.jacr.2007.01.015

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  41 in total

1.  Improving communication of diagnostic radiology findings through structured reporting.

Authors:  Lawrence H Schwartz; David M Panicek; Alexandra R Berk; Yuelin Li; Hedvig Hricak
Journal:  Radiology       Date:  2011-04-25       Impact factor: 11.105

2.  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

3.  Prepopulated radiology report templates: a prospective analysis of error rate and turnaround time.

Authors:  C M Hawkins; S Hall; J Hardin; S Salisbury; A J Towbin
Journal:  J Digit Imaging       Date:  2012-08       Impact factor: 4.056

4.  The role of key image notes in CT imaging study interpretation.

Authors:  Shu-Feng Fan; Zhe Xu; Hai-Qing He; Jian-Rong Ding; Gao-Jun Teng
Journal:  J Digit Imaging       Date:  2011-04       Impact factor: 4.056

Review 5.  Customization of medical report data.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2010-08       Impact factor: 4.056

6.  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

7.  Creating and curating a terminology for radiology: ontology modeling and analysis.

Authors:  Daniel L Rubin
Journal:  J Digit Imaging       Date:  2007-09-15       Impact factor: 4.056

8.  [IT systems in radiology and IT systems for radiologists].

Authors:  J-M Hempel; F Jungmann; R Klöckner; D Pinto dos Santos; H Kurz; C Düber
Journal:  Radiologe       Date:  2014-01       Impact factor: 0.635

Review 9.  Strategies for radiology reporting and communication. Part 1: challenges and heightened expectations.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

10.  Automatic Normalization of Anatomical Phrases in Radiology Reports Using Unsupervised Learning.

Authors:  Amir M Tahmasebi; Henghui Zhu; Gabriel Mankovich; Peter Prinsen; Prescott Klassen; Sam Pilato; Rob van Ommering; Pritesh Patel; Martin L Gunn; Paul Chang
Journal:  J Digit Imaging       Date:  2019-02       Impact factor: 4.056

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