Literature DB >> 32398536

The Use of Anatomical Side Markers in General Radiology: A Systematic Review of the Current Literature.

Lilian Chung1, Saravana Kumar1, Joanne Oldfield1, Maureen Phillips1, Megan Stratfold2.   

Abstract

OBJECTIVES: The use of an anatomical side marker (ASM) on x-rays, be it digital or radiopaque, is an important quality and safety concept within general radiology. Using radiopaque ASMs is best practice, and lack of any ASMs may have dire consequences in terms of patient safety. To date, there have been no systematic reviews investigating the use of ASMs in clinical practice.
METHODS: A systematic search of electronic databases (CINAHL, the Cochrane Library, Medline, EMBASE, ERIC, and JBI) from inception to March 1, 2018, was undertaken. Gray literature searching (through Google) and pearling was conducted. Methodological quality was assessed using a modified version of the McMaster Critical Appraisal tool for quantitative studies. A customized data extraction tool was developed, which included characteristics of the studies.
RESULTS: Of 624 studies, 7 studies met the eligibility criteria. Despite diverse study designs, collectively, the studies demonstrated that only a small number of x-rays did not include an ASM. On x-rays that did use a radiopaque ASM, most of them were positioned in the primary radiation field. A noticeable shift in practice from the use of radiopaque ASMs to digital ASM was also identified. Multifaceted barriers were reported for the use of ASM in routine clinical practice.
CONCLUSIONS: Although missing ASMs on x-rays were a small feature, findings from this review highlight opportunities for improvement and a need to ameliorate barriers for ASM use.
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2022        PMID: 32398536     DOI: 10.1097/PTS.0000000000000716

Source DB:  PubMed          Journal:  J Patient Saf        ISSN: 1549-8417            Impact factor:   2.844


  1 in total

1.  Determining the anatomical site in knee radiographs using deep learning.

Authors:  Anton S Quinsten; Lale Umutlu; Michael Forsting; Kai Nassenstein; Aydin Demircioğlu
Journal:  Sci Rep       Date:  2022-03-07       Impact factor: 4.379

  1 in total

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