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An Evolution of Reporting: Identifying the Missing Link
In recent years, radiologic imaging has undergone tremendous technological advances and is now a pillar of diagnostic and treatment algorithms in clinical medicine. The increased complexity and volume of medical imaging has led clinicians to become ever more reliant on radiologists to both identify...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323531/ https://www.ncbi.nlm.nih.gov/pubmed/35885664 http://dx.doi.org/10.3390/diagnostics12071761 |
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author | Harsini, Sara Tofighi, Salar Eibschutz, Liesl Quinn, Brian Gholamrezanezhad, Ali |
author_facet | Harsini, Sara Tofighi, Salar Eibschutz, Liesl Quinn, Brian Gholamrezanezhad, Ali |
author_sort | Harsini, Sara |
collection | PubMed |
description | In recent years, radiologic imaging has undergone tremendous technological advances and is now a pillar of diagnostic and treatment algorithms in clinical medicine. The increased complexity and volume of medical imaging has led clinicians to become ever more reliant on radiologists to both identify and interpret patient studies. A radiologist’s report provides key insights into a patient’s immediate state of health, information that is vital when choosing the most appropriate next steps in management. As errors in imaging interpretation or miscommunication of results can greatly impair patient care, identifying common error sources is vital to minimizing their occurrence. Although mistakes in medical imaging are practically inevitable, changes to the delivery of imaging reporting and the addition of artificial intelligence algorithms to analyze clinicians’ communication skills can minimize the impact of these errors, keep up with the continuously evolving landscape of medical imaging, and ultimately close the communication gap. |
format | Online Article Text |
id | pubmed-9323531 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93235312022-07-27 An Evolution of Reporting: Identifying the Missing Link Harsini, Sara Tofighi, Salar Eibschutz, Liesl Quinn, Brian Gholamrezanezhad, Ali Diagnostics (Basel) Review In recent years, radiologic imaging has undergone tremendous technological advances and is now a pillar of diagnostic and treatment algorithms in clinical medicine. The increased complexity and volume of medical imaging has led clinicians to become ever more reliant on radiologists to both identify and interpret patient studies. A radiologist’s report provides key insights into a patient’s immediate state of health, information that is vital when choosing the most appropriate next steps in management. As errors in imaging interpretation or miscommunication of results can greatly impair patient care, identifying common error sources is vital to minimizing their occurrence. Although mistakes in medical imaging are practically inevitable, changes to the delivery of imaging reporting and the addition of artificial intelligence algorithms to analyze clinicians’ communication skills can minimize the impact of these errors, keep up with the continuously evolving landscape of medical imaging, and ultimately close the communication gap. MDPI 2022-07-21 /pmc/articles/PMC9323531/ /pubmed/35885664 http://dx.doi.org/10.3390/diagnostics12071761 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Harsini, Sara Tofighi, Salar Eibschutz, Liesl Quinn, Brian Gholamrezanezhad, Ali An Evolution of Reporting: Identifying the Missing Link |
title | An Evolution of Reporting: Identifying the Missing Link |
title_full | An Evolution of Reporting: Identifying the Missing Link |
title_fullStr | An Evolution of Reporting: Identifying the Missing Link |
title_full_unstemmed | An Evolution of Reporting: Identifying the Missing Link |
title_short | An Evolution of Reporting: Identifying the Missing Link |
title_sort | evolution of reporting: identifying the missing link |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323531/ https://www.ncbi.nlm.nih.gov/pubmed/35885664 http://dx.doi.org/10.3390/diagnostics12071761 |
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