Common Data Elements in Head and Neck Radiology Reporting
Authors
Anandh G. Rajamohan, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA. Electronic address: anandh.rajamohan@med.usc.edu.
Vishal Patel, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA; USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Keck School of Medicine, 2025 Zonal Avenue, Los Angeles, CA 90033, USA.
Nasim Sheikh-Bahaei, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA.
Chia-Shang J. Liu, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA.
John L. Go, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA.
Paul E. Kim, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA.
Wende Gibbs, Department of Radiology, Mayo Clinic School of Medicine, 18522 North 96th Way, Scottsdale, AZ 85255, USA.
Jay Acharya, Department of Radiology, Division of Neuroradiology, University of Southern California, Keck School of Medicine, 1500 San Pablo Street, Second Floor, Los Angeles, CA 90033, USA.
Abstract
Radiologists must convert the complex information in head and neck imaging into text reports that can be understood and used by clinicians, patients, and fellow radiologists for patient care, research, and quality initiatives. Common data elements in reporting, through use of defined questions with constrained answers and terminology, allow radiologists to incorporate best practice standards and improve communication of information regardless of individual reporting style. Use of common data elements for head and neck reporting has the potential to improve outcomes, reduce errors, and transition data consumption not only for humans but future machine learning systems.
Medical Subject Headings
Common Data Elements; Head and Neck Neoplasms (diagnostic imaging); Humans; Magnetic Resonance Imaging (methods); Radiology Information Systems (standards); Tomography, X-Ray Computed (methods)
Publication Date
8-1-2020
Publication Title
Neuroimaging clinics of North America
Digital Object Identifier (DOI)
10.1016/j.nic.2020.05.002
Recommended Citation
Rajamohan, Anandh G.; Patel, Vishal; Sheikh-Bahaei, Nasim; Liu, Chia-Shang J.; Go, John L.; Kim, Paul E.; Gibbs, Wende; and Acharya, Jay, "Common Data Elements in Head and Neck Radiology Reporting" (2020). Neuroradiology. 13.
https://scholar.barrowneuro.org/neuroradiology/13
