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.
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.
Neuroimaging Clin N Am. 2020 Aug;30(3):379-391. doi: 10.1016/j.nic.2020.05.002. Epub 2020 Jun 11.
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.
放射科医生必须将头部和颈部成像中的复杂信息转化为文本报告，以便临床医生、患者和放射科医生能够理解和使用这些报告，从而进行患者护理、研究和质量计划。通过使用具有约束答案和术语的定义问题，报告中的常见数据元素允许放射科医生纳入最佳实践标准，并改善信息交流，而不受个人报告风格的影响。使用头部和颈部报告的常见数据元素有可能改善结果、减少错误，并不仅为人类而且为未来的机器学习系统转换数据使用。
