Recent years have seen the focus of healthcare shift from service delivery to patient outcomes. In radiology, the spotlight on improving the quality of patient care has also drawn attention to the relationship between radiologists and referring physicians.
When physicians know their patients receive high-quality care from a particular radiologist, they’ll refer to that radiologist again. If they believe the radiologist did not provide adequate care, they’ll direct their patients somewhere else.
But the way and extent to which radiology recommendations and diagnoses are captured differs between organizations. Processes used to communicate this information vary as well. Often too, the radiologist has no oversight of a patient’s care pathway following a scan. All of this leads to communication gaps between radiologists, referring physicians and ultimately patients.
For this discussion, we have brought together leaders in radiology workflow and patient care to explore questions like: What can be done to strengthen communication between radiologists and referring physicians? And what role can AI and NLP technology play in supporting this?
Nina Kottler, MD, MS
Associate Chief Medical Officer, Clinical AI at Radiology Partners
With a background in applied mathematics and optimization theory, Nina uses imaging informatics to improve quality and drive value in radiology. She leads the Data Science and Analytics division at Radiology Partners, and oversees clinical AI for the practice.
Jim Anderson, MD
Professor of Neuroradiology at Oregon Health & Science University (OHSU)
After spending 4 years in private practice following Radiology residency, Dr. Anderson, MD, found his passion for teaching, mentoring, and Neuroradiology at Vanderbilt University. He served on the ACGME Radiology Review Committee for 8 years, 5 of which as Chair.
Kevin Seals, MD
Attending Radiologist at Cedars-Sinai
Kevin Seals, MD, is a physician with background in bioengineering and expertise in medical imaging and machine learning. Dr Seals built the first radiology chatbot using deep learning, to help physicians make smarter choices and take better care of their patients.
Omri Sivan
Co-founder & CTO at Agamon
Omri Sivan heads up Agamon's data science team. He has led the development of Agamon's proprietary Deep Learning and Natural Language Processing technology, and overseas ongoing work to train and further develop the models that power solutions like Agamon Coordinate.
Nina Kottler, MD, MS
Associate Chief Medical Officer, Clinical AI at Radiology Partners
With a background in applied mathematics and optimization theory, Nina uses imaging informatics to improve quality and drive value in radiology. She leads the Data Science and Analytics division at Radiology Partners, and oversees clinical AI for the practice.
Jim Anderson, MD
Professor of Neuroradiology at Oregon Health & Science University (OHSU)
After spending 4 years in private practice following Radiology residency, Dr. Anderson, MD, found his passion for teaching, mentoring, and Neuroradiology at Vanderbilt University. He served on the ACGME Radiology Review Committee for 8 years, 5 of which as Chair.
Kevin Seals, MD
Attending Radiologist at Cedars-Sinai
Kevin Seals, MD, is a physician with background in bioengineering and expertise in medical imaging and machine learning. Dr Seals built the first radiology chatbot using deep learning, to help physicians make smarter choices and take better care of their patients.
Omri Sivan
Co-founder & CTO at Agamon
Omri Sivan heads up Agamon's data science team. He has led the development of Agamon's proprietary Deep Learning and Natural Language Processing technology, and overseas ongoing work to train and further develop the models that power solutions like Agamon Coordinate.
Agamon Health is a digital health company that closes care gaps by leveraging Generative AI to identify required follow-ups and behavioral-based automation to coordinate the operational workflow.
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