Can a Generative AI Platform Enhance Workflow Triage and Efficiency in Radiology?
Through the use of a multimodal system, Viz Assist provides generative AI summaries of patient histories that may ehance care coordination and facilitate more timely interventions.
Could time-consuming manual mining of electronic health record (EHR) data and other patient history information be a thing of the past?
Based upon a combination of ambient listening and EHR data, the newly launched multimodal Viz Assist (Viz.ai) platform provides generative artificial intelligence (AI) patient summaries, according to Viz.ai. The company said Viz Assist utilizes autonomous AI agents that zero in on key clinical signals and relevant information to help reduce cognitive burden for radiologists and other clinicians.
The company said Viz Assist utilizes autonomous AI agents that zero in on key clinical signals and relevant information in patient data to help reduce cognitive burden for radiologists and other clinicians. (Image courtesy of Viz.ai.)
Emphasizing a goal of streamlining clinical documentation, Viz.ai noted that the capabilities with Viz Assist may be expanded over time to deliver coding recommendations based on the combination of imaging, ambient listening and EHR data for patients.
“Viz Assist represents a remarkable step forward in health care,” said Peter Kan, M.D., chair of the Department of Neurosurgery at the University of Texas Medical Branch. “This platform does far more than simply send alerts — it works seamlessly in the background to identify critical patients, automates clinical documentation which saves us time, delivers the most relevant information in real time, and coordinates action across the entire care team. In many ways, it has the potential to function like an added expert on staff — one that’s available 24/7.”
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