Beyond Watson: AI in Radiology
Published on the April 14, 2016, DiagnosticImaging.com website
By Whitney L.J. Howell
Imagine this: your hospital administrator asks you to help reduce the length of inpatient stays and they need a plan within a week. Could you do it?
Chances are, most of you couldn’t. But, the technology to mine and analyze your data does exist. Much like your daily Google searches, it’s possible to input your search criteria, click Enter, and have answers at your fingertips in seconds.
Doing so is part of radiology’s push toward using big data, said Woojin Kim, MD, director of innovation at Montage Healthcare Solutions, Inc.
“Radiology doesn’t yet have big data like other industries, but that’s changing rapidly. People want access to data to be able to turn insight into action,” he said. “Providers want quick easy access to radiology reports, and they want to mine through data intelligently for research and quality and performance improvements.”
That’s why Kim, along with William Boonn, MD, Curtis Langlotz, MD, and Rajan Agarwal, MD, co-founded Montage. Its products use proprietary natural language processing to search and pull information from your RIS and electronic medical record (EMR), pinpointing clinical findings to augment business performance and clinical-quality analytics.
To read the remainder of the article at its original location: http://www.diagnosticimaging.com/pacs-and-informatics/beyond-watson-ai-radiology
No Such Thing as Big Data in Health Care
Published on the Dec. 3, 2014, DiagnosticImaging.com website
When it comes to big data, health care doesn’t really have any. And, for radiology, that’s a good thing. Small and medium data will work just fine – especially for testing and designing new reimbursement models, according to speakers at this year’s Radiological Society of North America (RSNA) meeting.
Industry experts at this year’s RSNA say the data hospitals and health care systems already have can help providers identify ways to maximize their influence in the design of any future payment models.
“We’re currently in the lowest life form of payment policy. We get paid for events – it’s a transactional delivery system,” said Richard Duszak, MD, vice chair for health policy and practice, department of radiology and imaging sciences, Emory University School of Medicine. “Increasingly, we’re moving to models where we’ll be paid by encounters and engagements.”
The question, he said, is how those models will be designed to ensure radiologists receive appropriate reimbursement for services rendered in a correctly incentivized way. To date, there’s no clear-cut answer, but there are steps radiologists can take – armed with small-to-medium data – to ensure their seat at the decision table.
To read the article in its entirey at its original location: http://www.diagnosticimaging.com/rsna-2014/no-such-thing-big-data-health-care
Who am I?
I’m a seasoned reporter, writer, freelancer and public relations specialist with a master’s degree in international print journalism from The American University in Washington, D.C.
I launched my journalism career as a stringer for UPI on Sept. 11, 2001, on Capitol Hill. That day led to a two-year stint as a daily political reporter in Montgomery County, Md. As a staff writer for the Association of American Medical Colleges, a public relations specialist for the Duke University Medical Center and the public relations director for the UNC-Chapel Hill School of Nursing, I’ve earned in-depth experience in covering health care, including academic medicine, health care reform, women’s health, pediatrics, radiology, and Medicare.
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