Whitney Palmer

Natural Language Processing Underutilized in Radiology Despite Advanced Capabilities

Published on the Sept. 22, 2011, DiagnosticImaging.com website

By Whitney L.J. Howell

Natural language processing, considered the next generation of voice recognition software, makes it easier for you to summarize, find, and retrieve data from radiology reports. But a recent study shows many of you still aren’t using it.

Nearly 50 years ago, speech recognition software debuted on the healthcare scene, and providers used it to record radiology report findings. Technology improvements have taken the software to the next level with natural language processing (NLP), and it now plays a significant role in quality improvement efforts, said Ronilda Lacson, MD, a radiology research associate at Brigham & Women’s Hospital. NLP takes the voice-created narratives and makes them structured and searchable.

“NLP makes sure physicians report findings appropriately,” Lacson said. “They can record information in such a concise form so that when patient histories are pulled for review they’re like a thin cut of focused data.”

In a study published in the September Journal of the American College of Radiology, Lacson and her colleagues identified three main uses for NLP. The software can pull records that meet specific criteria to support effective outcomes research. Various versions also let you pinpoint specific data points, such as individual imaging findings, for analysis and quality improvements. However, the most valuable, long-term NLP use, Lacson said, is the brief reports it can create to highlight key content and critical findings. Other radiologists can study these summaries to improve their future documentation.

To read the article in its entirety: http://www.diagnosticimaging.com/voice-recognition/content/article/113619/1955806

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