Natural Language Processing technology can take transcribed text, structure it into computable data, and apply SNOMED CT and other terminologies or codes for richer data abstraction and analysis.

During an educational session at the American Health Information Management Association annual convention, Oct. 1-6 in Salt Lake City, two NLP experts will walk through the technology and its potential. They'll cover tagging and preparing data for electronic health records meaningful use reporting, identifying caps in ICD-10 coding, and tools needed for data mining, among other issues. "We want the audience to walk away understanding how NLP works," says Dee Lang, vice president of product management and strategy at Precyse Solutions, Wayne, Pa.

Lang and Scott Briercheck, chief scientist at Precyse, will talk about how achieving meaningful use can be easier with a larger body of structured data. The premise, Briercheck says, is turning non-accessible information into accessible data. This includes such information often now in unstructured text as patient histories, physical examinations and physician notes, which can be turned into data that enables population profiling based on diagnoses to better target preventive care.

"We'll show how to achieve the maximum benefit of their data," Lang says. While an immediate benefit is more easily reaching meaningful use, "We want folks to understand this technology can maximize their use of data beyond meaningful use," she adds.

Educational session 7142, "Driving Your Organization to Meaningful Use with Data Analytics," is scheduled on Oct. 3 at 4:45 p.m. More information is available at ahima.org.

 

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