From Recognized Text To Clinically-Actionable Data

What is a Speech Recognition Context ? In a recent article from Health Imaging & IT, the respective Chief Medical Officers of Philips Speech Recognition Systems and Health Language shed light on the future of speech recognition technology for healthcare. Beyong speech-to-text conversion, SR is clearly turning into a full enterprise solution with a direct impact on both clinical decision-making and the actual cost of healthcare.

Nick van Terheyden, MD, CMO, Philips Speech Recognition Systems:

Speech recognition can reduce costs by 30 to 40 percent, and early users will have a very high competitive advantage.

Providing clinically actionable data is the key to solving fundamental challenges with EMRs such as: capturing data at the source to input into the EMR, supporting clinical decision-making with clinically actionable data, and providing tools that enable the capability to catch errors before they’re committed.

Speech recognition and natural language understanding bridges the gap between clinicians and technology

Brian Levy, MD, CMO of Health Language:

The language engine works simultaneously with the speech engine allowing for real-time conversion of text to standards. In addition, an EMR may be set up to allow smaller sections of dictations for various components of the record such as history, problem lists, medications, and so on. The EMR or other application may then permit the clinician to select more specific or additional codes to further standardize the information.

The current interaction with the patient usually occurs separately from the ability to look up referential material pertinent to the patient. But the introduction of speech and conversion to standards within an electronic medical record enables real-time information.

> Read full article

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