Who adapts to whom in voice recognition?
Radiologists and referring clinicians should learn the language of voice recognition.
If only speech recognition understood what radiologists were saying.
Radiology report turn-around times improve with introduction of speech recognition software.
How would you feel about expanding the capability of your speech recognition software to analyze and measure your stress and fatigue levels?
Speech recognition software can be leveraged to tell if a radiologist is stressed, prompting individualized interventions to improve quality and satisfaction.
The way radiology reports are generated has certainly changed since I began my radiology residency in the Navy in the late ‘70s.
C. Matthew Hawkins, MD, discusses challenges of natural language processing and how more standardization can reduce error rates of speech recognition software.
Whether you’ve embraced voice recognition software or rely on a transcriptionist, there’s still the problem of large amounts of text that’s largely unusable. Enter natural language processing, which makes structured reporting and data mining possible by coding the text and extracting data.
Radiologists at University of Chicago Medical Center set out to decrease their own error rates, and found that with peers scoring and reviewing each others’ reports, and then discussing them at section meetings, error rates dropped.