In a study conducted by the Annals of Family Medicine in 2017, it was concluded that clinicians spend approximately 6 hours out of an 11.4 hour workday interacting with EHR. This is astonishing that more than half of their time is spent logging patient data, and it is quite evident that there is a need for change within this aspect of the current healthcare system.
The demand for more efficient EHR workflow is at an all-time high, which is why companies like Google and Amazon are working with AI technology to better assist medical professionals. As of today, December 2, 2019, Amazon has announced their latest product: Amazon Transcribe Medical.
Amazon Transcribe Medical will allow physicians to more efficiently dictate their clinical notes and visually see their dialogue transformed to accurate text instantaneously. The clinicians will not have to worry about dictating punctuation, as Transcribe Medical automatically translates medical language effortlessly.
“The text can automatically be fed to downstream applications such as EHR systems, or to AWS language services such as amazon Comprehend Medical for entity extraction,” said Julien Simon, an AI and Machine Learning Evangelist for EMEA.
With using machine learning, Amazon Transcribe Medical provides extremely accurate automatic speech recognition (ASR) for the medical industry. One could simply use this application to quickly and efficiently gather physician-patient conversations in text for later examination using natural language processing or for entry into EHR systems.
According to Amazon, Transcribe Medical is “HIPAA eligible and integrates simply with clinical documentation applications and any device with a microphone”. Services such as Amazon Comprehend Medical work with Transcribe Medical by using machine learning to extract relevant medical information from transcriptions, such medical condition, medication, dosage, strength, and frequency.
Amazon Transcribe Medical is available now in the U.S. East (N. Virginia) and U.S. West (Oregon) regions.
Do you believe this type of information is valuable to clinicians and physicians? Comment your opinion below!