AWS Launches HealthScribe Clinical Documentation Solution

Amazon Web Services at its AWS Summit New York launched AWS HealthScribe, a service that empowers healthcare software providers to build clinical applications that use speech recognition and generative artificial intelligence for clinical documentation.

With AWS HealthScribe, healthcare software providers can use a single API to automatically create transcripts, extract key details, and create summaries from doctor-patient discussions that can then be entered into electronic health record (EHR) systems.

Powered by Amazon Bedrock, AWS HealthScribe will start with two popular specialties, general medicine and orthopedics. AWS HealthScribe cites the source of every line of generated text from within the original conversation transcript so physicians can review clinical notes before entering them into the EHR.

AWS HealthScribe also gives users control over where their data is stored, encrypts data in transit and at rest, and does not use inputs or outputs generated through the service to train its models. Healthcare providers can leverage built-in text-to-speech capabilities to create conversation transcripts that identify speaker roles and segment transcripts into categories (e.g., small talk, subjective comments, or objective comments) based on clinical relevance. The application can then use AWS HealthScribe's natural language processing and generative AI capabilities to extract structured medical terms, such as medical conditions and medications, and generate discussion-based notes that include relevant details (e.g., key takeaways, reason for visit, and history of the present illness)

"Our healthcare customers and partners tell us they want to spend more time creating innovative clinical care and research solutions for their patients while spending less time building, maintaining, and operating foundational health data capabilities," said Bratin Saha, vice president of machine learning and artificial intelligence services at AWS, in a statement. "That is why AWS has invested in building a portfolio of AI-powered, high-performance, and population-scale health applications so that clinicians can spend more time with the patients during the face-to-face or telehealth visits. Documentation is a particularly time-consuming effort for healthcare professionals, which is why we are excited to leverage the power of generative AI in AWS HealthScribe and reduce that burden. Today's announcement builds on AWS's commitment to the healthcare and life sciences industry and our responsible approach to technologies like generative AI to help reduce the burden of clinical documentation and improve the consultation experience."

Two of AWS's early partners in the HealthScribe project are 3M Health Information Systems, whose M*Modal speech understanding, conversational, and ambient AI solutions are currently used by more than 300,000 clinicians, and ScribeEMR, a provider of virtual medical scribing, virtual medical coding, and virtual medical office services for hundreds of medical practices, hospitals, and health systems.

"Machine learning on AWS enables 3M HIS to transform clinician workflows and laborious processes to help healthcare organizations streamline clinical documentation and billing," said Garri Garrison, president of 3M HIS, in a statement. "3M HIS is collaborating with AWS to bring conversational and generative AI directly into clinical documentation workflows. AWS HealthScribe will be a core component of our clinician applications to help expedite, refine, and scale the delivery of 3M's ambient clinical documentation and virtual assistant solutions."

"ScribeEMR's goal is to help increase practice efficiency, maximize revenue, and reduce clinician burnout in the healthcare industry," said Daya Shankar, co-founder and general manager of ScribeEMR, in a statement. "By harnessing the power of AWS HealthScribe, we can transform the process of healthcare documentation using generative AI. With AWS HealthScribe, our advanced processes can now capture and interpret patient visits more effectively and optimize EMR workflows, coding, and reimbursement processes."