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AWS Expands HIPAA Eligible Machine Learning Services

New HIPAA-compliant machine learning services from AWS allow organizations to take advantage of dynamic transcription, translation, and language comprehension services.

Source: Thinkstock

By Elizabeth O'Dowd

- Amazon Web Services (AWS) announced the expansion of its machine learning services to healthcare organizations. Amazon Translate, Amazon Comprehend, and Amazon Transcribe are now HIPAA compliant.

Healthcare professionals can now take advantage of these Amazon services to help leverage better insights and deliver better patient outcomes.

The services use the AWS environment already in use by many healthcare organizations so integrating the technology is more simplified than using a desperate system.

Customers can use these three services to leverage the following ML capabilities:

  • Amazon Transcribe: A speech-to-text service that automatically creates text transcripts from audio files will allow healthcare organizations to create text transcripts calls with patients.
  • Amazon Translate: A neural machine translation service that delivers fast, high-quality, and affordable language translation. This service can be employed to easily translate large volumes of text efficiently and enable patients to chat with their healthcare provider in their preferred language.
  • Amazon Comprehend: A natural language processing (NLP) service that can find insights and relationships in unstructured text. It can analyze sentiment (e.g., negative, positive, and neutral), and extract key phrases from patient interactions to better understand and improve engagement.

“Many healthcare customers are exploring new ways use the power of ML to advance their current workloads and transform how they provide care to patients, all while meeting the requirements of HIPAA,” AWS explained.

Healthcare organizations are already leveraging these AWS services to perform machine learning tasks, including medical care search company Zocdoc.

“At Zocdoc, our focus has been making it easier for patients to find the right doctor and book an appointment at the most convenient time and location,” said Zocdoc in a starement. “You can imagine the ML use cases. There is a lot of excitement among Zocdoc engineers around how easy it is to quickly build and deploy a model using Amazon SageMaker.”

“As a matter of fact, one of our mobile engineers was able to train and deploy a doctor specialty recommendation model from scratch in less than a day during a recent Zocdoc Hackathon, which we ended up rolling out to production. Previously, our data science team had to contribute to the development of any model work, which slowed down product teams given that the data science team is a shared resource. With Amazon SageMaker, we could get this from concept to a quick production test much faster, due to the ease of streamlined end-to-end build/deploy/test capabilities of Amazon SageMaker. HIPAA eligibility is a welcome improvement and will allow us to expand its use to improve healthcare experience for our patients.”

Aculab has also taken advantage of AWS’ machine learning services, leveraging Amazon Polly, a tool that turns text into lifelike speech.

“One of the key decision points that led Aculab to choose Amazon Polly for our Text-to-Speech (TTS) on the Aculab Cloud platform was the HIPAA support,” said David Samuel, CEO of Aculab. “We have major customers using our system for services such as medical appointment reminders, and we needed a TTS solution that we could use with HIPAA workloads to complement the rest of our HIPAA-compliant architecture. Amazon Polly was able to provide not only a world-class TTS service, but one that could safely handle protected health information,”


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