HealthScribe is “HIPAA eligible,” however - meaning customers who work with Amazon to meet HIPAA requirements can ultimately reach compliance. law that provides protections for personal health information. But the service isn’t compliant (out of the box) with HIPAA, the U.S. Healthcare software providers using HealthScribe also have control over where they want to store transcriptions and preliminary clinical notes. HealthScribe doesn’t retain customer data after processing requests and encrypts data at transit and at rest, and Amazon says it doesn’t use the inputs and outputs generated by HealthScribe to train any of its AI models. Given the reluctance of some companies to let generative AI apps field sensitive data, it’s not surprising that Amazon’s also highlighting HealthScribe’s security and privacy aspects in its marketing materials. And the platform offers clinicians a chance to review notes before finalizing records in their EHR, providing references to the original transcript for sentences used in the AI-generated notes. So is HealthScribe consistent? Can it be trusted, particularly when it comes to deciding whether to label a part of a discussion as “subjective” or “objective” or identifying medications? And can it handle the wide array of different accents and vernaculars that patients and providers might use?īut perhaps in an effort to prevent some of the more major potential mistakes, HealthScribe can only create clinical notes for two medical specialties at present: general medicine and orthopedics. But there’s no code-switching with automated speech recognition programs - either you assimilate, or you’re not understood. One recent study published in The Proceedings of the National Academy of Sciences showed that speech recognition systems from leading tech companies were twice as likely to incorrectly transcribe audio from Black speakers as opposed to white speakers.Īs a piece in Scientific American points out, in normal conversations, we might choose to “code-switch” depending on the audience. Speech recognition algorithms, too, often contain biases. This might be cause for alarm, given generative AI’s tendency to exhibit biases, confidently invent facts and generally go off the rails. The notes in HealthScribe, augmented by AI, include details like the history of the present illness, takeaways and reasons for a visit.Īmazon says that the AI capabilities in HealthScribe are powered by Bedrock, its platform that provides a way to build generative AI-powered apps via pretrained models from startups as well as Amazon itself. HealthScribe identifies speaker roles and segments transcripts into categories based on clinical relevance, like “small talk,” “subjective comments” or “objective comments.” In addition, HealthScribe delivers natural language processing capabilities that can be used to extract structured medical terms from conversations, such as medications and medical conditions. “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.” “Documentation is a particularly time-consuming effort for healthcare professionals, which is why we’re excited to leverage the power of generative AI in AWS HealthScribe and reduce that burden,” Bratin Saha, VP of machine learning and AI services at AWS, said in a blog post shared with TechCrunch via email. The transcripts from HealthScribe can be converted into patient notes by the platform’s machine learning models, Amazon says, which can then be analyzed for broad insights. Amazon is expanding its range of health-focused apps and services with a platform that offers AI tools to help clinicians transcribe and analyze their conversations with patients.Īt its annual AWS Summit conference in New York, Amazon unveiled AWS HealthScribe, an API to create transcripts, extract details and create summaries from doctor-patient discussions that can be entered into an electronic health record (EHR) system.
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