Healthcare organizations often grapple with the task of making sense of the extensive amounts of unstructured medical data contained within patient records, lab results, and clinical guidelines. Astonishingly, a significant 97 percent of the 50 petabytes (PB) of healthcare data generated annually remains unused. This untapped reservoir holds the promise of transforming patient care and saving precious clinician time.

Harnessing AWS Generative AI to Revolutionize Healthcare

Overcoming the Data Challenge

Healthcare organizations find themselves at a crossroads when it comes to dealing with the vast amounts of unstructured medical data. This data, trapped within various sources, has the potential to be a game-changer. By building an innovative solution on Amazon Web Services (AWS) generative artificial intelligence (AI) capabilities, clinicians can now unlock this data treasure trove. 1: The significance of this challenge cannot be overstated. With the increasing volume of healthcare data being generated, it becomes crucial to find ways to extract valuable insights. AWS provides the necessary tools and technologies to handle this data effectively. 2: The 97 percent of unused data represents a vast opportunity waiting to be tapped. By leveraging AWS generative AI, healthcare organizations can start to make sense of this data and use it to improve patient care and clinician efficiency.

One Medical's Testing and Benefits

One Medical, a leading primary care organization, is currently testing a solution that aims to help clinicians obtain summarized patient clinical notes in an easily understandable format. By using Amazon Q Business, a generative AI-powered assistant, HealthLinker can answer questions, provide summaries, and generate content based on data from One Medical's systems. 1: This solution offers a significant advantage by saving clinicians valuable time. Estimated to save 5-7 minutes per patient, clinicians can now focus more on delivering exceptional care rather than spending time on administrative tasks. 2: For example, automatically generating personalized messages that explain lab results and recommend actions to improve health is a game-changer. This not only saves time but also improves patient communication and engagement.

Solution Overview

The solution works by feeding a highly secure Amazon Simple Storage Service (Amazon S3) bucket with a knowledge base of patient records, lab results, clinical guidelines, and instructions on analyzing findings and calculating risk scores. Clinicians authenticated by AWS IAM Identity Center can then query this knowledge base using natural language through the Amazon Q Business chat interface, powered by large language models (LLMs) from Amazon Bedrock. Amazon Q Business is HIPAA eligible. 1: This integrated approach allows clinicians to access the relevant information quickly and easily. The visual representation of the patient's medical chart, including lab results, in the chat interface provides a clear overview. 2: The ability to ensure that the language used in the generated messages is patient-friendly and easy to understand is a crucial aspect of this solution. Clinicians can review and approve the final content, ensuring its accuracy and relevance.

Conclusion

By leveraging the power of AWS generative AI services, this use case showcases how healthcare providers can unlock the potential of their unstructured data. As One Medical continues to test and refine this solution, it has the potential to pave the way for a future where AI-driven insights are seamlessly integrated into the clinical workflow, benefiting both providers and patients. 1: The possibilities are endless when it comes to using AWS for healthcare innovation. From improving patient care to enhancing clinician efficiency, this solution offers a promising path forward. 2: By exploring AWS healthcare offerings, generative AI in healthcare on AWS, and participating in Amazon Q Business workshops, healthcare organizations can start to harness the power of AI and transform their operations.