Amazon Bedrock for Real-World Health Outcomes
Introduction
In modern healthcare, decision-makers rely on real-world data to analyze patient journeys and health outcomes. Scientists, epidemiologists, and biostatisticians conduct complex queries to extract clinically relevant patient variables. These variables often involve sequences of medical events, treatment responses, and detailed numeric calculations that help capture the diversity of patient experiences.
To simplify this process, Aetion, a leader in real-world evidence solutions, integrates Amazon Bedrock into its platform. By leveraging Amazon Bedrock’s foundation models (FMs), Aetion enables healthcare professionals to express scientific intent using natural language, allowing them to explore patient timelines and transform real-world data into actionable insights.
Amazon Bedrock is a fully managed service providing access to high-performing foundation models from various AI providers. It empowers organizations like Aetion to enhance their analytical workflows and generate decision-grade real-world evidence (RWE) efficiently.
Aetion’s Technology and Amazon Bedrock
Aetion is a healthcare software company that applies causal inference to generate real-world evidence on medications and clinical interventions. They work with top biopharma companies, payors, and regulatory agencies such as the FDA and EMA to enhance clinical trials, expand market access, and conduct safety and effectiveness studies.
Aetion’s core applications, including Discover and Substantiate, operate within AEP. The platform integrates generative AI through AetionAI, which powers the Measures Assistant—a feature designed to translate scientific intent into structured patient data.
With Amazon Bedrock, Aetion leverages foundation models to enhance Measures Assistant, making it more efficient and accurate. This AI-driven approach improves how researchers analyze patient cohorts, reducing the time required to extract meaningful insights.
Measures Assistant: AI-Powered Healthcare Analytics
How Measures Assistant Works
Aetion Substantiate enables users to build studies and extract patient data with precision. Measures Assistant allows researchers to define variables, such as filtering out negative cost values in claims data or tracking hemoglobin changes in diabetic patients.
For example, a user might query:
“Find patients with diabetes who received metformin prescriptions within three months of diagnosis.”
Measures Assistant then translates this request into structured queries using Amazon Bedrock-powered AI, reducing the complexity of real-world data analysis.
Key Benefits of Measures Assistant
– Efficiency: Converts scientific intent into structured queries within minutes instead of days.
– Accessibility: Enables users without extensive data science expertise to interact with real-world datasets.
– Scalability: Supports large-scale healthcare studies by leveraging Amazon Bedrock’s AI capabilities.
Solution Overview: Amazon Bedrock Integration
Aetion’s solution architecture incorporates Amazon Bedrock to enhance the accuracy and efficiency of real-world evidence generation.
Technical Implementation
– Microservices & Kubernetes: Measures Assistant operates as a microservice within an AWS Kubernetes environment.
– Data Security: All transmissions are encrypted with TLS 1.2 to ensure privacy and compliance.
– AI Model Selection: Aetion leverages Anthropic’s Claude 3 Haiku, available through Amazon Bedrock, for efficient, cost-effective natural language processing.
The following diagram illustrates the solution architecture.
Enhancing Decision-Making with AI
AetionAI enhances real-world evidence studies by integrating scientific knowledge and Amazon Bedrock-powered AI. Key features include:
– Retrieval-Augmented Generation (RAG): Combines structured prompts with real-world healthcare data.
– Context-Aware Responses: AI-generated instructions include domain-specific knowledge for accurate data analysis.
– Continuous Learning: Subject matter experts refine the AI knowledge base for ongoing improvements.
Impact on Healthcare Analytics
By leveraging Amazon Bedrock, AetionAI accelerates the conversion of real-world data into evidence-based healthcare insights. Users can now:
– Automate patient cohort creation.
– Enhance real-world safety and effectiveness studies.
– Generate real-time insights for clinical decision-making.
Conclusion
This post explored how Aetion leverages Amazon Bedrock to enhance real-world healthcare analytics. Measures Assistant enables scientists to build complex studies with ease, reducing the time required to define patient variables and analyze health data.
As AI continues to revolutionize healthcare, companies like Aetion are expanding their generative AI capabilities to refine decision-making processes. With cloud-based solutions, organizations can optimize data processing, improve patient care, and accelerate medical research.
For the latest insights into cloud innovation, check out the AWS Weekly Roundup: New Launches and Announcements, where groundbreaking advancements in AI and cloud services are regularly featured.
Do you like to read more educational content? Read our blogs at Cloudastra Technologies or contact us for business enquiry at Cloudastra Contact Us.