Use Case Work Groups
Description
While there are many different CDS use cases, this chosen focus area describes a CDS solution that leverages a large language model (LLM) using a retrieval-augmented generation (RAG) approach to process and deliver evidence-based medical information. By integrating with curated medical content, the AI system provides rapid and personalized clinical insights at the point of care. When a healthcare professional queries a clinical topic, the system generates an AI-driven response displayed alongside conventional search results.
Timeline
Q2 2025 – Q4 2025
Goals:
Develop Responsible AI content that focuses on:
Critical best practice guidance and associated tools & resources
Methods, metrics, benchmarks, and open-source tooling to objectively evaluate responsible use of a clinical decision support solution
Output
Best Practice Guidance
link to guidance documentation once availableTesting & Evaluation Framework
link to GitHub once available
Work Group Leads
Name | Organization |
---|---|
Han-Chin Shing | Amazon |
Geralyn Miller | Microsoft |
Raj Ratwani | Medstar |
Jessica Handley | Medstar |
Kate Eisenberg | EBSCO/DynaAI |
Ben Hollis | EBSCO/DynaAI |
Pawan Jindal | Darena Solutions |
Howard Strasberg | Wolters Kluwer |
Dennis Shung | Yale |
Sonya Makhni | Mayo Clinic |
Work Group Members
In-Progress