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:​

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    Critical best practice guidance and associated tools & resources

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    Methods, metrics, benchmarks, and open-source tooling to objectively evaluate responsible use of a clinical decision support solution


Output

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    Best Practice Guidance
    link to guidance documentation once available

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    Testing & 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

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Get in touch

info@chai.org


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