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Related Experiment Video

Updated: Feb 24, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

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Published on: December 6, 2024

Automating Patient Safety Workflows: The Development and Implementation of LLaMPS, a Secure Large Language Model

Gavin M Schaeferle¹, Margaret Zhou¹, Shrinath Patel¹

¹Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|February 23, 2026

Summary

This summary is machine-generated.

Generative Artificial Intelligence (GenAI) can enhance patient safety event management. A new platform, LLaMPS (Large Language Model for Patient Safety), uses local AI to improve incident reporting and user satisfaction while ensuring data privacy.

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Area of Science:

Healthcare Informatics
Artificial Intelligence in Medicine
Patient Safety

Background:

Generative Artificial Intelligence (GenAI) adoption in healthcare faces challenges like data privacy and clinical relevance.
Existing systems struggle to effectively manage and report patient safety events.

Purpose of the Study:

To introduce LLaMPS (Large Language Model for Patient Safety), a locally deployed GenAI platform.
To enhance patient safety event management and reporting through advanced AI capabilities.

Main Methods:

LLaMPS utilizes a Retrieval-Augmented Generation (RAG) approach with secure, institutionally hosted Large Language Models (LLMs).
A vector database ensures data privacy and regulatory compliance.
Iterative development involved clinicians and patient safety experts.

Main Results:

LLaMPS demonstrated high accuracy in incident classification.
The platform showed improved user satisfaction among healthcare professionals.
The system integrates automated classification, harm prediction, intelligent search, and a chatbot.

Conclusions:

Locally controlled AI solutions like LLaMPS can significantly enhance patient safety workflows.
LLaMPS addresses key concerns regarding data privacy and clinical integration of GenAI in healthcare.
The platform shows potential for broader adoption in improving healthcare safety.