Innovative AI Models for Provider-to-Provider Consults

Project Overview

This project leverages artificial intelligence (AI) large language models (LLMs) to aggregate and synthesize patient data from electronic medical records (EMRs) to enhance provider-to-provider consultations (eConsults). The integration of LLMs within EMR systems offers a transformative opportunity to streamline and strengthen eConsult workflows by automatically extracting, organizing, and summarizing relevant clinical information from both structured and unstructured data. These AI-generated summaries enable providers to deliver focused, high-quality case overviews for specialist review, improving the accuracy and consistency of consults while expanding access to specialty expertise in rural and underserved areas.
In parallel, the project will deploy a contracted AI platform to automate the generation of concise, one- to two-page patient summaries for eConsult submissions. By highlighting the most clinically relevant details, this system will reduce the time required for specialists to review cases, improve workflow efficiency, and enhance the timeliness and quality of consultations—ultimately enabling rapid, statewide access to specialty care through a more efficient, equitable, and AI-supported telehealth infrastructure.