Vanderbilt develops AI tool to cut Alzheimer's treatment delays from weeks to days

AI tool aims to accelerate Alzheimer's treatment through faster referrals

Vanderbilt University Medical CenterAug 5 2026Reviewed Vanderbilt Health researchers have received a grant from Eli Lilly and Company, a multinational pharmaceutical company headquartered in Indianapolis, to build an artificial intelligence (AI) tool within the electronic health record system (EHR) to get patients with Alzheimer's disease to treatment faster. The computer project is designed for transferability to other health systems. Newly approved monoclonal antibody therapies are being used to slow early stages of cognitive decline in amyloid-positive Alzheimer's patients. As these drugs have become available, patients who qualify often wait weeks - moving through referrals, specialist evaluation, brain imaging and insurance authorization - before receiving a first infusion. To help speed the process, the team will build an AI triage agent embedded in Vanderbilt Health's EHR. The 18-month, $600,000 project targets the referral from primary care or geriatrics to neurology. As a clinician enters a referral for cognitive concern, the AI triage agent will summarize the relevant chart information, flag missing details that commonly slow evaluation, and recommend whether a case should be routed as priority or standard. Clinicians will retain the ability to accept, edit or override every recommendation. "By the time a patient reaches our clinic, the clock has often been running for weeks," said Amalia Peterson, MD, Assistant Professor of Neurology and a co-principal investigator on the project. "This tool will be designed to make sure that when a referral arrives, we already have the information we need to act quickly. It doesn't replace clinical judgment, but it will remove a lot of the friction that keeps patients waiting." The project is led by principal investigator You Chen, PhD, Associate Professor of Biomedical Informatics, with co-principal investigators Peterson and geriatrician Sean Huang, MD, Assistant Professor of Medicine and Biomedical Informatics. Chen also leads an ongoing $1 million Lilly-funded project to study and address gaps in obesity care. "Our goal with the new project is to reduce avoidable delays across this dementia care pathway," Chen said. "We are grateful to Lilly for this vital support. We see grants like these as highlighting Vanderbilt's leadership in AI-enabled health care delivery." The team will first map where delays accumulate, using AI to reconstruct care timelines from a Vanderbilt Health cohort of more than 5,300 patients. The researchers will identify root causes of those delays with input from clinicians and operational staff and finally deploy and evaluate their AI agent in a pilot. Success will be measured by the reduction in time from diagnosis to first infusion. "For many patients and families, the pathway begins in primary care or geriatrics, where cognitive concerns are first recognized, and the next steps can be difficult to navigate," said co-principal investigator Huang. "Our goal is to help clinicians identify what information is needed earlier, streamline referral communication, and make the handoff to specialty care timelier and complete." The team's project proposal contemplates additional EHR-AI projects targeting this care pathway: A second AI agent could be developed to analyze MRI images and generate Alzheimer's-related safety reports for review by radiologists, and a third agent could be developed to compile Alzheimer's therapy authorization packets and track the insurance authorization process. Project co-investigators include two Biomedical Informatics associate professors, Laurie Novak, PhD, and Kim Unertl, PhD, and Biomedical Informatics Research Instructor Chao Yan, PhD.

Team's AI agent to speed Alzheimer's treatment | Newswise

Vanderbilt Health researchers have received a grant from Eli Lilly and Company, a multinational pharmaceutical company headquartered in Indianapolis, to build an artificial intelligence (AI) tool within the electronic health record system (EHR) to get patients with Alzheimer's disease to treatment faster. The computer project is designed for transferability to other health systems. Newly approved monoclonal antibody therapies are being used to slow early stages of cognitive decline in amyloid-positive Alzheimer's patients. As these drugs have become available, patients who qualify often wait weeks -- moving through referrals, specialist evaluation, brain imaging and insurance authorization -- before receiving a first infusion. To help speed the process, the team will build an AI triage agent embedded in Vanderbilt Health's EHR. The 18-month, $600,000 project targets the referral from primary care or geriatrics to neurology. As a clinician enters a referral for cognitive concern, the AI triage agent will summarize the relevant chart information, flag missing details that commonly slow evaluation, and recommend whether a case should be routed as priority or standard. Clinicians will retain the ability to accept, edit or override every recommendation. "By the time a patient reaches our clinic, the clock has often been running for weeks," said Amalia Peterson, MD, Assistant Professor of Neurology and a co-principal investigator on the project. "This tool will be designed to make sure that when a referral arrives, we already have the information we need to act quickly. It doesn't replace clinical judgment, but it will remove a lot of the friction that keeps patients waiting." The project is led by principal investigator You Chen, PhD, Associate Professor of Biomedical Informatics, with co-principal investigators Peterson and geriatrician Sean Huang, MD, Assistant Professor of Medicine and Biomedical Informatics. Chen also leads an ongoing $1 million Lilly-funded project to study and address gaps in obesity care. "Our goal with the new project is to reduce avoidable delays across this dementia care pathway," Chen said. "We are grateful to Lilly for this vital support. We see grants like these as highlighting Vanderbilt's leadership in AI-enabled health care delivery." The team will first map where delays accumulate, using AI to reconstruct care timelines from a Vanderbilt Health cohort of more than 5,300 patients. The researchers will identify root causes of those delays with input from clinicians and operational staff and finally deploy and evaluate their AI agent in a pilot. Success will be measured by the reduction in time from diagnosis to first infusion. "For many patients and families, the pathway begins in primary care or geriatrics, where cognitive concerns are first recognized, and the next steps can be difficult to navigate," said co-principal investigator Huang. "Our goal is to help clinicians identify what information is needed earlier, streamline referral communication, and make the handoff to specialty care timelier and complete." The team's project proposal contemplates additional EHR-AI projects targeting this care pathway: A second AI agent could be developed to analyze MRI images and generate Alzheimer's-related safety reports for review by radiologists, and a third agent could be developed to compile Alzheimer's therapy authorization packets and track the insurance authorization process. Project co-investigators include two Biomedical Informatics associate professors, Laurie Novak, PhD, and Kim Unertl, PhD, and Biomedical Informatics Research Instructor Chao Yan, PhD.