The goal of the project led by Vanderbilt University Medical Center is to create the Vanderbilt Chatbot Accuracy and Reliability Evaluation System (V-CARES) to effectively and efficiently detect hallucinations, omissions, and misaligned values from large language model (LLM) responses in the healthcare domain. The project aims to improve the quality of LLM-based Chatbot systems so they can serve as trustworthy, transparent, and accurate sources of information and guidance on health-related topics for the general public, patients, and their caregivers. In addition to reducing hallucinations and omissions, the project aims to create a generalizable evaluation process and technology to improve the quality of the output responses and ensure they are consistent with users’ values and expectations. Immediate use cases include two distinct and prevalent mental health disorders: Major depression and generalized anxiety disorder.