Vanderbilt Researchers Use AI to Address Gaps in Long-Term Obesity Care

Key Takeaways:

• A $1 million Eli Lilly grant will fund a two-year Vanderbilt University Medical Center (VUMC) project using artificial intelligence (AI) to address gaps in obesity care.
• The initiative will analyse electronic health records (EHRs), survey patients and clinicians, and build a multi-agent AI system to develop evidence-based strategies for improving long-term engagement.
• A patient-facing mobile application will be designed and piloted in VUMC obesity clinics to support shared decision-making and sustained weight management.
  
  

Major investment in addressing gaps in care

Vanderbilt University Medical Center (VUMC) has secured a $1 million grant from Eli Lilly and Company to fund a two-year research project aimed at improving continuity of care for people living with obesity. The initiative seeks to understand why many individuals discontinue treatment and to create scalable solutions to help them stay engaged in long-term care.

“Obesity is a chronic, relapsing condition that requires ongoing management, yet too often it is treated episodically because of barriers like delayed medication access,” explained You Chen, PhD, Associate Professor of Biomedical Informatics and the project’s Principal Investigator for informatics and technology. “We’re combining data-driven insights, stakeholder input and multi-agent AI to understand where continuity breaks down and to design evidence-based interventions that keep patients engaged.”

Data-driven insights and stakeholder engagement

In its first year, the research team will analyse VUMC’s electronic health records to identify patterns distinguishing people who remain in continuous follow-up from those who disengage. Patient and clinician surveys will be conducted to capture real-world barriers to care, including logistical, financial and psychological challenges.

The findings will be integrated into a multi-agent AI system, featuring simulated physician, nurse and dietitian agents. This system will generate and prioritise strategies for maintaining engagement, which will then be reviewed by panels of clinicians, informaticians and patient representatives.

Patient-facing app to support engagement

The second year of the project will focus on designing and piloting a mobile application to be used in VUMC obesity clinics. This app is intended to help patients view and interpret their own health data, complete pre-visit tasks, and communicate more effectively with their care teams.

“By helping patients view and interpret their own data, complete previsit tasks, and communicate more effectively with care teams, the app will aim to strengthen shared decision-making and sustain engagement over time,” said Chen.

Clinical leadership and broader impact

The project’s clinical lead is Gitanjali Srivastava, MD, Professor of Medicine in the Division of Diabetes, Endocrinology and Metabolism.

“Medicine has evolved, and we need to adapt to new technological advances while catering to patient needs,” Srivastava stated. “It’s about designing practical tools and processes that fit naturally into patients’ lives and clinicians’ workflows, ultimately supporting healthier weight management over time.”

Chen emphasised that the project is intended to be scalable across health systems. The researchers believe that the human–AI collaborative approach developed through this project could serve as a reproducible framework for improving continuity of care for other chronic conditions that require long-term management.