Paul Dupenloup

In the US, diabetes poses a substantial challenge in the form of outsized medical costs, significant morbidity, and premature mortality. In 2022, total costs for diabetes were estimated to be $419 billion and diabetes care accounted for a whopping 1 in 4 healthcare dollars in the U.S. However, given that many patients use continuous glucose monitors, insulin pumps, and wearable devices, there is a unique opportunity to measure individual patient outcomes in real-time and deliver timely, on-demand interventions. Though significant research has demonstrated that AI tools have the potential to transform risk stratification and personalized strategies for diabetes, these theoretical advancements have been slow to materialize in patient care. My proposed interdisciplinary research aims to bridge the gap between theory and practice – namely, by quantifying the cost-effectiveness of AI-enabled remote patient monitoring, articulating financially sustainable pathways for clinics to adopt AI, and supporting payors and providers in expanding access to high-value, personalized care for all patients.