I-Corps: Health and wellness supportive mobile application

New York University Medical Center, New York NY

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project will be a comprehensive digital lifestyle solution for providers serving patients at low-resourced facilities to optimize patient adherence to diet, physical activity and sleep national guidelines. We define low-resourced facilities as having 10 full time-employees or less, serving patient populations whose median income is at least 25% below the poverty level and are uninsured or under-insured. Patient populations may be characterized as having low health literacy, and experiencing economic and social disadvantage, which are crucial social determinants of health. Thus, the target immediate user, providers at low-resourced facilities, may not have financial, employee, or material resources to support patients to improve their health outcomes. Distal outcomes include improved provider performance measures that could affect reimbursement rates. The commercial impact of a digital support tool is to aid providers in improving the health behaviors of their patient populations that could prevent and manage health conditions in high-need populations. Providers at low-resourced facilities could supplant their patient lifestyle support services, which typically offer nutrition, exercise, and mental/social support during isolated events. This mobile application would allow continuous lifestyle support services, outside of patient office visits. This I-Corps project is focused on a personalized mobile application synced with a wearable device that uses machine learning to generate tailored data visualizations and text messages to optimize user healthful behavior change. Based on customer discovery with providers serving low-resourced facilities, the project aims to unearth whitespace opportunity areas with a novel technical innovation that incorporates three behavioral pillars of cardiovascular health: physical activity, diet/nutrition, and sleep. The proposed application utilizes data on daily lifestyle habits, combined with a user's biological footprint of healthcare data, to automatically generate tailored just-in-time communications to nudge users towards behavior change goals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.