Multi-modal Health Information Technology Innovations for Precision Management of Glaucoma

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PROJECT SUMMARY/ABSTRACT Glaucoma is the world's leading cause of irreversible blindness. Early detection and treatment are critical, as symptoms typically do not present until the disease is advanced. A data-driven precision medicine approach is needed to better identify individuals who are at greatest risk of developing the disease and who are at greatest risk of progressing quickly to vision loss. While there has been considerable progress in eye imaging and testing to improve glaucoma monitoring, precision management of glaucoma is incomplete without accounting for patients' co-existing systemic conditions, concurrent systemic medications and treatments, and adherence with prescribed glaucoma treatment. These factors are important for providing a more comprehensive perspective of glaucoma management and for improving patient outcomes, yet they are relatively understudied. In the parent award, I am applying multi-modal advancements in health information technology (IT) to address these gaps and achieve the following specific aims: (1) Develop machine learning-based predictive models classifying patients at risk for glaucoma progression using systemic electronic health record (EHR) data from a diverse nationwide patient cohort (the NIH All of Us Research Program); (2) evaluate how integrating blood pressure (BP) data from novel smartwatch-based home BP monitors enhance predictive models for risk stratification in glaucoma, and (3) measure glaucoma medication adherence using innovative flexible electronic sensors to validate their use for future interventions aimed at improving adherence and clinical outcomes in glaucoma. In this proposal for an administrative supplement, I intend to build upon my existing studies by continuing to analyze data from the NIH All of Us Researcher Workbench. I will leverage my extensive experience with All of Us and will conduct research to better understand the relationships between glaucoma and factors such as social determinants of health, substance use, wearable/activity data, and genetics. This will expand the impact of my existing research program, which aims to improve risk stratification and generate novel therapeutic targets for glaucoma patients.