Harvard Catalyst Profiles

Contact, publication, and social network information about Harvard faculty and fellows.

Lidia Maria Veras Rocha De Moura, M.D.

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Overview
I am a clinician, neurologist and epidemiologist with a subspecialty in advanced general neurology, specifically focusing on aging, frailty, and patients with multiple co-morbid neurological conditions such as ADRD, stroke, traumatic brain injuries, and seizures. Additionally, I specialize in clinical epilepsy and neurophysiology. I hold a Master's in Public Health and a PhD in Population Health Sciences from both the Harvard T.H. Chan School of Public Health and the Harvard Graduate School of Arts and Sciences.

Currently, I serve as an Associate Professor of Neurology at Harvard Medical School and co-direct The MGH Center for Value-based Healthcare and Sciences. My expertise lies in the epidemiology of aging, methods in neuro and pharmaco-epidemiology, as well as leveraging machine-learning approaches to enhance the quality of real-world data (RWD).

My academic endeavors primarily revolve around promoting care efficiency, reducing health inequities, and establishing a resilient healthcare system. I lead ADRD-focused projects as a Principal Investigator for the National Institutes of Aging, and I also hold the role of co-Principal Investigator for a Centers for Disease Control and Prevention (CDC)'s project. I have contributed to several peer-reviewed manuscripts and hold leadership positions in institutions such as the American Academy of Neurology, where I chair the quality informatics subcommittee.

Collaboration is a significant aspect of my work, and I closely collaborate with the CDC, the American Academy of Neurology, and other institutions on nationwide epidemiological surveillance, implementation, dissemination, and data platform initiatives. I am the Director of the Data Coordinating Center for a Learning Healthcare System for individuals with seizures. This data platform integrates electronic health records (EHR), claims and billing data, case report forms, medical images (such as MRI and CT scans), and patient-generated data from various mobile applications.

Furthermore, I am frequently invited to speak on machine-learning approaches to enhance data quality and organizational efficiency. I also deliver lectures on value-based care and actively contribute to efforts aimed at reducing disparities in neurology care delivery nationwide. I have been recognized with awards for my excellence in supervision and for fostering the careers of minority youth. Ultimately, my overarching goal is to utilize real-world data to ensure that individuals with complex healthcare needs receive timely and appropriate screening, education, and care.
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.