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Antihypertensive Deprescribing in Nursing Home Residents: A Target Trial Emulation

March 5, 2024 at 3PM ET | 12PM PT

Presenter: Dr. Michelle Odden

Michelle Odden, PhD, is an Associate Professor of Epidemiology in the Department of Epidemiology and Population Health at the Stanford School of Medicine and a Research Scientist at the Geriatric Research, Education, and Clinical Center at the Palo Alto VA Health Care System. Her NIH-funded research program has two major foci. First, she aims to better understand the biologic and physiologic mechanisms that characterize the aging process. Second, she strives to improve our understanding of how aging affects optimal preventive strategies for cardiovascular disease and related morbidity in older adults, including dementia and disability. She is particularly interested in populations who have been underrepresented in research including minoritized populations and frail older adults. She also brings expertise in epidemiological and statistical methods to reduce biases in observational studies. Dr. Odden is a Fellow of the Gerontological Society of American and Chairs the Aging, Injury, Musculoskeletal, and Rheumatologic Disorders Study Section for the NIH. At Stanford. Dr. Odden leads the Justice, Equity, Diversity, and Inclusion Committee in her Department and strives to support an anti-racist and anti-oppressive academic culture. She is a Founder and Steering Committee Member of the Stanford AHEaD program. She completed her Ph.D. in Epidemiology from the University of California, Berkeley (2009), a postdoctoral fellowship at the University of California, San Francisco in Primary Care Research (2011).

Description: In this talk we will discuss the use of electronic health records from the Veteran’s Health Administration to estimate the effects of antihypertensive deprescribing in nursing home residents, based on a target trial approach. This approach leverages epidemiologic design principles and state-of-the-art statistical methods to estimate causal effects. We will provide results from our work and discuss the benefits and pitfalls of this approach.


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