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Irene Dankwa-Mullan, MD MPH (she/her/hers)

Bethesda, Maryland, United States

Dr. Dankwa-Mullan is a physician leader and scientist with diverse local, regional, and national leadership experience. She has worked in primary care, public health, within government, research, and industry. She is currently Chief Health Officer at Marti Health, a health equity start-up company that promotes comprehensive quality care and case management coordination targeting individuals and families from underserved and socially disadvantaged communities. She is an affiliate faculty professor at the George Washington University Milken Institute School of Public Health. She also serves as a strategic advisor for health equity start-up companies.

Dr. Dankwa-Mullan was formerly Chief Health Equity Officer at IBM Watson Health. She also served as Deputy Chief Health Officer, Lead Scientific Officer for Data and Evidence. Her work at IBM received recognition and she was appointed to the IBM Industry Academy of distinguished leaders, to work collaboratively with other industry leaders on creative and cutting-edge technology innovation.

Prior to IBM, Dr. Dankwa-Mullan served in various leadership roles at the National Institutes of Health. Dr. Dankwa-Mullan helped launched the transformational research agenda at the NIH to advance the science of health disparities research in a deliberate and inclusive engagement process involving the NIH, community partners and the broader scientific community.

Dr. Dankwa-Mullan has maintained keen passion for patient-centered care, promoting equitable health outcomes and the patient experience while identifying opportunities to create more inclusive, culturally competent, equitable and compassionate clinical care services. Prior to NIH, she served as Medical Director for public health services, working with community coalitions to develop community prevention and screening programs.

She has published widely on health disparities, including on the integration of health equity, artificial intelligence and machine-learning, ethical artificial intelligence (AI) and social justice principles into data science methods and technology development lifecycle.

Disclosure information not submitted.

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