Skin Color and Tone as Biomedical and Social Determinants of Health Data

Presentation Time: 09:45 AM - 11:15 AM

Abstract Keywords: Health Equity, Diversity, Equity, Inclusion, Accessibility, and Health Equity, Clinical Decision Support, Machine Learning, Legal, Ethical, Social and Regulatory Issues
Primary Track: Foundations
Programmatic Theme: Clinical Informatics

Perceptions of skin color and tone, while intricately linked to ethnoracial identity, are separate from race and ethnicity and less well understood in their effect on health. Furthermore, skin color and tone have historically been poorly measured and continue to be misrepresented in data, including for training of machine learning algorithms. If ethically achievable, the use of skin color and tone data as biomedical and social determinants of health data could support improved clinical care, more detailed health equity research, and more effective machine learning tools. This panel discusses using skin color and tone data in the context of health equity and methods for doing so.

Speaker(s):
Katherine Brown, PhD
Vanderbilt University Medical Center

Jenna Lester, MD
University of California San Francisco

Benjamin Collins, MD
Vanderbilt University Medical Center

Leandra Barnes, MD
Stanford University

Author(s):
Benjamin Collins, MD - Vanderbilt University Medical Center; Katherine Brown, PhD - Vanderbilt University Medical Center; Art Papier, MD - 1. VisualDx 2. University of Rochester; Jenna Lester, MD - University of California San Francisco;