Abstract Number:
1108
Submission Type:
Invited Paper Session
Participants:
Audrey Hendricks (1), Maricela Cruz (2), Miguel Marino (3), Betzaida Maldonado (1), Mariah Tso (4), Sherri Rose (5)
Institutions:
(1) University of Colorado Anschutz Medical Campus, Aurora, CO, (2) Kaiser Permanente Washington Health Research Institute, Seattle, WA, (3) Oregon Health & Science University, Portland, OR, (4) UCLA’s Ralph J. Bunche Center for African American Studies, Los Angeles, CA, (5) Stanford University, Stanford, CA
Chair:
Maricela Cruz
Kaiser Permanente Washington Health Research Institute
Session Organizer:
Speaker(s):
Mariah Tso
UCLA’s Ralph J. Bunche Center for African American Studies
Session Description:
As society and research moves towards precision medicine and a better understanding of structural and systemic determinants of health, inclusion of race, ethnicity, and ancestry in research has become more prevalent. These terms and groupings are, however, often conflated with each other and with structural racism, resulting in incorrect usage or conclusions. Speakers in this session will discuss considerations and best practices for the use of race, ethnicity, and ancestry across different areas of statistics and data science research such as genetics, electronic health records data, and chronic kidney disease.
The first speaker, Mariah Tso, will invite the audience to reflect on how standard methods of data collection, analysis, and interpretation can reinforce systems of oppression rather than challenge them. The second speaker, Dr. Miguel Marino, will discuss advantages and disadvantages of disaggregating race and ethnicity data to design and implement culturally appropriate interventions. The third speaker, Betzaida Maldonado, will present on challenges and considerations for using race, ethnicity, and ancestry data in the context of genomic studies. The fourth and final speaker, Dr. Sherri Rose, will discuss how racial bias has manifested in clinical care of chronic kidney disease via the staging formula.
After attending this session, audience members will have a better understanding of the differences between race, ethnicity, and ancestry, as well as considerations to improve data collection, study design, and analysis across a variety of study types.
Sponsors:
Justice Equity Diversity and Inclusion Outreach Group 2
Section on Statistics in Genomics and Genetics 3
WNAR 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Medium (80-150)
I have read and understand that JSM participants must abide by the Participant Guidelines.
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I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
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