Question Wording & Response Sets for Disaggregated Racial/Ethnic Data
Question Wording & Response Sets for Disaggregated Racial/Ethnic Data
Published: 10/30/2020

Disaggregated race/ethnicity data is needed to expose health inequities and inform policies and programs to address those inequities. In this webinar, four researchers talk about data disaggregation and working with collecting data for populations in New York, one of the most diverse populations in the U.S. and in the world.
 

About the National Network of Health Surveys' Advancing Health Equity Through Data Disaggregation Workshop Series

Disaggregated race/ethnicity data is needed to expose gaps in health equities and inform policies and programs and close those gaps. The National Network of Health Surveys, part of the UCLA Center for Health Policy Research, offers a series of workshops designed to improve the disaggregation of race and ethnicity measures in health data sources. Our goal is to boost the number of subpopulation categories made available to key constituencies working to improve health equity. This is especially important for representing communities that are often “hidden” in large health data sets.

Martha Alexander
Martha Alexander
April Aviles
April Aviles
Stephanie E. Farquhar
Stephanie E. Farquhar
Michael Sanderson
Michael Sanderson

Download the presentation slides.
 

Topics and Timestamps

Demographic Data Measures Social Constructs (9:08) 
What can people who work with data do? (19:09) 
Ongoing Development and Refinement of Racial/Ethnic Categories – Community Health Survey (25:52) 
Putting Health Data in Context (55:11) 
Disaggregation in Special Reports (56:25)
Making Data More Accessible and Easier to Use (57:57)