Workshop Series: Addressing Health Equity through Data Disaggregation 

Disaggregated race/ethnicity data is needed to expose gaps in health equities and inform policies and programs and close those gaps. If you work with health data and want to increase population representation, we invite you to join in our technical assistance workshops to address barriers to disaggregation.

The National Network of Health Surveys, part of the UCLA Center for Health Policy Research, is offering 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.

Survey leaders, health data managers, community groups and data users are encouraged to join us for expert-led sessions to work on the more pressing issues of disaggregation.

Upcoming workshops include:

Disaggregating Racial/Ethnic Data Decision-making: Who, What, When?
Tuesday, August 31, 2021 | 10:30 a.m.–Noon PT
Presenters: Samantha Artiga, Vice President and Director, Racial Equity and Health Policy Program, Kaiser Family Foundation; Joshua Quint, PhD, MPH, Epidemiologist, Disease Outbreak Control Division, Hawai’i Department of Health; and Eva Wong, PhD, Epidemiologist, Public Health – Seattle & King County
Join us for a panel discussion on approaching the key considerations when choosing to expand racial/ethnic categories in health data sets. Health data leaders will discuss their decision making on: Who: what categories to include? What: what question-wording gets at the information desired? When: what conditions should be present to trigger expanded racial/ethnic data disaggregation?  

Imputation Strategies for Racial/Ethnic Data Disaggregation
Friday, October 8, 2021 | 10:30 a.m.–Noon PT
Presenter: Marc Elliott, PhD Senior Principal Researcher and Distinguished Chair in Statistics RAND Corporation
Surveys offer excellent first-person, self-reported data. But sometimes, survey data contains missing data in some response sets. Imputation is a technique for replacing missing data with a substitute value that retains the integrity of the full data set. Join us for a discussion on strategies for imputation, an important method to use when missing data can potential deplete small racial/ethnic data categories.

Previous workshops:

Disaggregated Racial/Ethnic Data: Considerations for Data Collection and Processing    
Wednesday, October 21 | 10 a.m.–11:30 a.m. PT
Presenter: Ninez Ponce, Director, UCLA Center for Health Policy Research
The workshop will explore effective strategies to ensure your data represents the true diversity of your population. The discussion will include decision-making approaches, community engagement strategies, and case studies in survey science. Following the presentation, Dr. Ninez Ponce will lead activities and provide opportunities to discuss specific project needs.

Question Wording and Response Sets for Disaggregated Racial/Ethnic Data   
Friday, October 30 | 10 a.m.–11:30 a.m. PT
Presenters: Martha Alexander, Data Communications Outreach Analyst, Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene; April Aviles (she/her/ella), Child Health Survey Manager, Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene; Stephanie E. Farquhar, Director of Social Research, Bureau of Equitable Health Systems, New York City Department of Health and Mental Hygiene; and Michael Sanderson, Surveillance Surveys Lead, Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene

User Experience Accessing Disaggregated Racial/Ethnic Data
Wednesday, November 18 | 10 a.m.–11:30 a.m. PT
Presenters: Elizabeth Blomberg, Research Scientist, County Health Rankings & Roadmaps; Marjory Givens,  Associate Director, University of Wisconsin Population Health Institute (UWPHI); and David Van Riper, Spatial Analysis Director, Minnesota Population Center
The first part of the workshop will offer participants an opportunity to learn about County Health Rankings & Roadmaps as a data-to-action platform that is both a consumer and producer of disaggregated data. Presenters will share challenges and key considerations around norms and values pertaining to accessing, manipulating, and displaying disaggregated data, such as how groups of individuals are categorized or making sense of the best available information even when it is data with limited reliability. Workshop participants will learn with others on how to navigate such challenges and considerations. In the second part of the workshop, we will discuss how decennial census data, broken down by gender, age, race, and Hispanic ethnicity for multiple geographic levels, is used to track a wide range of health outcomes. Changes to the Census Bureau's disclosure avoidance system for the 2020 decennial census may hurt our ability to track health outcomes across a wide variety of sub-populations. The talk will review the new disclosure avoidance system, based on differential privacy, and highlight public health analyses using multiple demonstration datasets published by the Census Bureau.

Coding and Machine-Learning Strategies for Disaggregated Racial/Ethnic Data
Tuesday, December 15 | 10 a.m.–11:30 a.m. PT
Presenter: Scott Comulada, Director for UCLA Semel Institute Center for Community Health, and Associate Professor, UCLA Department of Psychiatry and Biobehavioral Sciences

Weighting Strategies for Disaggregated Racial/Ethnic Data
Friday, January 29, 2021 | 10 a.m.–11:30 a.m. PT
Presenters: Ninez Ponce, Director, Tara Becker, Senior Researcher, and Brian Wells, Survey Methodologist, UCLA Center for Health Policy Research
This webinar will discuss the ways in which survey weighting processes can and cannot be used to improve the representativeness of data on small and disaggregated populations within population surveys. Presentations will cover the purpose of providing survey weights that account for specific subpopulations, things to consider when selecting a control population to use for calibration, and methods of accounting for small subgroups in weighting data.

Collection and Reporting of Data on the Multiracial Population
Friday, February 26, 2021 | 10 a.m.–11:30 a.m. PT
Presenters: Jacqueline Lucas, Health Statistician/Epidemiologist, National Center for Health Statistics (NCHS); and Neil Ruiz, Associate Director of Global Migration and Demography, Pew Research Center
As more surveys and other health data sources want to allow respondents to identify with the multiple races that reflect their identity, data managers are working on the strategies for developing the best question wording, tabulation methods, and dissemination strategies to most accurately reflect the population. Neil Ruiz will discuss trends in capturing multiracial identity and the implications for researchers. Jacqueline Lucas will share trends in federal health surveys, such as the National Health Interview Survey, and how data is processed, and how researchers can access racial/ethnic data in public use files as well as a federal Research Data Center (RDC) locations.

Strategies in Mitigating Disclosure Risk in Disaggregated Racial/Ethnic Data
Friday, April 30, 2021 | 10 a.m.–11:30 a.m. PT
Presenter: Darius J. Singpurwalla, Mathematical Statistician, National Science Foundation’s National Center for Science and Engineering Statistics (NCSES)
This presentation will review several commonly used statistical disclosure limitation (SDL) techniques that are used to protect sensitive government data.  In addition to this review, the presenter will demonstrate these techniques in practice by presenting several case studies. Finally, the presenter will share several useful resources that the audience can refer to for further guidance on available techniques used to protect its data.

Support for this workshop series was provided by a grant from the Robert Wood Johnson Foundation.