This Workshop covers two topics:

• Strategies in Mitigating Disclosure Risk in Disaggregated Racial/Ethnic Data
• User Experience Accessing Disaggregated Racial/Ethnic Data

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.

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 about 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 sex, age, race, and Hispanice ethnicity for multiple geograhpic 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. My 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.