Data-Driven Engagement to Underrepresented in Biomedical Research Populations

Background: Our organization aims to provide resources to libraries, national and local organizations, and community-based organizations to conduct outreach and engagement activities in their communities. Of particular interest to us is increasing libraries’ and organizations’ capacity to reach populations underrepresented in biomedical research (UBR). A challenge to our work was identifying libraries and organizations that are located within communities with high UBR populations. To address this, we developed a data dashboard in Microsoft PowerBI that identifies Zip Code Tabulation Area (ZCTAs) to identify areas with significant representation of UBR communities.

Description: To define UBR status, we adopted the definitions of UBR and non-UBR for each diversity category described by Mapes et al (2020). We used the 2015-2019 Census estimates and Health Resources and Services Administration (HRSA) data to generate ZCTA data for the UBR race and ethnicity, age, annual household income, educational attainment, and geography categories. The process of developing such a tool requires numerous decisions such as the definition of UBR, community-level data selection, selecting which software to use, and accessibility of the tool. For example, we worked with staff and various stakeholders to determine the thresholds to categorize communities into two groups - UBR and non-UBR - for the dashboard. Furthermore, the development process involved numerous iterations to incorporate user feedback, feasibility constraints, and resolve bugs in a timely manner.

Conclusion: During this session, the authors will describe the dashboard development process including using Rstudio to access and manipulate the data, evaluating data visualization tools, and the benefits and limitations of using community-level characteristics data. We will also describe how we use the dashboard to inform data-driven community engagement activities to identify and connect with libraries and organizations within our community of interests to partner with us to serve their communities. For example, we used the dashboard to prioritize funding projects in areas with high UBR populations. We will also discuss the 2.0 of this tool which will include data about the service-based organizations in ZCTAs to create a composite of strengths and lack of services in communities.