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Adopting Data Equity Principles in Public Health Research and Analysis

There is power in data. It drives decisions, influences funding, and can change lives…for better or worse. Implicit biases influence the decisions we make, including data decisions. Biases infiltrate data, potentially skewing or discrediting findings. 

Common Ground Health is on a journey to embed data equity principles into our research and analytic processes to ensure that our work is inclusive, equitable, and minimizes potential biases. 

Potential for bias exists at every stage of research and analytic processes. To mitigate biases in our work, staff participate in data equity training utilizing an approach developed by Heather Krause at We All Count. We actively integrate and adapt these principles to fit the work we do.

What do we mean by data equity?

Data equity is an approach to critically examining the ways in which data are collected, analyzed, interpreted, and shared. We operate on the principles that: 
  • Data are not objective; 
  • Data can create and perpetuate power dynamics; 
  • Equity needs to be considered throughout each phase of the data life cycle. 
Data are collected, analyzed, interpreted, and shared by people who carry with them subjective experiences and potential biases, whether we realize it or not. We integrate an equity lens into our work to ensure that those who the data represent are not misrepresented and/or harmed by our analyses. 

How do we integrate data equity principles into our work?

We use the “We All Count” framework, which identifies seven different areas to integrate equity into a data project. These phases are: 
  1. Funding
  2. Motivation
  3. Project design
  4. Data collection and sourcing
  5. Analysis
  6. Interpretation
  7. Communication and distribution

Here are examples of ways in which we have embedded and adapted these phases, as necessary, to integrate equity into our data work. 

Funding: Funding dynamics have the potential to influence the ways in which a project is conducted. At the beginning of a project, we identify the interplay between money, raw data, data reports, and influence within a project. We differentiate raw data from reports as we feel different power dynamics exist between those with the ability to create narratives from raw data and those who have a narrative delivered to them through aggregated data found in a report. 

Motivation: Each member of the team brings with them a different reason for participating in a project and different perspectives as to why they feel the organization is working on a particular project. We dedicate time at the onset of each initiative to identify intrinsic and extrinsic reasons for completing a project. Team members individually draft a motivation statement and come to consensus to create a single motivation statement for the organization. 

Project Design: Biases can infiltrate all elements of project design if we do not critically assess the ways in which data are collected. Data collection instruments including survey tools, assessment forms, and interview and focus group guides can quickly derail well-intentioned projects if not examined through an equity lens. We find that intentional partner engagement is critical to equitable work. Partner organizations and community residents have provided us with feedback on our data collection tools. They let us know when they may not have felt included in our response options on a survey or when they felt that one of our questions has a “judgy tone.”

They also let us know what data is important for them so that we can integrate it into our work. For example, members of the Indigenous community in our area wanted to know what specific tribes were located in our region. We were able to build simple skip logic into our tool so that if someone indicated that they identified as American Indian / Alaska Native, they would be prompted to share their tribal membership. In a different example, based on the suggestion of a partner organization, we added a section for fathers and non-birthing parents to a survey we were developing after they noted that maternal and child health section was not as inclusive as it should be.

We also examine the roles of partner organizations and community residents beyond providing feedback and input on tools. Intentional engagement of partners is critical, whether through a Community Advisory Group or Memorandums of Understanding. Community-based organizations and community residents have helped us to frame questions and responses, think through recruitment strategies and how best to reach the audience that we want to hear from, and determine what incentives may work best for different groups of people.