A Shift in Thinking: Principles for Building Equitable Public Health Data

Data influences decisions across public health, including how resources are allocated, the initiation, continuation or ending of projects and changes to policies and regulations. 

These decisions directly impact communities. It is critical that communities’ perspectives, experiences and priorities are reflected in the data, so that the data conveys the community story. This allows public health leaders and practitioners to better understand the health challenges we are trying to solve to improve daily lives.  

The CDC Foundation’s Principles for Using Public Health Data to Drive Equity, also known as the data equity principles, acknowledges the power data has in shaping community landscapes and encourages a shift in mindset to embed a focus on equity throughout the entire data life cycle.  

Historically, public health data often excludes community input and wisdom. Oftentimes, communities do not know how data collected about the health and wellbeing of their residents will be used and are not offered the opportunity to help shape the process.  

The data equity principles prioritize deeper community engagement and connect the social and economic factors that impact health.  They build on thought leadership across the fields of public health and equitable data to reinforce a shift in perspective and practices that many field leaders are endorsing. The five data equity principles are: 

1. Recognize and define systemic factors: Recognize and define systemic, social and economic factors that affect individual health outcomes and communities’ ability to thrive. 
2. Use equity-mindedness as the guide for language and action: Use equity-mindedness as the guide for language and action in a continual process of learning, disaggregating data and questioning assumptions about relevance and effectiveness. 
3. Allow for cultural modification: Proactively include participants from the communities of interest in research and program design to allow for cultural modifications to standard data collection tools, analysis and sharing. 
4. Create shared data agreements: Collaborate with agencies and the community to generate a shared data development agenda ensuring a plan for data completeness, access and prioritized use to answer high-interest questions. 
5. Facilitate data sovereignty: Facilitate data sovereignty by paving the way for communities to govern the collection, ownership, dissemination and application of their data. 

There is an opportunity to embed equitable approaches at every stage of the data life cycle while public health practitioners are planning, collecting, analyzing and sharing data.  

Equitable data practices create the ability for government, local and private organizations to work with community partners to collaboratively design research plans, identify barriers and community assets and, ultimately, dismantle the underlying causes of health disparities.  

All of us have a role to play in building data that reflects all members of our communities. 

Moving toward more equitable data practices happens in various spheres, such as research and program management, across sectors such as social services, philanthropy and public health, and across organizational levels, such as local, state and federal government. The principles are also a reminder that every public health practitioner has the opportunity across the data life cycle to improve the equity of their data systems in some way. 

By shifting approaches to data planning, collection, analysis and interpretation, use and sharing, public health data becomes a better reflection of everyone’s life experiences providing opportunities for health in all corners of our communities.  

To learn more about the data equity principles, visit the CDC Foundation’s website.  

Lauren Smith, MD, MPH is the chief health equity and strategy officer for the CDC Foundation