Data is power. 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. If we do not address power dynamics in the creation of research, at best, we are driving decision-making from partial truths. At worst, we are generating inaccurate information that ultimately does more harm than good. Data equity frameworks provide us with tools to help identify and assess biases at each phase of the research process. We adopted a data equity framework and adapted it to suit our work as a Regional Health Improvement Collaborative. We discuss transparency, inclusion, partnerships, and intentional engagement as essential elements to advancing data equity.
2. Identify components of a data equity framework by answering the following questions: why are we doing this work, what will its impact be, who will be involved and when, how will we communicate our findings?
3. Describe effective strategies for implementing data equity principles.