Categorizing measures of health disparity by questions addressed, implicit assumptions, and data required

Objective: An important goal for the next 100 years will be eliminating health disparities. However, successful interventions aimed at reducing and eliminating health disparities rely upon accepted and accurate measurement of existing disparities. Although progress has been made toward standardizing health outcomes measurements, standard definitions of disparity indices based on such measurements have not been established. We sought to summarize commonly used difference measures and develop a typology for categorizing those measures based on data required and research questions of interest.

Methods: We conducted a literature review and organized studies by health outcomes, type of data, and measures of health status and disparity.

Results: The categorization reveals key differences between approaches regarding available data and questions addressed as well as providing a critical comparison between original questions of interest and questions answered by available data. The typology provides insight into which types of research questions a given class of tools may be most suitable in addressing.

Conclusion: Lack of specificity when referencing analytical tools used to determine health disparities can lead to inaccurate language in reports of observed health disparities. A better understanding of data requirements and types of questions addressable by different disparity measures can clarify conclusions both for researchers and their scientific and lay audiences, leading to more accurate, reliable, and comparable reporting of results.