Measuring health disparities and health inequities: do you have REGAL data?

Abstract

Measuring health disparities is a challenging and at times a difficult proposition. It is generally accepted that at minimum, collecting, analyzing, reporting, and applying data through tailored and targeted interventions responsive to issues regarding race, ethnicity, and preferred language are essential for identifying, monitoring, and, ultimately, eliminating health disparities. Key to eliminating these disparities is determining whether the care and services being provided are resulting in vastly different experiences for some patients. Health care institutions and providers often convince themselves that collecting these data is a time-consuming, costly, and arduous endeavor. However, if patient information on Race, Ethnicity, Gender, Age, and preferred Language (REGAL) is currently being collected, one has the basic elements to effectively measure disparities across a host of clinical and nonclinical indicators. In formulating comparisons among targeted populations in areas such as access to health care, health care quality, health outcomes, prevention, early detection, treatment, and morbidity and mortality rates, it is critical to frame part of the discussion around collecting, analyzing, reporting, and applying REGAL data, including future expansion of measures and indicators. The Health Disparities REGAL Data Dashboard is a useful tool for health care institutions and providers and can provide an innovative approach to measuring health disparities.