Federal efforts to develop and improve payment models and other programs designed to foster health equity are often hamstrung by poor data: inconsistent data requests from program to program and flawed and incomplete data reporting by those participating in those programs.
As a result, federal policymakers often are unable to tell whether programs – both those developed specifically to address health equity and those that are not – are having the desired effect on health equity.
The result, according to a new study from the Centers for Medicare & Medicaid Services’ Center for Medicare and Medicaid Innovation, is that
1) The variable quality of race/ethnicity data in Medicare and Medicaid claims data presents a challenge for understanding whether models reach and enroll underserved individuals; 2) Model designs have not always considered needs specific to underserved individuals; and, 3) Model designs that do not prioritize the inclusion of underserved individuals may have small sample sizes for these populations that limits the ability to draw conclusions.
Learn more about the challenges federal policymakers faces in developing Medicare and Medicaid payment models that address health equity in its new analysis “Assessing Equity to Drive Health Care Improvements: Learnings from the CMS Innovation Center.”