Improving health equity is a priority for health care organizations, but many are challenged with inaccurate data on member race and ethnicity, and concerns about increased administrative burden to collect better, more detailed data. Structural racism and implicit bias in care delivery settings have contributed to deprioritization of data collection efforts and a lack of trust from populations that have experienced racism, making them reluctant to share these data. 

This session will cover why current systems of collecting race and ethnicity data do not capture the full diversity of patient populations and the importance of these data in evaluating and improving healthcare quality, grounded in the perspective of patients’ lived experience. Panelists will discuss how health care organizations can leverage technology to capture detailed, self-reported race and ethnicity data at scale with best practices for equity and inclusion. These approaches can enable organizations to collect and use more inclusive, standardized data sets and improve patient experience when answering questions about race and ethnicity. 

Phreesia will share early results from a 2023 pilot program to test the use of detailed, standardized question language and enable patients to self-report detailed race and ethnicity data across three phases. Panelists will discuss how increased data accuracy can benefit patients, and the health care industry at large, and can be used to address disparities in care. The presentation will also discuss implications from the pilot’s findings for changes to national race and ethnicity standards (e.g., Office of Management and Budget categories), and how they can inform improved collection of other key equity data elements, such as information about a patient’s social needs, sexual orientation and gender identity, patient-reported outcomes and more.