Improving health equity is a priority for healthcare organizations, but many face challenges with inaccurate member race and ethnicity data and the increased administrative burden of collecting better, more detailed data. Additionally, structural racism and implicit bias in healthcare settings have led to the deprioritization of data collection efforts, which causes a lack of trust from populations who have experienced racism, making them hesitant to share information. 

This session will explain why current methods of collecting race and ethnicity data fail to capture the full diversity of patient populations. Attendees will learn why these data are crucial for evaluating and improving healthcare quality, especially when considering patients' lived experiences. Panelists will discuss the benefits of increased data accuracy, how this data can be used to address disparities in care, and how organizations can leverage technology to capture detailed, self-reported race and ethnicity data at scale with best practices for equity and inclusion to improve patient experience. 

You Will Learn:

• Early results for Phreesia’s 2023 pilot program and findings
• How the use of standardized question language to enable patients to self-report detailed race and ethnicity data across three phases. 
• Potential changes to national race and ethnicity standards (e.g., Office of Management and Budget categories)
• How to improve collection of key equity data elements, such as patient’s social needs, sexual orientation and gender identity