RAISE: elevating person-centered data for healthy communities.

Area of Science:

• Health Informatics
• Public Health Data Science
• Healthcare Data Management

Background:

• Accurate population characterization is essential for addressing unmet medical needs.
• Existing healthcare data systems often lack comprehensive person-centered demographic information.
• Standardizing the collection and curation of race and ethnicity data is a critical challenge.

Purpose of the Study:

• To improve the standard of collection and curation of race and ethnicity data in healthcare through the RAISE initiative.
• To share solutions and address barriers in collecting, curating, and sharing demographic data.
• To provide a resource for organizations to transform data systems for healthier communities.

Main Methods:

• Conducted 11 virtual workshops with diverse stakeholders from healthcare, technology, government, and community sectors.
• Summarized workshop proceedings into thematic areas.
• Developed a multidimensional action framework based on community polling and workshop learnings.

Main Results:

• Identified common barriers and shared solutions for demographic data reporting, collection, curation, and sharing.
• Created an action framework to address critical gaps in person-centered data collection.
• Highlighted the importance of community partnership in developing reliable data systems.

Conclusions:

• Community partnership and collaboration are central to creating effective data systems.
• Intentionality, standards, education, and respect are crucial for co-creating data systems that support health equity.
• The RAISE initiative provides a model for improving person-centered data collection to advance healthcare and community well-being.