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ONC-Funded FHIR Project for Patient Data Access Takes Health Equity Focus

Researchers identified the preferences of a diverse group of patients to create a FHIR-based platform for patient data access that could help boost health equity.

The University of Texas at Austin’s Dell Medical School (Dell Med) has developed a health equity-focused patient engagement platform that supports patient data access through FHIR.

Dell Med developed the tool as a 2019 ONC Leading Edge Acceleration Projects (LEAP) for Health IT program awardee.

The team proposed developing a patient engagement technology platform using application programming interfaces (APIs) and FHIR and SMART on FHIR, the same national standards used by EHRs.

Researchers developed the FHIRedApp using human-centered design methodology to identify the preferences of a group of Latino, African American, and Asian American patients.

The Dell Med team held 20 Community Engagement Studio (CES) sessions with ethnically and racially diverse patients from Central Texas. The process involved beta testing, semi-structured interviews, and pilot testing with participants to ensure the tool’s usability.

A community navigator led each CES session. Discussion topics included community health experiences, community readiness, design preferences, adoption, and sustainability.

Insights gathered from the CES sessions helped identify features and capabilities that ethnically and racially diverse patients desired from a health app.

The FHIRedApp will be able to connect to FHIR API endpoints provided by certified EHR technologies required by the ONC Cures Act Final Rule. Additionally, the platform can leverage health information exchanges (HIEs) and research networks, which act as data aggregators from multiple EHRs.

The platform also allows patients to access their data, grant access to all or part of their data, and make it available to third-party app developers via FHIR APIs.

The Dell Med team is currently developing a pilot app to assist with recruitment for clinical research studies and integration with social services referral networks.

In the future, the team and community members hope to offer additional features and enhancements to the platform and test scalability using other HIEs and data sources.

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