ONC LEAP Program Adds SDOH, AI-Focused Projects

Aug. 13, 2021

University of Texas at Austin researchers will use the FHIR standard to integrate a closed-loop social services referral system

David Raths

The University of Texas at Austin and DARTNet Institute have received grant funding from the Office of the National Coordinator for Health IT as part of the Leading Edge Acceleration Projects (LEAP) in Health IT program.

Each year since 2018, ONC has made LEAP in Health IT awards to entrepreneurial groups dedicated to developing and scaling technological breakthroughs. Together, these awardees bring forth solutions to advance research capabilities and improve care delivery. For instance, in 2020, CRISP, the Maryland statewide health information exchange, and the American College of Cardiology worked on using the FHIR standard both in the acquisition of clinical data for registry submission as well as the subsequent use of clinical data to improve care decisions.

For 2021, LEAP in Health IT focused on two areas of interest:

• Referral Management to Address Social Determinants of Health (SDOH) Aligned with Clinical Care, and

• Health IT Tools to Make Electronic Health Record (EHR) Data Research- and Artificial Intelligence (AI)-Ready.

Integrating social determinants of health (SDOH) data into EHRs provides valuable context around how a person’s living conditions can impact their health, ONC noted. However, merging SDOH data with data in EHRs is only the starting point. To maximize the use of SDOH data, it also needs to be integrated into a closed-loop system to ensure that patient hand-offs are completed seamlessly, to prevent gaps in care from happening when patients are referred or transferred to other care providers.

The University of Texas at Austin will be working to create an Application Programming Interface (API)-enabled Social and Health Information Platform using the FHIR standard to integrate a closed-loop social services referral system. The system will be accessible to the EHRs used by Federally Qualified Health Centers (FQHCs) to leverage SDOH data.

The system will be used to:

Manage social needs identified in clinical settings;
Exchange information between clinical providers and community-based organizations;
Integrate clinical workflows in EHRs; and
Provide patient access, consent, and navigation via a mobile platform

The system will leverage the use cases developed by the Gravity Project, an HL7 FHIR accelerator, for the collection of SDOH data related to food security, housing stability, and transportation access.

The nonprofit DARTNet Institute has created a federated network that includes 85 healthcare organizations, 13 academic medical centers, 3,000 clinicians, and extensive electronic health record repositories. It will be working to make clinical data usable for research and by AI-enabled machine learning models. DARTNet will be partnering with Cloud Privacy Labs, a privacy technology company, to build and evaluate a data processing framework. The framework will use innovative technologies to enable semantic harmonization of health data collected from multiple small and large sized healthcare provider EHR systems.

The collection of this data will provide the type of high-quality health data sets needed for training AI based models and research needs.