Today, the Office of the National Coordinator for Health Information Technology (ONC) has officially launched a new platform dedicated to organizing and building USCDI+ datasets. This user-friendly platform, located at https://uscdiplus.healthit.gov, provides a central location for accessing and exploring all USCDI+ datasets across various domains.

The wait is finally over! If you’ve been following ONC’s work on USCDI+ over the past year, you’ve likely heard discussion of a new platform for organizing and building out the various USCDI+ datasets. After several months of development and testing, the new platform is now live at https://uscdiplus.healthit.gov and will be the single location where USCDI+ datasets for all domains will be located.

MedStar Health Research Institute, a 2020 ONC Leading Edge Acceleration Project (LEAP) in Health IT awardee, has developed new Fast Healthcare Interoperability Resources (FHIR) platforms to support EHR data access for clinical research. In collaboration with the Georgetown University Medical Center and HealthLab, the MedStar project team developed two new tools to provide researchers access to standardized data for at-scale extraction and analysis. The tools, available via ONC’s GitHub repository (registration required), include the Bugs & Drugs FHIR Factory and the Trend Engine FHIR Factory. The framework for both data platforms performs automated, iterative data extraction, as well as transformation and integration of the data using FHIR application programming interfaces (APIs).

Researchers, developers, and clinicians have new tools to help them access high-quality electronic health record (EHR) data more effectively. A 2020 ONC Leading Edge Acceleration Project (LEAP) in Health IT awardee, MedStar Health Research Institute, in collaboration with the Georgetown University Medical Center and HealthLab, developed two new data tools as part of MedStar’s Fast Healthcare Interoperability Resources® (FHIR) Factories: An Evolving Digital Architecture to Scale Health Research project. The project team developed FHIR Factories, which are enhanced data platforms (or data factories) that provide researchers the ability to easily access data in standardized formats and to conduct at-scale extraction and analysis. These data factories use FHIR to transform data into actionable knowledge that is accessible via application programming interfaces (APIs) and bring that actionable knowledge to the frontlines of clinical care.

The nutrition-label proposal was published in April by the Office of the National Coordinator for Health Information Technology, a. . .part of HHS that certifies electronic health-record software. The ONC’s certification requirements function like industry regulations because this software typically must have the agency’s blessing before hospitals and doctors buy it. Under the proposal, an AI system’s nutrition label would show how the model was trained and tested, its intended uses and measures of its “validity and fairness.” The agency doesn’t mandate how the label would look, only that the information must be visible to doctors, hospital officials and others via their ONC-certified software. AI developers could choose not to disclose anything. But clinicians would be able to see that, too. “We do believe that blank fields would be very informative,” said Tripathi, the ONC leader.