Department of Health
and Human Services (HHS)
and Human Services (HHS)
July 30, 2020
NOT-OD-19-122 - Fast Healthcare Interoperability Resources (FHIR ) Standard
NOT-OD-19-150 - Request for Information (RFI): Use of the Health Level Seven International (HL7 ) Fast Healthcare Interoperability Resources (FHIR ) for Capturing and Sharing Clinical Data for Research Purposes
NOT-OD-19-014 - Request for Information (RFI) on Proposed Provisions for a Draft Data Management and Sharing Policy for NIH Funded or Supported Research
NOT-OD-18-134 - Request for Information (RFI): Soliciting Input for the National Institutes of Health (NIH) Strategic Plan for Data Science
Office of The Director, National Institutes of Health (OD)
Purpose
The purpose of this notice is to encourage NIH-supported clinical research programs and researchers to adopt and use the standardized set of data classes, data elements, and associated vocabulary standards specified in the United States Core Data for Interoperability (USCDI) standard.[1] The use of USCDI will facilitate the use of clinical data in research studies and enable greater consistency in clinical research data that are shared.
Background
USCDI will enable NIH researchers to benefit from the opportunities created by the increased availability of clinical data from electronic health record (EHR) systems for research and improved approaches for making data from a single research study useful for other research endeavors. It can complement use of the HL7 Fast Healthcare Interoperability Resources (FHIR ) standard,[2] which NIH encouraged researchers to use in a Guide Notice[3] issued on July 30, 2019 to facilitate researcher access to clinical data in EHRs and to facilitate the sharing of research data. While the use of FHIR will enable the standardized sharing of health information for research, it is also critical to ensure the underlying data are consistently structured to enable research data sharing and discovery at scale.
The USCDI will enable researchers to leverage structured clinical data for research and enhance the ability to aggregate research data sets and enable discovery. USCDI defines the coding systems required for different classes of data applicable to all of the US clinical data exchange standards. On May 1, 2020, the Office of the National Coordinator for Health Information Technology (ONC) published the Cures Act Final Rule, which requires that EHR systems certified under the ONC’s Health Information Technology (IT) Certification Program adopt and use USCDI v1.[4] Most of the clinical data covered by the USCDI has been required for EHR certification since 2012.[5] Therefore, USCDI-organized data currently exist in EHR systems for research use.
Adoption of USCDI will allow care delivery and research organizations to use the same coding systems for key data elements that are part of the USCDI data classes. The USCDI includes widely adopted coding systems that are supported by the National Library of Medicine (NLM) and are important to the interoperable exchange of electronic health data, such as, RxNorm[6] for medications, SNOMED CT [7] for conditions and many specialized terms, and LOINC[8] for tests and measurement. This coding consistency is essential to data aggregation across health care organizations, as has been important to the tracking of the COVID-19 epidemic. NLM-supported USCDI code systems are used to organize clinical data in smart phone-based mobile health applications and across several institutional research systems [9] [10] [11].
Leveraging the USCDI to Accelerate Discovery
NIH research investments generate and leverage vast amounts of data, and ensuring those data are findable, accessible, interoperable, and reusable (FAIR) can be achieved in part through more consistent use of data standards.[12],[13] The widespread adoption of EHR systems has increased the availability of electronic health data and created a tremendous opportunity for clinical, biomedical, and health services researchers.
Through this notice, NIH encourages NIH-supported clinical programs and researchers to adopt and use the standardized set of healthcare data classes, data elements, and associated vocabulary standards in the USCDI v1, as they are applicable, to enable greater interoperable exchange of health information for clinical care and research. As with all NIH-funded or supported research involving human participants, and as is currently the expectation using USCDI, investigators must obtain participant consents and follow applicable national, tribal, and state laws and regulations, as well as relevant institutional policies, for the protection of human subjects.
About the USCDI
USCDI is composed of 15 data classes which are an aggregation of various data elements by a common theme or use case (e.g., patient demographics, clinical notes) [14]. Each data class is composed of one or more data elements, which are the most granular level at which a piece of data is represented in the USCDI for exchange (e.g., date of birth, discharge summary note). The data classes have different scopes and levels of detail. A few enumerate a small list of specific variables that could be exchanged, such as the Vital Signs class. Others specify the coding system for identifying a large class of items without saying anything about individual class members (i.e., data elements). For example, the medication class specifies the uses of RxNorm to identify medication carried in message without calling out any specific medicine.
USCDI v1 expands on data long-required to be supported by certified EHRs including: updated versions of vocabulary standard code sets; new data classes (i.e., allergies and intolerances, clinical notes, and provenance); and new data elements (i.e., current and previous address; phone number and phone number type; and pediatric vital signs). These latest enhancements will support improvements in patient matching, the development of a longitudinal record, better access to information for research purposes, and inclusion of standardized metadata information about who, when, and where data were collected. Moving forward, ONC will follow a predictable, transparent, and collaborative process to expand the USCDI, including providing stakeholders the opportunity to comment on the USCDI’s expansion.
[1] https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi
[3] https://grants.nih.gov/grants/guide/notice-files/NOT-OD-19-122.html
[4] https://www.healthit.gov/curesrule
[5] https://www.federalregister.gov/documents/2013/11/04/2013-26290/2014-edition-electronic-health-record-certification-criteria-revision-to-the-definition-of-common
[6] https://www.nlm.nih.gov/research/umls/rxnorm/index.html
[9] https://www.ohdsi.org/data-standardization/the-common-data-model/
[11] https://ncats.nih.gov/ctsa
[12] https://datascience.nih.gov/news/nih-releases-strategic-plan-data-science
[13] https://www.nlm.nih.gov/pubs/plan/lrp17/NLM_StrategicReport2017_2027.html
[14] https://www.healthit.gov/isa/sites/isa/files/2020-03/USCDI-Version1-2020-Final-Standard.pdf
Office of Data Science Strategy
National Institutes of Health
Email: datascience@nih.gov