Pilot Project 4.2 – Feasibility Study of Indexing Clinical Research Data Using HL7 FHIR

Leader: Guoqian Jiang, MD, PhD, Mayo Clinic College of Medicine

The overall goal of the pilot project is to design, develop and evaluate a prototype of clinical research data discovery index (crDDI) leveraging both standards-based representation and scalable Semantic Web technologies. The ultimate goal is to advance clinical research data discovery and analytic capabilities for clinical and translational centers and investigators. HL7 Fast Healthcare Interoperability Resources (FHIR) is an emerging HL7 standard that provides a consistent, easy to implement, and rigorous mechanism for exchanging data between healthcare applications. In this pilot study, we will demonstrate the feasibility of indexing clinical research datasets through the transformation of corresponding data dictionaries into a common format using an indexing schema tailored from the HL7 FHIR. Specifically, we will leverage existing technologies with tools developed in our previous and ongoing projects to create methods and tools for 1) indexing clinical research data using standard HL7 FHIR resources and 2) exposing and validating FHIR-based metadata in clinical research datasets. We will test out our indexing schema through using the clinical research datasets available from existing NIH pilot data commons: dbGaP and TCGA.