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J Am Med Inform Assoc. 2015 Nov;22(6):1173-8. doi: 10.1093/jamia/ocv045. Epub 2015 Jul 21.

SMART on FHIR Genomics: facilitating standardized clinico-genomic apps.

Author information

1
Children's Hospital Informatics Program, Boston, MA Center for Biomedical Informatics, Harvard Medical School, Boston, MA Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA ga@alum.mit.edu.
2
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN Department of Medicine, Division of Hematology/Oncology, Vanderbilt University, Nashville, TN.
3
Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA.
4
Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL.
5
Dana-Farber Cancer Institute, Boston, MA.
6
Center for Biomedical Informatics, Harvard Medical School, Boston, MA.
7
Children's Hospital Informatics Program, Boston, MA Center for Biomedical Informatics, Harvard Medical School, Boston, MA Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA.

Abstract

BACKGROUND:

Supporting clinical decision support for personalized medicine will require linking genome and phenome variants to a patient's electronic health record (EHR), at times on a vast scale. Clinico-genomic data standards will be needed to unify how genomic variant data are accessed from different sequencing systems.

METHODS:

A specification for the basis of a clinic-genomic standard, building upon the current Health Level Seven International Fast Healthcare Interoperability Resources (FHIR®) standard, was developed. An FHIR application protocol interface (API) layer was attached to proprietary sequencing platforms and EHRs in order to expose gene variant data for presentation to the end-user. Three representative apps based on the SMART platform were built to test end-to-end feasibility, including integration of genomic and clinical data.

RESULTS:

Successful design, deployment, and use of the API was demonstrated and adopted by HL7 Clinical Genomics Workgroup. Feasibility was shown through development of three apps by various types of users with background levels and locations.

CONCLUSION:

This prototyping work suggests that an entirely data (and web) standards-based approach could prove both effective and efficient for advancing personalized medicine.

KEYWORDS:

EHR; EMR; FHIR; HL7; SMART; clinicogenomics; data sharing; data warehouse; genomics; i2b2; standards

PMID:
26198304
DOI:
10.1093/jamia/ocv045
[Indexed for MEDLINE]

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