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. 2019 Oct 16;7(4):e15199.
doi: 10.2196/15199.

Fast Healthcare Interoperability Resources (FHIR) as a Meta Model to Integrate Common Data Models: Development of a Tool and Quantitative Validation Study

Affiliations

Fast Healthcare Interoperability Resources (FHIR) as a Meta Model to Integrate Common Data Models: Development of a Tool and Quantitative Validation Study

Emily Rose Pfaff et al. JMIR Med Inform. .

Abstract

Background: In a multisite clinical research collaboration, institutions may or may not use the same common data model (CDM) to store clinical data. To overcome this challenge, we proposed to use Health Level 7's Fast Healthcare Interoperability Resources (FHIR) as a meta-CDM-a single standard to represent clinical data.

Objective: In this study, we aimed to create an open-source application termed the Clinical Asset Mapping Program for FHIR (CAMP FHIR) to efficiently transform clinical data to FHIR for supporting source-agnostic CDM-to-FHIR mapping.

Methods: Mapping with CAMP FHIR involves (1) mapping each source variable to its corresponding FHIR element and (2) mapping each item in the source data's value sets to the corresponding FHIR value set item for variables with strict value sets. To date, CAMP FHIR has been used to transform 108 variables from the Informatics for Integrating Biology & the Bedside (i2b2) and Patient-Centered Outcomes Research Network data models to fields across 7 FHIR resources. It is designed to allow input from any source data model and will support additional FHIR resources in the future.

Results: We have used CAMP FHIR to transform data on approximately 23,000 patients with asthma from our institution's i2b2 database. Data quality and integrity were validated against the origin point of the data, our enterprise clinical data warehouse.

Conclusions: We believe that CAMP FHIR can serve as an alternative to implementing new CDMs on a project-by-project basis. Moreover, the use of FHIR as a CDM could support rare data sharing opportunities, such as collaborations between academic medical centers and community hospitals. We anticipate adoption and use of CAMP FHIR to foster sharing of clinical data across institutions for downstream applications in translational research.

Keywords: controlled vocabularies; data sharing; electronic health records; health information interoperability.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
An example of demographic data transformation. CAMP FHIR: Clinical Asset Mapping Program for Fast Healthcare Interoperability Resources; i2b2: Informatics for Integrating Biology & the Bedside.
Figure 2
Figure 2
The Clinical Asset Mapping Program fast healthcare interoperability resources (CAMP FHIR) pipeline as used for translator. CSV: comma-separated value; JSON: JavaScript Object Notation; PIT: Patient data Integration Tool.

References

    1. McMurry AJ, Murphy SN, MacFadden D, Weber G, Simons WW, Orechia J, Bickel J, Wattanasin N, Gilbert C, Trevvett P, Churchill S, Kohane IS. SHRINE: enabling nationally scalable multi-site disease studies. PLoS One. 2013;8(3):e55811. doi: 10.1371/journal.pone.0055811. http://dx.plos.org/10.1371/journal.pone.0055811 - DOI - DOI - PMC - PubMed
    1. Heerman WJ, Jackson N, Roumie CL, Harris PA, Rosenbloom ST, Pulley J, Wilkins CH, Williams NA, Crenshaw D, Leak C, Scherdin J, Muñoz D, Bachmann J, Rothman RL, Kripalani S. Recruitment methods for survey research: findings from the mid-south clinical data research network. Contemp Clin Trials. 2017 Nov;62:50–5. doi: 10.1016/j.cct.2017.08.006. - DOI - PubMed
    1. Voss EA, Makadia R, Matcho A, Ma Q, Knoll C, Schuemie M, DeFalco FJ, Londhe A, Zhu V, Ryan PB. Feasibility and utility of applications of the common data model to multiple, disparate observational health databases. J Am Med Inform Assoc. 2015 May;22(3):553–64. doi: 10.1093/jamia/ocu023. http://europepmc.org/abstract/MED/25670757 - DOI - PMC - PubMed
    1. Murphy SN, Weber G, Mendis M, Gainer V, Chueh HC, Churchill S, Kohane I. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) J Am Med Inform Assoc. 2010;17(2):124–30. doi: 10.1136/jamia.2009.000893. http://europepmc.org/abstract/MED/20190053 - DOI - PMC - PubMed
    1. Fleurence RL, Curtis LH, Califf RM, Platt R, Selby JV, Brown JS. Launching PCORnet, a national patient-centered clinical research network. J Am Med Inform Assoc. 2014;21(4):578–82. doi: 10.1136/amiajnl-2014-002747. http://europepmc.org/abstract/MED/24821743 - DOI - PMC - PubMed