Yearb Med Inform 2017; 26(01): 139-147
DOI: 10.15265/IY-2017-018
Section 6: Knowledge Representation and Management
Survey
Georg Thieme Verlag KG Stuttgart

Representing Knowledge Consistently Across Health Systems

S. T. Rosenbloom1, 2, 3, R. J. Carroll1, J. L. Warner1, 3, 4, M. E. Matheny1, 3, 5, 6, J. C. Denny1, 3
  • 1Department of Biomedical Informatics, Vanderbilt University Medical Center
  • 2Department of Pediatrics, Vanderbilt University Medical Center
  • 3Department of Medicine, Vanderbilt University Medical Center
  • 4Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center
  • 5Geriatrics Research Education and Clinical Care, Tennessee Valley Healthcare System VA
  • 6Department of Biostatistics, Vanderbilt University Medical Center
  • All affiliations: Nashville, TN, USA
Further Information

Publication History

Publication Date:
11 September 2017 (online)

Summary

Objectives: Electronic health records (EHRs) have increasingly emerged as a powerful source of clinical data that can be leveraged for reuse in research and in modular health apps that integrate into diverse health information technologies. A key challenge to these use cases is representing the knowledge contained within data from different EHR systems in a uniform fashion.

Method: We reviewed several recent studies covering the knowledge representation in the common data models for the Observational Medical Outcomes Partnership (OMOP) and its Observational Health Data Sciences and Informatics program, and the United States Patient Centered Outcomes Research Network (PCORNet). We also reviewed the Health Level 7 Fast Healthcare Interoperability Resource standard supporting app-like programs that can be used across multiple EHR and research systems.

Results: There has been a recent growth in high-impact efforts to support quality-assured and standardized clinical data sharing across different institutions and EHR systems. We focused on three major efforts as part of a larger landscape moving towards shareable, transportable, and computable clinical data.

Conclusion: The growth in approaches to developing common data models to support interoperable knowledge representation portends an increasing availability of high-quality clinical data in support of research. Building on these efforts will allow a future whereby significant portions of the populations in the world may be able to share their data for research.