Genomics Inform.  2013 Dec;11(4):186-190. 10.5808/GI.2013.11.4.186.

Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care

Affiliations
  • 1Department of Medical Informatics, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.
  • 2Department of Medical Informatics, MRC, IRCGP, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.
  • 3Department of Clinical Laboratory, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.
  • 4Open Source Electronic Health Record Agent (OSEHRA), Arlington Innovation Center, Virginia Tech, Arlington, VA 22203, USA.
  • 5Department of Microbiology, Department of Medical Informatics, Integrated Research Center for Genome Polymorphism (IRCGP), MRC, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea. yejun@catholic.ac.kr

Abstract

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

Keyword

clinical data warehouse; database; electronic health records; medical informatics

MeSH Terms

Biology
Computational Biology
Confidentiality
Delivery of Health Care
Electronic Health Records
Genome
Human Genome Project
Humans
Informatics
Medical Informatics*
Pathology, Molecular
Privacy
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