Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care
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 differen...
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| Format: | Article |
| Language: | English |
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BioMed Central
2013-12-01
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| Series: | Genomics & Informatics |
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| Online Access: | http://genominfo.org/upload/pdf/gni-11-186.pdf |
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| author | In Young Choi Tae-Min Kim Myung Shin Kim Seong K. Mun Yeun-Jun Chung |
| author_facet | In Young Choi Tae-Min Kim Myung Shin Kim Seong K. Mun Yeun-Jun Chung |
| author_sort | In Young Choi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c60f8762a0f24f5a9a911dc9e37c5857 |
| institution | Kabale University |
| issn | 1598-866X 2234-0742 |
| language | English |
| publishDate | 2013-12-01 |
| publisher | BioMed Central |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj-art-c60f8762a0f24f5a9a911dc9e37c58572025-02-02T09:22:28ZengBioMed CentralGenomics & Informatics1598-866X2234-07422013-12-0111418619010.5808/GI.2013.11.4.18655Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical CareIn Young Choi0Tae-Min Kim1Myung Shin Kim2Seong K. Mun3Yeun-Jun Chung4Department of Medical Informatics, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.Department of Medical Informatics, MRC, IRCGP, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.Department of Clinical Laboratory, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.Department of Medical Informatics, The Catholic University of Korea College of Medicine, Seoul 137-701, Korea.Department 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.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.http://genominfo.org/upload/pdf/gni-11-186.pdfclinical data warehousedatabaseelectronic health recordsmedical informatics |
| spellingShingle | In Young Choi Tae-Min Kim Myung Shin Kim Seong K. Mun Yeun-Jun Chung Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care Genomics & Informatics clinical data warehouse database electronic health records medical informatics |
| title | Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care |
| title_full | Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care |
| title_fullStr | Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care |
| title_full_unstemmed | Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care |
| title_short | Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care |
| title_sort | perspectives on clinical informatics integrating large scale clinical genomic and health information for clinical care |
| topic | clinical data warehouse database electronic health records medical informatics |
| url | http://genominfo.org/upload/pdf/gni-11-186.pdf |
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