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Emerging landscape of genomics in the electronic health record for personalized medicine
Author(s) -
UllmanCullere Mollie H.,
Mathew Jomol P.
Publication year - 2011
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.21456
Subject(s) - personalized medicine , health care , stakeholder , clinical decision support system , quality (philosophy) , knowledge management , genomics , precision medicine , data science , business , computer science , medicine , bioinformatics , public relations , biology , economics , economic growth , philosophy , biochemistry , epistemology , pathology , genome , political science , gene
The Information Technology (IT) roadmap for personalized medicine requires Electronic Health Records (EHRs), extension of Healthcare IT (HIT) standards, and understanding of how genetics/genomics should be integrated into the clinical applications. For reduced overall costs and development times, these three initiatives should run in parallel. EHRs must contain structured data and infrastructure that enables quality analysis, Clinical Decision Support (CDS) and messaging within the healthcare information network. Fortunately, as a result of sustained financial commitment to nongenetic‐based healthcare, the industry has HIT data standards and understanding of EHR functionality that improves patient safety and outcomes while reducing overall healthcare costs. However, the HIT standards and EHR functional requirements, needed for personalized medicine, are only beginning to support simple genetic tests and need significant extension. In addition, our understanding of the clinical implications of genomic data is evolving and translation of new discovery into clinical care remains a challenge. Therefore, priority areas include CDS, educational resources, and knowledgebases for the EHR, clinical and research data warehouses, messaging frameworks, and continued review of healthcare policies and regulations supporting personalized medicine. Where core infrastructure remains to be developed and implemented, funding is needed for pilot projects, data standards, policy, and stakeholder collaboration. Hum Mutat 32:1–5, 2011. © 2011 Wiley‐Liss, Inc.