Emerging landscape of genomics in the electronic health record for personalized medicine

Abstract

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.

comoR: a software for disease comorbidity risk assessment

“…In particular, the availability of these data sets for many different diseases presents a ripe opportunity to use data-driven approaches to advance our current knowledge of disease relationships in a systematic way. Patient’s genetic/genomic data is becoming important for clinical decision making, including disease risk assessment, disease diagnosis and subtyping, drug therapy and dose selection [44]. In the future, clinicians will have to consider genetic/genomic implications to patient care throughout their clinical workflow, including electronic prescribing of medications.…”

The integration and interpretation of pharmacogenomics – a comparative study between the United States of America and Europe: towards better health care

“…Various models for implementation of pharmacogenomic testing have been proposed in the US [44][45][46], and reviews into how pharmacogenomic information should be integrated into an electronic medical record (EMR) are available [47]. The RAPID GENE trial is the first study to show efficacy of a point-of-care pharmacogenomic test to determine antiplatelet treatment [48].…”

Integrating cancer genomic data into electronic health records

“…Perhaps the greatest challenge to the integration of genomic laboratory results into EHRs has been the lack of consistent standards for the unambiguous transfer of such information [85, 86]. While there are well-established nomenclatures for the representation of genetic variation, such as HUGO Gene Nomenclature Committee (HGNC) for gene names [87], Human Genome Variation Society (HGVS) for SNVs and indels [88], and International System for Human Cytogenetic Nomenclature (ISCN) for structural variation [89], applying these nomenclatures with vigor has not yet occurred in the clinical domain.…”