Description
Genomics is the new frontier in clinical care and scientific discovery. Genomic assessments of oncogenes and tumor suppressor genes, that is gene loci associated with cancer development and prognosis, is rapidly becoming the standard of care for cancer.
Current molecular pathology reports are represented and stored in the electronic health record (EHR) as pdf documents and are not suitable for clinical decision support and data analytics. Incorporation of genetic data into the EHR as discrete data is not standard practice because of the complexity of the data itself (ADDIN RW.CITE{{2326 Warner,J.L. 2016; 2166 Masys,D.R. 2012}}(1, 2) and underrepresentation of genomic concepts in the SNOMED CT and LOINC concept models (ADDIN RW.CITE{{2327 Hoffman,M. 2005}}(3).
Investigators at the University of Nebraska Medical Center used the SNOMED CT observables concept model and authored fully defined observable entity concepts for genomic information including Next Generation Sequence (NGS) data and non-sequence based molecular data. These SNOMED CT concepts are deployed in the clinical information systems at UNMC beginning in the laboratory and molecular pathology information systems and bound to molecular observations. Encoded molecular data is then transmitted to the EHR and the institutional cancer tissue biobank and registry for clinical care, quality and research purposes.
References
1. Warner JL, Jain SK, Levy MA. Integrating cancer genomic data into electronic health records. Genome Med. 2016 Oct 26;8(1):113.
2. Masys DR, Jarvik GP, Abernethy NF, Anderson NR, Papanicolaou GJ, Paltoo DN, et al. Technical desiderata for the integration of genomic data into Electronic Health Records. J Biomed Inform. 2012 Jun;45(3):419-22.
3. Hoffman M, Arnoldi C, Chuang I. The clinical bioinformatics ontology: a curated semantic network utilizing RefSeq information. Pac Symp Biocomput. 2005:139-50.
Location: Nebraska, United States