Summary
Inclusion of individual's genetic variation data (e.g. specific genetic test results, SNPs, whole genome sequencing) in the EHR is becoming increasingly important for Personalised/Precision Medicine.
While it is possible to save such data using existing openEHR data structures and types, given the fact that the Bioinformatics domain has been enjoying good standardisation in terms of terminology, data, meta-data and protocols long before health informatics, an opportunity exists to more appropriately represent such data natively by possibly extending RM (or even creating a new Genomic RM!) and also by creating new family of archetypes to represent clinical genetics concepts. Thus we have decided to establish an authoritative group to further investigate and advise.
During 2018, a clinical modelling group was consisting of members from the CRS4 research institute in Sardinia, Italy; the HiGHmed project in Germany; the CINTESIS group in Porto, Portugal; the BigMed project in Norway, and the international openEHR clinical modelling programme. The objective of the group was to consolidate, enhance, review and publish a set of archetypes about genetic variants as lab results.
Initial Interest Group
Amnon Shabo (Shvo) (Philips)
Gianluigi Zanetti (CRS4 - Italy)
Patrik Georgii-Hemming (Karolinska)
Navin Ramachandran (UCL/NHS - OpenCancer)
Wai Keong Wong (UCL/NHS - OpenCancer)
Ian McNicoll (openEHR co-chair)
Koray Atalag (openEHR, Univ. of Auckland)
Thomas Beale (openEHR)
- Diego Bosca (VeraTech)
Related Work / Resources
- http://projects.iq.harvard.edu/smartgenomics/api
- Alterovitz G, Warner J, Zhang P, Chen Y, Ullman-Cullere M, Kreda D, et al. SMART on FHIR Genomics: Facilitating standardized clinico-genomic apps. Journal of the American Medical Informatics Association. 2015 Jul 21;ocv045.
- Genetic testing information standardization in HL7 CDA and ISO13606. https://www.ncbi.nlm.nih.gov/pubmed/23920572
- https://www.ncbi.nlm.nih.gov/pubmed/?term=29678078