Integration of Genomic Data in Electronic Health Records

U. Sax; S. Schmidt

doi:10.1055/s-0038-1634006

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2005; 44(04): 546-550
DOI: 10.1055/s-0038-1634006

Original Article

Schattauer GmbH

Integration of Genomic Data in Electronic Health Records

Opportunities and Dilemmas

U. Sax

¹Children's Hospital Informatics Program (CHIP), Harvard-MIT Division of Health Sciences and Technology, Children’s Hospital Boston, Boston, Massachusetts, USA

³Harvard Medical School, Boston, Massachusetts, USA

,

S. Schmidt

²Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts, USA

³Harvard Medical School, Boston, Massachusetts, USA

› Author Affiliations

Abstract

Summary

Objectives: In this paper we give an overview about the challenge the postgenomic era poses on biomedical informaticists. The occurrence of new (genomic) data types necessitates new data models, new viewing metaphors and methods to deal with the disclosure of genomic data. We discuss integration issues when inferring phenotype and genotype data. Another challenge is to find the right phenotype to genotype data in order to get appropriate case numbers for sound clinical genotype-phenotype inference studies.

Methods: Genomic data could be integrated in an Electronic Health Record (EHR) in several ways. We describe patient-centered and pointer-based integration strategies and the corresponding data types and data models. The inference mechanisms for the interpretation of raw data contain different agents. We describe vertical, horizontal and temporal agents.

Results: We have to deal with several new data types, not being standardized for EHR integration. Genomic data tends to be more structured than phenotype data. Beyond the development of new data models, vertical, horizontal and temporal agents have to be developed in order to link genotype and phenotype. As the genomic EHR will contain very sensitive data, confidentiality and privacy concerns have to be addressed.

Conclusions: Given the necessity to capture both environment and genomic state of a patient and their interaction, clinical information systems have to be redesigned. While genotyping seems to be automatable easily, this is not the case for clinical information. More integration work on terminologies and ontologies has to be done.

Keywords

Human genome - phenotype - genotype - personal health record - hospital information systems - medical informatics - bioinformatics

Full Text

References

References
1 Venter JC, Adams MD, Myers EW. et al The sequence of the human genome. Science 2001; 291 5507 1304-51.
2 Istrail S, Sutton GG, Florea L. et al Whole-genome shotgun assembly and comparison of human genome assemblies. Proc Natl Acad Sci USA 2004; 101 (07) 1916-21.
3 Cerner Expands Industry Lead with Genome- Enabled Information System. Cerner Solutions. Available at http://www.cerner.com/public/NewsReleases_1a.asp?id=257&cid=220 Accessed February 10, 2005
4 Ford 2nd JH, Turner A, Yoshii A. Information requirements of genomics researchers from the patient clinical record. J Healthc Inf Manag 2002; 16 (04) 56-61.
5 Kohane IS. Bioinformatics and clinical informatics: the imperative to collaborate. J Am Med Inform Assoc 2000; 7 (05) 512-6.
6 Giere W. Electronic Patient Information – Pioneers and Much More; A Vision, Lessons Learned, and Challenges. Methods Inf Med 2004; 43 (05) 543-52.
7 Klar R. Selected Impressions on the Beginning of the Electronic Medical Record and Patient Information. Methods Inf Med 2004; 43 (05) 537-42.
8 HL7 Clinical Genomics SIG. HL7 Clinical Genomics SIG San Diego Meeting Minutes Jan 21-22, 2004. HL7. Available at http://tinyurl.com/4ducz Accessed February 10, 2005
9 Malin B, Sweeney L. How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems. J Biomed Inform 2004; 37 (03) 179-92.
10 Malin BA. An Evaluation of the Current State of Genomic Data Privacy Protection Technology and a Roadmap for the Future. J Am Med Inform Assoc Nov 18 2004
11 Kaiser J. Biobanks. Population databases boom, from Iceland to the U.S. Science 2002; 298 5596 1158-61.
12 W3C WWWC. Extensible Markup Language (XML). Available at http://www.w3.org/XML/,2003
13 Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. Gen Bank. Nucleic Acids Res 2003; 31 (01) 23-7.
14 Boeckmann B, Bairoch A, Apweiler R. et al The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res 2003; 31 (01) 365-70.
15 Kihara D, Skolnick J. The PDB is a covering set of small protein structures. J Mol Biol 2003; 334 (04) 793-802.
16 Spellman PT, Miller M, Stewart J. et al Design and implementation of microarray gene expression markup language (MAGE-ML). Genome Biol 2002; 3 (09) RESEARCH0046
17 DNA Sequencing Costs Continue to Decline. Future Pundit. Available at http://www.futurepundit.com/archives/002038.html Accessed 14.01.2005
18 Sherry ST, Ward MH, Kholodov M. et al dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001; 29 (01) 308-11.
19 Buckingham S. Bioinformatics: data’s future shock. Nature 2004; 428 6984 774-7.
20 Rebhan M, Chalifa-Caspi V, Prilusky J, Lancet D. Gene Cards: a novel functional genomics compendium with automated data mining and query reformulation support. Bioinformatics 1998; 14 (08) 656-64.
21 Becker KG, Barnes KC, Bright TJ, Wang SA. The genetic association database. Nat Genet 2004; 36 (05) 431-2.
22 Bioinformatics at EMBL Heidelberg. European Molecular Biology Laboratory. Available at http://www-db.embl.de/jss/EmblGroupsHD/serv_0?t=1&p=1#serv34 Accessed February 10, 2005
23 Wheeler DL, Church DM, Edgar R. et al Database resources of the National Center for Biotechnology Information: update. Nucleic Acids Res 2004; 32 Database issue D35-40.
24 Shabo A. Reusable Genotype R-MIM V0.4. HL7 Clinical-Genomics SIG. 2004-03-14. Available at http://www.hl7.org/library/committees/clingenomics/HL7-Clinical-Genomics-Genotype-Model-0.4.zip Accessed February 10, 2005
25 Dolin RH, Alschuler L, Beebe C. et al The HL7 Clinical Document Architecture. J Am Med Inform Assoc 2001; 8 (06) 552-69.
26 Dolin RH, Altschuler L, Boyer S, Beebe C, Behlen FM, Biron PV. HL7 Clinical Document Architecture (Release 2.0). Health Level Seven, Inc. Available at http://hl7.org/library/Committees/structure/CDA.ReleaseTwo.CommitteeBallot03 Aug.2004.zip. Accessed February 9, 2005
27 McDonald CJ, Huff SM, Suico JG. et al LOINC, a universal standard for identifying laboratory observations: a 5-year update. Clin Chem 2003; 49 (04) 624-33.
28 Bray B. The PICNIC approach to regional care networks. Stud Health Technol Inform 2003; 96: 80-7.
29 Heitmann KU, Schweiger R, Dudeck J. Discharge and referral data exchange using global standards – the SCIPHOX project in Germany. Int J Med Inf 2003; 70 2-3 195-203.
30 Snow D. Mayo Amassed Mounds of Data. Wired News. Available at http://www.wired.com/news/medtech/0,1286,61633,00.html?tw=wn_tophead_4 Accessed February 10, 2005
31 Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res 2004; 32 Database issue D267-70.
32 Holloway E. Meeting Review: From Genotype to Phenotype: Linking Bioinformatics and Medical Informatics Ontologies. Comp Funct Genom 2002; 2002 (03) 447-50.
33 Verschelde J-L, Dos Santos MC, Deray T, Smith B, Ceusters W. Ontology-assisted database integration to support natural language processing and biomedical data-mining. Journal of Integrative Bioinformatics, 15.01.2004 2004(0001, 2004)
34 Klein TE, Altman RB. Pharm GKB: the pharmacogenetics and pharmacogenomics knowledge base. Pharmacogenomics J 2004; 4 (01) 1
35 Riva A, Mandl KD, Oh DH. et al The personal internetworked notary and guardian. Int J Med Inf 2001; 62 (01) 27-40.
36 Guardian Angel – Personal Lifelong Active Medical Assistant. MIT CDM. Available at http://www.ga.org/ga/ February 10 2005
37 Karasavvas KA, Baldock R, Burger A. Bioinformatics integration and agent technology. J Biomed Inform 2004; 37 (03) 205-19.
38 Lin Z, Owen AB, Altman RB. Genetics. Genomic research and human subject privacy. Science 2004; 305 5681 183
39 HL7 OID Registry. HL7 Inc. Available at http://www.hl7.org/oid/mem_index.cfm Accessed February 10, 2005
40 FAct Sheet UMLS Metathesaurus. National Library of Medicine. Available at http://www.nlm.nih.gov/pubs/factsheets/umlsmeta.html Accessed February 10, 2005
41 Biomedical Information Science and Technology Initiative (BISTI): National Centers for Biomedical Computing. National Institutes of Health. Available at http://www.bisti.nih.gov/ncbc/index.cfm Accessed February 10, 2005
42 Kohane I, Glaser J. Informatics for Integrating Biology and the Bedside (I2B2). Available at http://www.i2b2.org/index2.html Accessed February 10, 2005
43 Jadad AR, Delamothe T. What next for electronic communication and health care?. Bmj 2004; 328 7449 1143-4.
44 IBM_Research. Genomics Messaging System (GMS). IBM Haifa Labs. Available at http://www.haifa.il.ibm.com/projects/software/imr/gms.html Accessed February 10, 2005