Advertisement

The Case for a Pediatric Terminology

  • George R. Kim
  • Samuel Trent Rosenbloom
Part of the Health Informatics book series (HI)

Abstract

Terminologies are structured collections of designations (“terms”) that describe entities and relationships that represent the knowledge within a given domain.1,2 Terms may consist of words, phrases, or other notations (such as numbers or symbols), and are designed to support communication, storage, retrieval, and use of knowledge and information by humans and machines. An example is the clinical entity of “blood pressure measured during the diastolic phase of the cardiac cycle,” which is designated (in the terminology SNOMED CT) by the preferred term “Diastolic blood pressure” and the concept identifier “271650006.” Terminologies can formally define and specify representation of information content, and when used with messaging standards, can support structured information exchange among different electronic patient care systems. Terminologies have been developed with differing levels of rigor, and best practices have been described.2,8

Keywords

Health Information Technology Unify Medical Language System Electronic Health Record System National Drug File Reference Terminology Patient Safety Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Shortliffe E, Cimino J. Glossary. From Biomedical Informatics: Computer Applications in Health Care and Biomedicine. 3rd ed. New York: Springer; 2006: 992.Google Scholar
  2. 2.
    Rosenbloom ST, Miller RA, Johnson KB, Elkin PL, Brown SH. Interface terminologies: facilitating direct entry of clinical data into electronic health record systems. J Am Med Inform Assoc. 2006;13:277–288.PubMedCrossRefGoogle Scholar
  3. 3.
    Dolin RH, Mattison JE, Cohn S, Campbell KE, et al. Kaiser permanente's convergent medical terminology. Medinfo. 2004;11(Pt 1):346–350.Google Scholar
  4. 4.
    Medicomp Systems, Inc. Medcin Website; 2008. Available at: http://www.medicomp.com. Accessed December 27, 2007.
  5. 5.
    Columbia University Department of Biomedical Informatics. Medical Entities Dictionary Website; 2007. Available at: http://med.dmi.columbia.edu/. Accessed December 27, 2007.
  6. 6.
    US Department of Health and Human Services Office of the National Coordinator for Health Information Technology (ONC). Consolidated Health Informatics. Available at: http://www. hhs.gov/healthit/chi.html. Accessed December 12, 2007.
  7. 7.
    US Agency for Healthcare Research and Quality. Consolidated Health Informatics, United States Health Informatics Knowledgebase; 2005. Available at: http://ushik.org/chi/. Accessed December 19, 2007.
  8. 8.
    Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med. 1998;37(4–5):394–403.PubMedGoogle Scholar
  9. 9.
    Federative Committee on Anatomical Terminology. Terminologia Anatomica. Stuttgart, Germany: Thieme; 1998.Google Scholar
  10. 10.
    van Regenmortel MHV et al. eds. Virus Taxonomy. Classification and Nomenclature of Viruses, Seventh Report of the International Committee on Taxonomy. New York/San Diego, CA: Academic; 1999.Google Scholar
  11. 11.
    National Cancer Institute. The NCI Terminology Browser/EVS Browser Portal; 2008. Available at: http://bioportal.nci.nih.gov/ncbo/faces/index.xhtml. Accessed December 21, 2008.
  12. 12.
    Gene Ontology. Gene Ontology Home; 2008. Available at: http://www.geneontology.org/. Accessed December 21, 2008.
  13. 13.
    Hammond WH, Cimino JJ. Standards in biomedical informatics. In: Shortliffe EH et al., ed. Biomedical Informatics: Computer Applications in Health Care and Biomedicine. New York: Springer; 2006: 265–311.Google Scholar
  14. 14.
    International Organization for Standardization. ISO 1087-1 2000 Terminology Work — Vocabulary, Part 1 (Theory and application); 2000. Available at: http://www.iso.org/iso/ iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=20057. Accessed December 20, 2008.
  15. 15.
    International Organization for Standardization. ISO 1087-2 2000 Terminology Work — Vocabulary, Part 2 (Computer applications); 2000. Available at: http://www.iso.org/iso/ iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=32819. Accessed December 20, 2008.
  16. 16.
    Friedman C, Johnson SB. Natural language and text processing in biomedicine. In: Shortliffe EH et al., eds. Biomedical Informatics: Computer Applications in Health Care and Biomedicine. New York: Springer; 2006: 312–343.Google Scholar
  17. 17.
    Campbell KE, Oliver DE, Spackman KA, Shortliffe EH. Representing thoughts, words, and things in the UMLS. J Am Med Inform Assoc. 1998;5(5):421–431.PubMedGoogle Scholar
  18. 18.
    Spooner SA, Council on Clinical Information Technology, American Academy of Pediatrics. Special requirements of electronic health record systems in pediatrics. Pediatrics. 2007;119(3):631–637.PubMedCrossRefGoogle Scholar
  19. 19.
    American Academy of Pediatrics Committee on Coding and Nomenclature. Application of the resource-based relative value scale system to pediatrics. Pediatrics. 113(5):1437–1440.Google Scholar
  20. 20.
    Goodson JD. Unintended consequences of resource-based relative value scale reimbursement. JAMA. 2007;298(19):2308–2310.PubMedCrossRefGoogle Scholar
  21. 21.
    Veltri MA, Ascenzi J, Clark JS, et al. Successful Elimination of the Rule of Six in an Academic Children's Hospital Through a Medication-Use-System Redesign and Standardization of Continuous Infusions. ASHP 42nd Midyear Clinical Meeting; 2006. Available at: http://www. ashpadvantage.com/bestpractices/2006_papers/veltri.htm. Accessed December 20, 2008.
  22. 22.
    Pestian JP, Itert L, Duch W. Development of a pediatric text-corpus for part-of-speech tagging. In: Wierzchon ST, Trojanowski K, eds. Intelligent information processing and web mining: Proceedings of the International IIS: IIPWM′04; 2004 May 17–20. Zakopane, Poland/Berlin: Springer; 2004: 219–226.Google Scholar
  23. 23.
    Rosenbloom ST, Miller RA, Johnson KB, Elkin PL, Brown SH. A model for evaluating interface terminologies. J Am Med Inform Assoc. 2008;15(1):65–76.PubMedCrossRefGoogle Scholar
  24. 24.
    Brown SH, Elkin PL, Bauer BA, et al. SNOMED CT: utility for a general medical evaluation template. AMIA Annu Symp Proc. 2006:101–105.Google Scholar
  25. 25.
    Woods DM, Johnson J, Holl JL, et al. Anatomy of a patient safety event: a pediatric patient safety taxonomy. Qual Saf Health Care. 2005;14(6):422–427.PubMedCrossRefGoogle Scholar
  26. 26.
    Suresh G, Horbar JD, Plsek P, et al. Voluntary anonymous reporting of medical errors for neonatal intensive care. Pediatrics. 2004;113(6):1609–1618.PubMedCrossRefGoogle Scholar
  27. 27.
    Creswell JW. Research Design: Qualitative and Quantitative Approaches. Thousand Oaks, CA: Sage; 1994.Google Scholar
  28. 28.
    Health Level 7. HL7 Website; 2008. Available at: http://www.hl7.org. Accessed December 21, 2008.
  29. 29.
    Digital Imaging and Communications in Medicine (DICOM). DICOM Website; 2008. Available at: http://medical.nema.org/. Accessed December 14, 2007.
  30. 30.
    US Department of Health and Human Services Centers for Medicare & Medicaid Services (CMS). Medicare program; identification of backward compatible version of adopted standard for e-prescribing and the Medicare prescription drug program (version 8.1). Interim final rule with comment period. Fed Regist. 2006;71(121):36020–36024.Google Scholar
  31. 31.
    Zhou L, Tao Y, Cimino JJ, et al. Terminology model discovery using natural language processing and visualization techniques. J Biomed Inform. 2006;39(6):626–636.PubMedCrossRefGoogle Scholar
  32. 32.
    Friedman C, Liu H, Shagina L. A vocabulary development and visualization tool based on natural language processing and the mining of textual patient reports. J Biomed Inform. 2003;36(3):189–201.PubMedCrossRefGoogle Scholar
  33. 33.
    Aronson AR. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. Proc AMIA Symp. 2001:17–21.Google Scholar
  34. 34.
    Kim GR, Aronson AR, Mork JG, Cohen BA, Lehmann CU. Application of a Medical Text Indexer to an online dermatology atlas. Medinfo. 2004;11(Pt 1):287–291.Google Scholar
  35. 35.
    Cerner Corporation. Discern nCode (formerly GoCode); 2008. Available at: http://www. cerner.com/public/Cerner_3.asp?id=31472. Accessed December 20, 2008.

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • George R. Kim
    • Samuel Trent Rosenbloom
      • 1
    1. 1.Assistant Professor, School of Nursing, Vanderbilt University School of MedicineNashville

    Personalised recommendations