Skip to main content

The Case for a Pediatric Terminology

  • Chapter
  • 876 Accesses

Part of the book series: Health Informatics ((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

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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. 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.

    Article  PubMed  Google Scholar 

  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. Medicomp Systems, Inc. Medcin Website; 2008. Available at: http://www.medicomp.com. Accessed December 27, 2007.

  5. Columbia University Department of Biomedical Informatics. Medical Entities Dictionary Website; 2007. Available at: http://med.dmi.columbia.edu/. Accessed December 27, 2007.

  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. 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. Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med. 1998;37(4–5):394–403.

    PubMed  CAS  Google Scholar 

  9. Federative Committee on Anatomical Terminology. Terminologia Anatomica. Stuttgart, Germany: Thieme; 1998.

    Google Scholar 

  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. 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. Gene Ontology. Gene Ontology Home; 2008. Available at: http://www.geneontology.org/. Accessed December 21, 2008.

  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. 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. 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. 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. 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.

    PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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. Goodson JD. Unintended consequences of resource-based relative value scale reimbursement. JAMA. 2007;298(19):2308–2310.

    Article  PubMed  CAS  Google Scholar 

  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. 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. 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.

    Article  PubMed  Google Scholar 

  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. 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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  27. Creswell JW. Research Design: Qualitative and Quantitative Approaches. Thousand Oaks, CA: Sage; 1994.

    Google Scholar 

  28. Health Level 7. HL7 Website; 2008. Available at: http://www.hl7.org. Accessed December 21, 2008.

  29. Digital Imaging and Communications in Medicine (DICOM). DICOM Website; 2008. Available at: http://medical.nema.org/. Accessed December 14, 2007.

  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. 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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  33. Aronson AR. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. Proc AMIA Symp. 2001:17–21.

    Google Scholar 

  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. Cerner Corporation. Discern nCode (formerly GoCode); 2008. Available at: http://www. cerner.com/public/Cerner_3.asp?id=31472. Accessed December 20, 2008.

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Kim, G.R., Rosenbloom, S.T. (2009). The Case for a Pediatric Terminology. In: Lehmann, C.U., Kim, G.R., Johnson, K.B. (eds) Pediatric Informatics. Health Informatics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-76446-7_33

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-76446-7_33

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-76445-0

  • Online ISBN: 978-0-387-76446-7

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics