SNOMED-Based Knowledge Representation

Abstract:

A standardized vocabulary and a standardized representation for this vocabulary are necessary prerequisites for the development of a computer-based patient record. A standard conceptual scheme or data structure for this vocabulary must be in place to define clinical events and to share data. SNOMED International is a detailed, fine grained, semantically typed and comprehensive computer processable vocabulary encompassing both human and veterinary medicine. Each term is placed in a standardized data structure that shows the term relationship within its own and other related taxonomic hierarchies. SNOMED International is a standardized vocabulary and data structure suitable for use in the computer-based patient record.

Keywords:

SNOMEDlnternational - Standardized Vocabulary - Standardized Data Structure - Computer-based Patient Record

• References

• 1 Institute of Medicine. The Computer-Based Patient Record: an Essential Technology for Health Care. Washington DC: National Academy Press; 1991
• 2 Board of Directors of the American Medical Informatics Association. Standards for medical identifiers, codes and messages needed to create an efficient computerstored medical record. JAMIA 1994; 1: 1-7.
• 3 Rothwell DJ, Côté RA, Cordeau JP, Boisvert MA. Developing a standard data structure for medical language – the SNOMED proposal. In: Proc SCAMC 93. McGraw-Hill; 1994: 695-9.
• 4 Huff SM, Rocha S. Vocabularies and data structures for the computerized patient record. AMIA Spring Congress 1993; 1-6.
• 5 Evans DA, Rothwell DJ, Monarch IA, Lefferts RG, Côté RA. Toward representations for medical concepts. Med Decis Making 1991; 11 (Suppl. 04) 102-8.
• 6 Rothwell DJ, Côté RA. Optimizing the structure of a standard vocabulary – the SNOMED model. In: Miller RD. ed. Proc SCAMC 90. New York: IEEE Computer Society Press; 1990: 181-4.
• 7 Hammond E. Personal communication. AMIA Meeting. St-Louis, Mo: Spring; 1993
• 8 Greenes RA, Deibel SRA. The DeSyGNER knowledge management architecture: a building block approach based on an extensible kernel. Artif Intell Med 1991; 3: 95-111.
• 9 Wingert F. Medical linguistics: automated indexing into SNOMED. Critical Review in Informatics 1988; 1: 333-403.
• 10 Côté RA, Rothwell DJ, Palotay JL, Beckett RS, Brochu L. The Systematized Nomenclature of Human and Veterinary Medicine – SNOMED International (4 volumes). College of American Pathologists; 1993
• 11 Campbell KE, Musen MA. Representation of clinical data using SNOMED III and conceptual graphs. In: Frisse ME. ed. Proc SCAMC ’92. New York: McGraw-HilI; 1992: 354-8.
• 12 Wingert F, Rothwell DJ, Côté RA. Automated indexing into SNOMED and ICD. In: Computerized Natural Medical Language Processing for Knowledge Representation. Amsterdam: Elsevier; 1989: 201-39.
• 13 Côté RA, Rothwell DJ. The classificationnomenclature issues in medicine: a return to natural language. Med Inf (Lond) 1989; 14: 25-41.
• 14 Miller D. Brain processing of optical input: the perception of visual reality. M. D. Computing 1994; 1: 34-42.
• 15 Campbell KE. et al. A logical foundation for representation of clinical data. JAMIA 1994; 1 (03) 218-32.
• 16 Evans DA. et al. Toward a medical-concept representation language. JAMIA 1994; 1 (03) 207-17.
• 17 Rothwell DJ. et al. Indexing medical information – The role of SNOMED. In: Preceeding of 13th SCAMC. New York: IEEE Comput Soc Press; 1989: 534-9.