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Why terminology standards?
Standardized terminologies facilitate: Electronic data collection Retrieval of relevant data or knowledge Allows data to be reused for multiple purposes
such as syndromatic surveillance, clinical decision support and quality and cost monitoring
Criteria for terminologies
Technical Criteria used by NCVHS for evaluating and selecting terminologies Page 145 – Table 4-2
CHI focus areas Page 146 – Table 4-3
Terminology Standards
November 13, 2003 – NCVHS recommends: the adoption of SNOMED CT as the terminology of choice
for representing clinical terms LOINC is endorsed as the standard to use for Laboratory
concepts coding RxNORM National Drug File Clinical Drug Reference Terminology
(NDF RT) Also have recommended the adoption of ICD-10
January 29, 2004 – CHI endorses SNOMED CT for anatomy, nursing, diagnosis and problems, and non-lab interventions and procedures
Unified Medical Language System
UMLS
Presentation Source Material: Oliver Bodenreider: “The Unified MedicalLanguage System (UMLS) integrating biomedical terminologies,” Nucleic AcidsResearch, 2004, Vol. 32, Database issue D267-D270
UMLS
Repository of Biomedical Vocabularies It integrates
2 million names 900,000 concepts 60 families of biomedical vocabularies 12 million relations among concepts
UMLS Metathesaurus
Sample vocabularies integrated here: NCBI taxonomy Gene Ontology The Medical Subject Headings (MeSH) OMIM Digital Anatomist Symbolic Knowledge Base ICD-9 CPT
UMLS Metathesaurus
Repository of biomedical concepts drawn from all the different terminologies integrated
Figure Source Material: Oliver Bodenreider: “The Unified MedicalLanguage System (UMLS) integrating biomedical terminologies,” Nucleic AcidsResearch, 2004, Vol. 32, Database issue D267-D270
National CenterFor BiotechnologyInformation
Online MendelianInheritance in Man
University of WashingtonDigitalAnatomist
Gene Ontology
Terminology Integration Principles Knowledge organized by concept/meaning Synonymous terms associated with concepts Concepts can be linked to other concepts Hierarchical, part-of, inheritance, associative
links and statistical relations between concepts are represented in the Metathesauraus.
Each Metathesauraus concept is categorized currently into one of 135 high-level categories
Structure of Metathesaurus
Allows Collecting terms associated with a particular
concept Exploring relationship between concepts Browsing the concepts associated with a
particular category
Section of the UMLS Semantic Network
Source: http://www.nlm.nih.gov/research/umls/META3_Figure_1.html
UMLS Tools
MetamorphoSys – helps users customize Metathesaurus
lvg : a program to generate lexical variants MetaMap : extracts Metathesaurus concepts
from text
LOINCSource: “LOINC, a Universal Standard for Identifying Laboratory Observations: A 5-Year Update” Clement J. McDonald, Stanley M. Huff, et. al. Clinical Chemistry 49:4, 624-633 (2003) http://www.clinchem.org/cgi/reprint/49/4/624
Logical Observation Identifiers Names and Codes Started by a group of researchers who met in
1994 in Regenstrief Institute 1995 first release of 6000 laboratory test
results 17 releases since then Regenstrief LOINC Mapping Assistant
(RELMA)
Examples
LOINC codes for partial pressure of arterial blood oxygen (Po2) and percentage lymphocytes
EKG measurements Vital signs LOINC only codes for observation types not
the values that are associated with a particular test