Cargando…

A method for encoding clinical datasets with SNOMED CT

BACKGROUND: Over the past decade there has been a growing body of literature on how the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) can be implemented and used in different clinical settings. Yet, for those charged with incorporating SNOMED CT into their organisation's clin...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Dennis H, Lau, Francis Y, Quan, Hue
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949694/
https://www.ncbi.nlm.nih.gov/pubmed/20849611
http://dx.doi.org/10.1186/1472-6947-10-53
_version_ 1782187554383069184
author Lee, Dennis H
Lau, Francis Y
Quan, Hue
author_facet Lee, Dennis H
Lau, Francis Y
Quan, Hue
author_sort Lee, Dennis H
collection PubMed
description BACKGROUND: Over the past decade there has been a growing body of literature on how the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) can be implemented and used in different clinical settings. Yet, for those charged with incorporating SNOMED CT into their organisation's clinical applications and vocabulary systems, there are few detailed encoding instructions and examples available to show how this can be done and the issues involved. This paper describes a heuristic method that can be used to encode clinical terms in SNOMED CT and an illustration of how it was applied to encode an existing palliative care dataset. METHODS: The encoding process involves: identifying input data items; cleaning the data items; encoding the cleaned data items; and exporting the encoded terms as output term sets. Four outputs are produced: the SNOMED CT reference set; interface terminology set; SNOMED CT extension set and unencodeable term set. RESULTS: The original palliative care database contained 211 data elements, 145 coded values and 37,248 free text values. We were able to encode ~84% of the terms, another ~8% require further encoding and verification while terms that had a frequency of fewer than five were not encoded (~7%). CONCLUSIONS: From the pilot, it would seem our SNOMED CT encoding method has the potential to become a general purpose terminology encoding approach that can be used in different clinical systems.
format Text
id pubmed-2949694
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-29496942010-10-06 A method for encoding clinical datasets with SNOMED CT Lee, Dennis H Lau, Francis Y Quan, Hue BMC Med Inform Decis Mak Research Article BACKGROUND: Over the past decade there has been a growing body of literature on how the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) can be implemented and used in different clinical settings. Yet, for those charged with incorporating SNOMED CT into their organisation's clinical applications and vocabulary systems, there are few detailed encoding instructions and examples available to show how this can be done and the issues involved. This paper describes a heuristic method that can be used to encode clinical terms in SNOMED CT and an illustration of how it was applied to encode an existing palliative care dataset. METHODS: The encoding process involves: identifying input data items; cleaning the data items; encoding the cleaned data items; and exporting the encoded terms as output term sets. Four outputs are produced: the SNOMED CT reference set; interface terminology set; SNOMED CT extension set and unencodeable term set. RESULTS: The original palliative care database contained 211 data elements, 145 coded values and 37,248 free text values. We were able to encode ~84% of the terms, another ~8% require further encoding and verification while terms that had a frequency of fewer than five were not encoded (~7%). CONCLUSIONS: From the pilot, it would seem our SNOMED CT encoding method has the potential to become a general purpose terminology encoding approach that can be used in different clinical systems. BioMed Central 2010-09-17 /pmc/articles/PMC2949694/ /pubmed/20849611 http://dx.doi.org/10.1186/1472-6947-10-53 Text en Copyright ©2010 Lee et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lee, Dennis H
Lau, Francis Y
Quan, Hue
A method for encoding clinical datasets with SNOMED CT
title A method for encoding clinical datasets with SNOMED CT
title_full A method for encoding clinical datasets with SNOMED CT
title_fullStr A method for encoding clinical datasets with SNOMED CT
title_full_unstemmed A method for encoding clinical datasets with SNOMED CT
title_short A method for encoding clinical datasets with SNOMED CT
title_sort method for encoding clinical datasets with snomed ct
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949694/
https://www.ncbi.nlm.nih.gov/pubmed/20849611
http://dx.doi.org/10.1186/1472-6947-10-53
work_keys_str_mv AT leedennish amethodforencodingclinicaldatasetswithsnomedct
AT laufrancisy amethodforencodingclinicaldatasetswithsnomedct
AT quanhue amethodforencodingclinicaldatasetswithsnomedct
AT leedennish methodforencodingclinicaldatasetswithsnomedct
AT laufrancisy methodforencodingclinicaldatasetswithsnomedct
AT quanhue methodforencodingclinicaldatasetswithsnomedct