Cargando…

Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these method...

Descripción completa

Detalles Bibliográficos
Autores principales: Nelson, Scott D, Parker, Jaqui, Lario, Robert, Winnenburg, Rainer, Erlbaum, Mark S., Lincoln, Michael J., Bodenreider, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5881380/
https://www.ncbi.nlm.nih.gov/pubmed/29295234
_version_ 1783311309435043840
author Nelson, Scott D
Parker, Jaqui
Lario, Robert
Winnenburg, Rainer
Erlbaum, Mark S.
Lincoln, Michael J.
Bodenreider, Olivier
author_facet Nelson, Scott D
Parker, Jaqui
Lario, Robert
Winnenburg, Rainer
Erlbaum, Mark S.
Lincoln, Michael J.
Bodenreider, Olivier
author_sort Nelson, Scott D
collection PubMed
description Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings.
format Online
Article
Text
id pubmed-5881380
institution National Center for Biotechnology Information
language English
publishDate 2017
record_format MEDLINE/PubMed
spelling pubmed-58813802018-04-03 Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT Nelson, Scott D Parker, Jaqui Lario, Robert Winnenburg, Rainer Erlbaum, Mark S. Lincoln, Michael J. Bodenreider, Olivier Stud Health Technol Inform Article Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings. 2017 /pmc/articles/PMC5881380/ /pubmed/29295234 Text en http://creativecommons.org/licenses/by-nc/4.0/ This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
spellingShingle Article
Nelson, Scott D
Parker, Jaqui
Lario, Robert
Winnenburg, Rainer
Erlbaum, Mark S.
Lincoln, Michael J.
Bodenreider, Olivier
Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
title Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
title_full Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
title_fullStr Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
title_full_unstemmed Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
title_short Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
title_sort interoperability of medication classification systems: lessons learned mapping established pharmacologic classes (epcs) to snomed ct
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5881380/
https://www.ncbi.nlm.nih.gov/pubmed/29295234
work_keys_str_mv AT nelsonscottd interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct
AT parkerjaqui interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct
AT lariorobert interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct
AT winnenburgrainer interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct
AT erlbaummarks interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct
AT lincolnmichaelj interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct
AT bodenreiderolivier interoperabilityofmedicationclassificationsystemslessonslearnedmappingestablishedpharmacologicclassesepcstosnomedct