CodeMapper: semiautomatic coding of case definitions. A contribution from the ADVANCE project

Background Assessment of drug and vaccine effects by combining information from different healthcare databases in the European Union requires extensive efforts in the harmonization of codes as different vocabularies are being used across countries. In this paper, we present a web application called...

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Vydáno v:Pharmacoepidemiology and drug safety Ročník 26; číslo 8; s. 998 - 1005
Hlavní autoři: Becker, Benedikt F.H., Avillach, Paul, Romio, Silvana, Mulligen, Erik M., Weibel, Daniel, Sturkenboom, Miriam C.J.M., Kors, Jan A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Wiley Subscription Services, Inc 01.08.2017
John Wiley and Sons Inc
Témata:
concept identification
database extraction
Databases, Factual - statistics & numerical data
Europe - epidemiology
Humans
International Classification of Diseases - statistics & numerical data
Mapping
Medical Records Systems, Computerized - statistics & numerical data
multiple medical vocabularies
Original Report
Original Reports
Pharmacology
semantic operations
UMLS
Unified Medical Language System - statistics & numerical data
Vocabularies & taxonomies
UMLS
semantic operations
database extraction
multiple medical vocabularies
concept identification
ISSN:1053-8569, 1099-1557, 1099-1557
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Shrnutí:Background Assessment of drug and vaccine effects by combining information from different healthcare databases in the European Union requires extensive efforts in the harmonization of codes as different vocabularies are being used across countries. In this paper, we present a web application called CodeMapper, which assists in the mapping of case definitions to codes from different vocabularies, while keeping a transparent record of the complete mapping process. Methods CodeMapper builds upon coding vocabularies contained in the Metathesaurus of the Unified Medical Language System. The mapping approach consists of three phases. First, medical concepts are automatically identified in a free‐text case definition. Second, the user revises the set of medical concepts by adding or removing concepts, or expanding them to related concepts that are more general or more specific. Finally, the selected concepts are projected to codes from the targeted coding vocabularies. We evaluated the application by comparing codes that were automatically generated from case definitions by applying CodeMapper's concept identification and successive concept expansion, with reference codes that were manually created in a previous epidemiological study. Results Automated concept identification alone had a sensitivity of 0.246 and positive predictive value (PPV) of 0.420 for reproducing the reference codes. Three successive steps of concept expansion increased sensitivity to 0.953 and PPV to 0.616. Conclusions Automatic concept identification in the case definition alone was insufficient to reproduce the reference codes, but CodeMapper's operations for concept expansion provide an effective, efficient, and transparent way for reproducing the reference codes.
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Prior posting and presentation: Parts of this article have been presented on a poster at ICPE 2016.
ISSN:1053-8569
1099-1557
1099-1557
DOI:10.1002/pds.4245