Evidence map›Paper›PMID 28657162›Full record

ArticlePharmacoepidemiology and drug safety2017

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

Benedikt F H Becker, Paul Avillach, Silvana Romio, Erik M van Mulligen, Daniel Weibel, Miriam C J M Sturkenboom, Jan A Kors, ADVANCE consortium

Abstract read
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Article in Pharmacoepidemiology and drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Benedikt F H BeckerDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.ORCID http://orcid.org/0000-0002-0819-8344
Paul AvillachDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Silvana RomioDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Erik M van MulligenDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Daniel WeibelDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Miriam C J M SturkenboomDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Jan A KorsDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
ADVANCE consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAssessment 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.

methodsCodeMapper 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.

resultsAutomated 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.

conclusionsAutomatic 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.

Indexed as

Databases, FactualEuropeHumansInternational Classification of DiseasesMedical Records Systems, ComputerizedUnified Medical Language Systemconcept identificationdatabase extractionmultiple medical vocabulariessemantic operationsUMLS

Identifiers

PMID28657162
PMCPMC5575526

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.