Evidence map›Paper›PMID 24618037›Full record

ArticleBMC medical informatics and decision making2014

Evaluating alignment quality between iconic language and reference terminologies using similarity metrics.

Nicolas Griffon, Gaetan Kerdelhué, Lina F Soualmia, Tayeb Merabti, Julien Grosjean, Jean-Baptiste Lamy, Alain Venot, Catherine Duclos, Stefan J Darmoni

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Using drug knowledgebase information to distinguish between look-alike-sound-alike drugs.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Nicolas GriffonCISMeF, Rouen University Hospital, Normandy & TIBS, LITIS EA 4108, Institute for Research and Innovation in Biomedicine, Rouen, France. nicolas.griffon@chu-rouen.fr.
Gaetan Kerdelhué
Lina F Soualmia
Tayeb Merabti
Julien Grosjean
Jean-Baptiste Lamy
Alain Venot
Catherine Duclos
Stefan J Darmoni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVisualization of Concepts in Medicine (VCM) is a compositional iconic language that aims to ease information retrieval in Electronic Health Records (EHR), clinical guidelines or other medical documents. Using VCM language in medical applications requires alignment with medical reference terminologies. Alignment from Medical Subject Headings (MeSH) thesaurus and International Classification of Diseases - tenth revision (ICD10) to VCM are presented here. This study aim was to evaluate alignment quality between VCM and other terminologies using different measures of inter-alignment agreement before integration in EHR.

methodsFor medical literature retrieval purposes and EHR browsing, the MeSH thesaurus and the ICD10, both organized hierarchically, were aligned to VCM language. Some MeSH to VCM alignments were performed automatically but others were performed manually and validated. ICD10 to VCM alignment was entirely manually performed. Inter-alignment agreement was assessed on ICD10 codes and MeSH descriptors, sharing the same Concept Unique Identifiers in the Unified Medical Language System (UMLS). Three metrics were used to compare two VCM icons: binary comparison, crude Dice Similarity Coefficient (DSCcrude), and semantic Dice Similarity Coefficient (DSCsemantic), based on Lin similarity. An analysis of discrepancies was performed.

resultsMeSH to VCM alignment resulted in 10,783 relations: 1,830 of which were manually performed and 8,953 were automatically inherited. ICD10 to VCM alignment led to 19,852 relations. UMLS gathered 1,887 alignments between ICD10 and MeSH. Only 1,606 of them were used for this study. Inter-alignment agreement using only validated MeSH to VCM alignment was 74.2% [70.5-78.0]CI95%, DSCcrude was 0.93 [0.91-0.94]CI95%, and DSCsemantic was 0.96 [0.95-0.96]CI95%. Discrepancy analysis revealed that even if two thirds of errors came from the reviewers, UMLS was nevertheless responsible for one third.

conclusionsThis study has shown strong overall inter-alignment agreement between MeSH to VCM and ICD10 to VCM manual alignments. VCM icons have now been integrated into a guideline search engine (http://www.cismef.org) and a health terminologies portal (http://www.hetop.eu).

Indexed as

Terminology as TopicVocabulary, ControlledElectronic Health RecordsHumansInformation Storage and RetrievalInternational Classification of DiseasesMedical Subject HeadingsUnified Medical Language System

Identifiers

PMID24618037
PMCPMC4007774

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.