Furthering the development of standardized nursing terminology through an ENP®‐ICNP® cross‐mapping

Wieteck, Pia

doi:10.1111/j.1466-7657.2008.00639.x

Cited by 15 publications

(17 citation statements)

References 14 publications

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“…This led to an estimated overall inter-alignment agreement ranging from 53% to 70% for fully manual alignment. The results presented here are better than Wieteck’s [29] for manual alignment, especially for similarity metrics.…”

Section: Discussionmentioning

confidence: 69%

“…Conversely, few studies to date have compared two manually created alignments. Wieteck [29] compared inter-alignment agreement between two nursing terminologies: the European Nursing care Pathway, which is mono-axial, and the International Classification for Nursing Practice (ICNP), which is multi-axial. Agreement was measured for each of the eight ICNP axes and ranged from 73% to 100%.…”

Section: Discussionmentioning

confidence: 99%

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

Griffon

Kerdelhué

Soualmia

et al. 2014

BMC Med Inform Decis Mak

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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).

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Section: Discussionmentioning

confidence: 69%

Section: Discussionmentioning

confidence: 99%

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

Griffon

Kerdelhué

Soualmia

et al. 2014

BMC Med Inform Decis Mak

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“…A quality assessment study of this mapping is currently under review for publication. Briefly, a kind of parallel mapping 19 was performed and showed high inter-mapper semantic agreement (>90%). Initially, the 2011 version of MeSH was mapped to VCM.…”

Section: Visualization Of Concepts In Medicinementioning

confidence: 99%

Design and usability study of an iconic user interface to ease information retrieval of medical guidelines

Griffon

Kerdelhué

Hamek

et al. 2014

Journal of the American Medical Informatics Association

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“…The terms mapping, cross-mapping, linking, and cross-walk are often used synonymously in the literature [21, 22]. Mapping techniques aim to match or relate the meaning of terms in one terminological system with the concepts of the same meaning in another vocabulary [22].…”

Section: Introductionmentioning

confidence: 99%

Mapping the Diagnosis Axis of an Interface Terminology to the NANDA International Taxonomy

2012

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Background. Nursing terminologies are designed to support nursing practice but, as with any other clinical tool, they should be evaluated. Cross-mapping is a formal method for examining the validity of the existing controlled vocabularies. Objectives. The study aims to assess the inclusiveness and expressiveness of the nursing diagnosis axis of a newly implemented interface terminology by cross-mapping with the NANDA-I taxonomy. Design/Methods. The study applied a descriptive design, using a cross-sectional, bidirectional mapping strategy. The sample included 728 concepts from both vocabularies. Concept cross-mapping was carried out to identify one-to-one, negative, and hierarchical connections. The analysis was conducted using descriptive statistics. Results. Agreement of the raters' mapping achieved 97%. More than 60% of the nursing diagnosis concepts in the NANDA-I taxonomy were mapped to concepts in the diagnosis axis of the new interface terminology; 71.1% were reversely mapped. Conclusions. Main results for outcome measures suggest that the diagnosis axis of this interface terminology meets the validity criterion of cross-mapping when mapped from and to the NANDA-I taxonomy.

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Furthering the development of standardized nursing terminology through an ENP®‐ICNP® cross‐mapping

Cited by 15 publications

References 14 publications

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

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

Design and usability study of an iconic user interface to ease information retrieval of medical guidelines

Mapping the Diagnosis Axis of an Interface Terminology to the NANDA International Taxonomy

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