Evidence map›Paper›PMID 21951759›Full record

ArticleJournal of biomedical informatics2012

Semantic mappings and locality of nursing diagnostic concepts in UMLS.

Tae Youn Kim, Amy Coenen, Nicholas Hardiker

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
  2. Observational
  3. Article
  4. Article
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4 · The record

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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

3 authors.

Tae Youn KimCollege of Nursing, University of Wisconsin-Milwaukee, 1921 E. Hartford Avenue, P.O. Box 413, Milwaukee, WI 53201-0413, USA. kimty@uwm.edu
Amy Coenen
Nicholas Hardiker

Funding

Predicting Care Coordination Needs of Frail Older Adults from Longitudinal DataR03NR012802 · NINR · UNIVERSITY OF WISCONSIN MILWAUKEE · PI KIM, TAE YOUN · 2011 to 2012
$162k
NINR NIH HHS 1R03NR012802NINR NIH HHS R03 NR012802
6 · The paper itself

Abstract

One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines.

Indexed as

SemanticsHumansNational Library of Medicine (U.S.)Systematized Nomenclature of MedicineUnified Medical Language SystemUnited StatesVocabulary, Controlled

Identifiers

PMID21951759
PMCPMC3272126

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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.