A multi-part matching strategy for mapping LOINC with laboratory terminologies

Li Hui Lee, Anika Groß, Michael Hartung, Der Ming Liou, Erhard Rahm

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Objective: To address the problem of mapping local laboratory terminologies to Logical Observation Identifiers Names and Codes (LOINC). To study different ontology matching algorithms and investigate how the probability of term combinations in LOINC helps to increase match quality and reduce manual effort. Materials and methods: We proposed two matching strategies: full name and multi-part. The multi-part approach also considers the occurrence probability of combined concept parts. It can further recommend possible combinations of concept parts to allow more local terms to be mapped. Three real-world laboratory databases from Taiwanese hospitals were used to validate the proposed strategies with respect to different quality measures and execution run time. A comparison with the commonly used tool, Regenstrief LOINC Mapping Assistant (RELMA) Lab Auto Mapper (LAM), was also carried out. Results: The new multi-part strategy yields the best match quality, with F-measure values between 89% and 96%. It can automatically match 70-85% of the laboratory terminologies to LOINC. The recommendation step can further propose mapping to (proposed) LOINC concepts for 9-20% of the local terminology concepts. On average, 91% of the local terminology concepts can be correctly mapped to existing or newly proposed LOINC concepts. Conclusions: The mapping quality of the multi-part strategy is significantly better than that of LAM. It enables domain experts to perform LOINC matching with little manual work. The probability of term combinations proved to be a valuable strategy for increasing the quality of match results, providing recommendations for proposed LOINC conepts, and decreasing the run time for match processing.

Original languageEnglish
Pages (from-to)792-800
Number of pages9
JournalJournal of the American Medical Informatics Association
Volume21
Issue number5
DOIs
Publication statusPublished - Jan 1 2014
Externally publishedYes

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Logical Observation Identifiers Names and Codes
Terminology
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ASJC Scopus subject areas

  • Health Informatics

Cite this

A multi-part matching strategy for mapping LOINC with laboratory terminologies. / Lee, Li Hui; Groß, Anika; Hartung, Michael; Liou, Der Ming; Rahm, Erhard.

In: Journal of the American Medical Informatics Association, Vol. 21, No. 5, 01.01.2014, p. 792-800.

Research output: Contribution to journalArticle

Lee, Li Hui ; Groß, Anika ; Hartung, Michael ; Liou, Der Ming ; Rahm, Erhard. / A multi-part matching strategy for mapping LOINC with laboratory terminologies. In: Journal of the American Medical Informatics Association. 2014 ; Vol. 21, No. 5. pp. 792-800.
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