Unit conversions between LOINC codes

Ronald G. Hauser, Douglas B. Quine, Alex Ryder, Sheldon Campbell

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Logical Observation Identifiers Names and Codes (LOINC) is the most widely used controlled vocabulary to identify laboratory tests. A given laboratory test can often be reported in more than 1 unit of measure (eg, grams or moles), and LOINC defines unique codes for each unit. Consequently, an identical laboratory test performed by 2 different clinical laboratories may have different LOINC codes. The absence of unit conversions between compatible LOINC codes impedes data aggregation and analysis of laboratory results. To develop such conversions, a computational process was developed to review the LOINC standard for potential conversions, and multiple expert reviewers oversaw and finalized the conversion list. In all, 285 bidirectional conversions were identified, including conversions for routine clinical tests such as sodium, magnesium, and human immunodeficiency virus (HIV). Unit conversions were applied to the aggregation of laboratory test results to demonstrate their usefulness. Diverse informatics projectsmay benefit from the ability to interconvert compatible results.

Original languageEnglish (US)
Pages (from-to)192-196
Number of pages5
JournalJournal of the American Medical Informatics Association
Volume25
Issue number2
DOIs
StatePublished - Feb 1 2018

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Logical Observation Identifiers Names and Codes
Controlled Vocabulary
Informatics
Magnesium
Sodium
HIV

All Science Journal Classification (ASJC) codes

  • Health Informatics

Cite this

Unit conversions between LOINC codes. / Hauser, Ronald G.; Quine, Douglas B.; Ryder, Alex; Campbell, Sheldon.

In: Journal of the American Medical Informatics Association, Vol. 25, No. 2, 01.02.2018, p. 192-196.

Research output: Contribution to journalArticle

Hauser, Ronald G. ; Quine, Douglas B. ; Ryder, Alex ; Campbell, Sheldon. / Unit conversions between LOINC codes. In: Journal of the American Medical Informatics Association. 2018 ; Vol. 25, No. 2. pp. 192-196.
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