Learning from the crowd in terminology mapping: The LOINC experience

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

National policies in the United States require the use of standard terminology for data exchange between clinical information systems. However, most electronic health record systems continue to use local and idiosyncratic ways of representing clinical observations. To improve mappings between local terms and standard vocabularies, we sought to make existing mappings (wisdom) from healt care organizations (the Crowd) available to individuals engaged in mapping processes. We developed new functionality to display counts of local terms and organizations that had previously mapped to a given Logical Observation Identifiers Names and Codes (LOINC) code. Further, we enabled users to view the details of those mappings, including local term names and the organizations that create the mappings. Users also would have the capacity to contribute their local mappings to a shared mapping repository. In this article, we describe the new functionality and its availability to implementers who desire resources to make mapping more efficient and effective.

Original languageEnglish (US)
Pages (from-to)168-174
Number of pages7
JournalLab Medicine
Volume46
Issue number2
DOIs
StatePublished - May 1 2015

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Keywords

  • Clinical laboratory information systems
  • Controlled vocabulary
  • Crowdsourcing
  • Electronic health records
  • Health information exchange
  • Logical observation identifiers names and codes

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Biochemistry, medical

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