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Mis-mappings between a producer's quantitative test codes and LOINC codes and an algorithm for correcting them.

Clement J McDonald1, Seo H Baik1, Zhaonian Zheng1

  • 1Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.

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|November 7, 2022
PubMed
Summary
This summary is machine-generated.

The Logical Observation Identifiers Names and Codes (LOINC) mapping to local lab codes had a 4.6% error rate in PCORnet data. Automatic error detection significantly reduced this rate to 0.1%.

Keywords:
LOINCPCORnetlocal test codemapping errors

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Area of Science:

  • Health Informatics
  • Clinical Data Management
  • Laboratory Medicine

Background:

  • Accurate mapping of laboratory tests to standardized codes like LOINC is essential for data integration in healthcare.
  • Existing data integration efforts face challenges due to mapping inaccuracies across different systems and over time.

Purpose of the Study:

  • To assess the accuracy of Logical Observation Identifiers Names and Codes (LOINC) mapping to local laboratory test codes.
  • To determine the rate of LOINC mapping errors within the PCORnet data.

Main Methods:

  • Utilized software tools and manual reviews to evaluate LOINC mapping accuracy.
  • Analyzed 179 million mapped test results from two PCORnet DataMarts.
  • Reported unweighted and weighted mapping error rates, overall and by LOINC term components.

Main Results:

  • A 4.6% LOINC mapping error rate was identified across 179,537,986 mapped results for 3029 quantitative tests.
  • Error rates were below 5% for common tests (≥100,000 results).
  • Significant variation in error rates observed across LOINC classes, with chemistry at 0.4% and hematology at 7.5%.

Conclusions:

  • The overall LOINC mapping error rate in PCORnet data is 4.6%, which is substantial but lower than previously published rates.
  • Automatic detection and correction algorithms can significantly reduce mapping errors, decreasing the rate to 0.1% for quantitative tests.