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Learning from the crowd while mapping to LOINC.

Daniel J Vreeman1, John Hook2, Brian E Dixon3

  • 1Associate Research Professor, Indiana University School of Medicine, Indianapolis, IN Research Scientist, Regenstrief Institute, Inc., Indianapolis, IN, USA.

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Summary

Users found community mapping features in the Regenstrief LOINC Mapping Assistant (RELMA) useful. Sharing mapping data improved the accuracy and efficiency of mapping local terms to Logical Observation Identifiers Names and Codes (LOINC) terms.

Keywords:
Clinical laboratory information systemsLOINCcontrolledmedical record systemsvocabulary

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Area of Science:

  • Health Informatics
  • Medical Terminology Standardization

Background:

  • The Regenstrief LOINC Mapping Assistant (RELMA) is a tool for mapping local terms to standardized Logical Observation Identifiers Names and Codes (LOINC).
  • Community Mapping features were introduced to leverage collective user knowledge for improved mapping accuracy.

Purpose of the Study:

  • To assess user perspectives on RELMA's Community Mapping features before and after deployment.
  • To characterize the utilization of these new features.
  • To evaluate the quality of community-submitted mappings.

Main Methods:

  • Pre- and post-launch user surveys were conducted to gauge perceptions and usage.
  • System logs monitored feature access and data utilization.
  • Automated methods analyzed the quality of community mappings.

Main Results:

  • Nearly 80% of users desired information on others' mapping choices prior to launch.
  • Community Mapping features were accessed frequently, with high reported usefulness by users.
  • Over 95% of submitted community mappings passed automated validation checks.

Conclusions:

  • User feedback indicates that shared mapping information is valuable.
  • The crowd-sourced repository of mappings enhances the process of mapping local terms to LOINC.
  • Community Mapping features improve the utility and quality of LOINC term mapping.