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Area of Science:

  • Medical Informatics
  • Clinical Laboratory Science

Background:

  • Laboratory test results offer valuable secondary data for healthcare analytics.
  • Standardizing laboratory test codes across institutions is crucial for data integration and technician support.
  • Manual test code mapping is time-consuming and prone to errors during data preparation.

Purpose of the Study:

  • To develop a system that semi-automatically maps laboratory test codes.
  • To reduce the manual workload associated with data preparation for laboratory test results.
  • To leverage electronic health record data for efficient test code mapping.

Main Methods:

  • Development of a semi-automatic mapping support system.
  • Utilization of the most recent laboratory test results from electronic health records.
  • Implementation of algorithms to facilitate test code identification and mapping.

Main Results:

  • The developed system assists in the semi-automatic mapping of laboratory test codes.
  • The system utilizes current electronic health record data for mapping.
  • Potential reduction in manual effort for data preparation is demonstrated.

Conclusions:

  • Semi-automatic mapping systems can improve the efficiency of laboratory data management.
  • Integrating electronic health record data streamlines the test code mapping process.
  • This approach supports laboratory technicians by reducing manual data preparation tasks.