Logical Observation Identifiers Names and Codes (LOINC®) Applied to Microbiology: A National Laboratory Mapping Experience in Taiwan

• Published in: Diagnostics (Basel) 2021-08, Vol.11 (9), p.1564
• Main Authors: Yeh, Chih-Yang, Peng, Syu-Jyun, Yang, Hsuan Chia, Islam, Mohaimenul, Poly, Tahmina Nasrin, Hsu, Chien-Yeh, Huff, Stanley M., Chen, Huan-Chieh, Lin, Ming-Chin
• Format: Article
• Language: English
• Subjects: Antigens; automated mapping; Automation; Codes; Disease control; electronic health record; Electronic health records; Hepatitis; Hospitals; Information systems; LOINC laboratory test; Medical laboratories; Names; Outsourcing; Pathogens; RELMA; Terminology; Tuberculosis
• ISSN: 2075-4418; 2075-4418
• DOI: 10.3390/diagnostics11091564

Background and Objective: Logical Observation Identifiers Names and Codes (LOINC) is a universal standard for identifying laboratory tests and clinical observations. It facilitates a smooth information exchange between hospitals, locally and internationally. Although it offers immense benefits for patient care, LOINC coding is complex, resource-intensive, and requires substantial domain expertise. Our objective was to provide training and evaluate the performance of LOINC mapping of 20 pathogens from 53 hospitals participating in the National Notifiable Disease Surveillance System (NNDSS). Methods: Complete mapping codes for 20 pathogens (nine bacteria and 11 viruses) were requested from all participating hospitals to review between January 2014 and December 2016. Participating hospitals mapped those pathogens to LOINC terminology, utilizing the Regenstrief LOINC mapping assistant (RELMA) and reported to the NNDSS, beginning in January 2014. The mapping problems were identified by expert panels that classified frequently asked questionnaires (FAQs) into seven LOINC categories. Finally, proper and meaningful suggestions were provided based on the error pattern in the FAQs. A general meeting was organized if the error pattern proved to be difficult to resolve. If the experts did not conclude the local issue’s error pattern, a request was sent to the LOINC committee for resolution. Results: A total of 53 hospitals participated in our study. Of these, 26 (49.05%) used homegrown and 27 (50.95%) used outsourced LOINC mapping. Hospitals who participated in 2015 had a greater improvement in LOINC mapping than those of 2016 (26.5% vs. 3.9%). Most FAQs were related to notification principles (47%), LOINC system (42%), and LOINC property (26%) in 2014, 2015, and 2016, respectively. Conclusions: The findings of our study show that multiple stage approaches improved LOINC mapping by up to 26.5%.