BGLM: big data-guided LOINC mapping with multi-language support

ABSTRACT: Abstract

Motivation

Mapping internal, locally used lab test codes to standardized logical observation identifiers names and codes (LOINC) terminology has become an essential step in harmonizing electronic health record (EHR) data across different institutions. However, most existing LOINC code mappers are based on text-mining technology and do not provide robust multi-language support.

Materials and methods

We introduce a simple, yet effective tool called big data-guided LOINC code mapper (BGLM), which leverages the large amount of patient data stored in EHR systems to perform LOINC coding mapping. Distinguishing from existing methods, BGLM conducts mapping based on distributional similarity.

Results

We validated the performance of BGLM with real-world datasets a

SUBMITTER:  

PROVIDER: S-EPMC9696745 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature