Developing a Standardization Algorithm for Categorical Laboratory Tests for Clinical Big Data Research: Retrospective Study.

ABSTRACT:

Background

Data standardization is essential in electronic health records (EHRs) for both clinical practice and retrospective research. However, it is still not easy to standardize EHR data because of nonidentical duplicates, typographical errors, or inconsistencies. To overcome this drawback, standardization efforts have been undertaken for collecting data in a standardized format as well as for curating the stored data in EHRs. To perform clinical big data research, the stored data in EHR should be standardized, starting from laboratory results, given their importance. However, most of the previous efforts have been based on labor-intensive manual methods.

Objective

We aimed to develop an automatic standardization method for eliminating the noises of categorical laboratory

SUBMITTER: Kim M 

PROVIDER: S-EPMC6740165 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature