COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 32569358.
- Also identified by DOI 10.1093/jamia/ocaa145 and PMC identifier 7337837.
- Licence recorded as CC BY-NC.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) codes. COVID-19 TestNorm was developed and evaluated using 568 test names collected from 8 healthcare systems. Our results show that it could achieve an accuracy of 97.4% on an independent test set. COVID-19 TestNorm is available as an open-source package for developers and as an online Web application for end users (https://clamp.uth.edu/covid/loinc.php). We believe that it will be a useful tool to support secondary use of EHRs for research on COVID-19.
Medical subject headings
- Betacoronavirus
- Clinical Laboratory Techniques
- Coronavirus Infections
- Logical Observation Identifiers Names and Codes
- Pneumonia, Viral
- Terminology as Topic