Optimize Querying of LOINC® with an Ontology: Give Me the Chlamydia Tests the Epidemiologists Want Me to Use!

Epidemiologists create and publish criteria for laboratory tests that must be reported to public health agencies. The sets of LOINC® codes are critical for electronic laboratory reporting but vary by source, are difficult to curate, and may be missing desired or include undesired tests. Using Chlamydia as an example, we developed an ontology that classifies the terminology used to describe LOINC® coded tests. For each test, we created a new ontology term with a logical definition, and used the HermiT reasoner to automatically classify the tests into an ontology. We used the ontology to query for logic using terms familiar to epidemiologists, and demonstrate views that allow the user to visualize selected codes in the context of all codes. We provided prototype classification and querying functionality that can be extended to address all organisms and allow users to visualize alternative strategies.