In conjunction with a project to structure and encode Cancer Synoptic data we have systematically employed a convergent concept model agreed by SNOMED International and the Regenstrief Institute for observation results. Extending the harmonization efforts of those organizations, we have brought together laboratory, clinical and pathology concepts from these efforts into a pragmatic ontology of SNOMED CT - LOINC Observable Entities unified by description logic. In this paper we describe the conceptual model that defines the ontology. We explain how this ontology supports query in our i2b2 data warehouse and discuss the utility of the ontology to promote reproducibility and interoperability of LOINC coded data for US healthcare and precision medicine in cancer.
Learning Objective 1: Appreciate the role of Observable entities in the Standards and Interoperability framework of ONCHIT
Learning Objective 2: Understand the utility of an Observables ontology for interoperable re-use of LOINC coded data
James Campbell (Presenter)
University of Nebraska