Content Coverage Evaluation of the OMOP Vocabulary on the Transplant Domain Focusing on Concepts Relevant for Kidney Transplant Outcomes Analysis.

ABSTRACT

BACKGROUND: Improving outcomes of transplant recipients within and across transplant centers is important with the increasing number of organ transplantations being performed. The current practice is to analyze the outcomes based on patient level data submitted to the United Network for Organ Sharing (UNOS). Augmenting the UNOS data with other sources such as the electronic health record will enrich the outcomes analysis, for which a common data model (CDM) can be a helpful tool for transforming heterogeneous source data into a uniform format. OBJECTIVES: In this study, we evaluated the feasibility of representing concepts from the UNOS transplant registry forms with the Observational Medical Outcomes Partnership (OMOP) CDM vocabulary to understand the content coverage of OMOP vocabulary on transplant-specific concepts. METHODS: Two annotators manually mapped a total of 3,571 unique concepts extracted from the UNOS registry forms to concepts in the OMOP vocabulary. Concept mappings were evaluated by (1) examining the agreement among the initial two annotators and (2) investigating the number of UNOS concepts not mapped to a concept in the OMOP vocabulary and then classifying them. A subset of mappings was validated by clinicians. RESULTS: There was a substantial agreement between annotators with a kappa score of 0.71. We found that 55.5% of UNOS concepts could not be represented with OMOP standard concepts. The majority of unmapped UNOS concepts were categorized into transplant, measurement, condition, and procedure concepts. CONCLUSION: We identified categories of unmapped concepts and found that some transplant-specific concepts do not exist in the OMOP vocabulary. We suggest that adding these missing concepts to OMOP would facilitate further research in the transplant domain.