Appl Clin Inform 2020; 11(04): 650-658
DOI: 10.1055/s-0040-1716528
Research Article

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

Sylvia Cho
1  Department of Biomedical Informatics, Columbia University, New York, New York, United States
,
Margaret Sin
1  Department of Biomedical Informatics, Columbia University, New York, New York, United States
,
Demetra Tsapepas
2  Department of Surgery, Columbia University, New York, New York, United States
3  Department of Transplantation, New York Presbyterian Hospital, New York, New York, United States
,
Leigh-Anne Dale
4  Department of Medicine, Columbia University Medical Center, New York, New York, United States
,
Syed A. Husain
5  Division of Nephrology, Department of Medicine, Columbia University Medical Center, New York, New York, United States
,
Sumit Mohan
5  Division of Nephrology, Department of Medicine, Columbia University Medical Center, New York, New York, United States
6  Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, United States
,
Karthik Natarajan
1  Department of Biomedical Informatics, Columbia University, New York, New York, United States
› Author Affiliations
Funding This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01-DK114893 and U01-DK116066) and National Institute on Minority Health and Health Disparities (R01-MD14161). This work was also supported by the National Center for Advancing Translational Sciences (1U01TR002062–01).

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.

Protection of Human and Animal Subjects

Neither human nor animal subjects were included in the project.




Publication History

Received: 14 May 2020

Accepted: 28 July 2020

Publication Date:
07 October 2020 (online)

Georg Thieme Verlag KG
Stuttgart · New York