Wang L, Wen A, Fu S, Ruan X, Huang M, Li R, Lu Q, Williams AE, Liu H. Adoption of the OMOP CDM for Cancer Research using Real-world Data: Current Status and Opportunities.
MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.23.24311950. [PMID:
39228725 PMCID:
PMC11370549 DOI:
10.1101/2024.08.23.24311950]
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Abstract
Background
The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) that is developed and maintained by the Observational Health Data Sciences and Informatics (OHDSI) community supports large scale cancer research by enabling distributed network analysis. As the number of studies using the OMOP CDM for cancer research increases, there is a growing need for an overview of the scope of cancer research that relies on the OMOP CDM ecosystem.
Objectives
In this study, we present a comprehensive review of the adoption of the OMOP CDM for cancer research and offer some insights on opportunities in leveraging the OMOP CDM ecosystem for advancing cancer research.
Materials and Methods
Published literature databases were searched to retrieve OMOP CDM and cancer-related English language articles published between January 2010 and December 2023. A charting form was developed for two main themes, i.e., clinically focused data analysis studies and infrastructure development studies in the cancer domain.
Results
In total, 50 unique articles were included, with 30 for the data analysis theme and 23 for the infrastructure theme, with 3 articles belonging to both themes. The topics covered by the existing body of research was depicted.
Conclusion
Through depicting the status quo of research efforts to improve or leverage the potential of the OMOP CDM ecosystem for advancing cancer research, we identify challenges and opportunities surrounding data analysis and infrastructure including data quality, advanced analytics methodology adoption, in-depth phenotypic data inclusion through NLP, and multisite evaluation.
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