The HemOnc Chemotherapy Regimen Vocabulary
On Wednesday, December 18, Dr. Jeremy Warner will present "The HemOnc Chemotherapy Regimen Vocabulary."
In this talk, Dr. Warner will describe the rationale, data model, and initial contents of the HemOnc vocabulary along with several use cases for which it may be valuable. Systematic application of observational data to understand the impacts of cancer treatments requires detailed information models allowing meaningful comparisons between treatment regimens. Unfortunately, details of systemic therapies are scarce in registries and data warehouses, primarily due to the complex nature of the protocols and a lack of standardization. Since 2011, Dr. Warner and his team have been creating a curated and semi-structured website of chemotherapy regimens, HemOnc.org. In coordination with the Observational Health Data Sciences and Informatics (OHDSI) Oncology Subgroup, they have transformed a substantial subset of this content into the OMOP common data model, with bindings to multiple external vocabularies, e.g., RxNorm and the National Cancer Institute Thesaurus. Currently, there are >76,000 concepts and >186,000 relationships in the full vocabulary, a portion of which has been released within the ATHENA tool for widespread utilization by the OHDSI membership.
The Data Science Seminar Series presents talks from innovators in the research and informatics communities both within and outside of NCI.
Jeremy Warner M.D., M.S. is an associate professor of medicine and biomedical informatics at Vanderbilt University, where he also directs the Vanderbilt Cancer Registry and Stem Cell Transplant Data Analysis Team. He is board certified in Internal Medicine, Medical Oncology, Hematology, and Clinical Informatics; his clinical focus is malignant hematology. His primary research goal is to make sense of the structured and unstructured data present in electronic health records (EHRs) and clinical knowledge bases to directly improve clinical care for patients, with a focus on oncology. This includes high-dimensional data analysis and visualization, natural language processing of cancer-oriented narratives, and development/implementation of oncology-specific health IT standards. Dr. Warner holds a doctorate of medicine from Boston University School of Medicine and a master's degree from University of California, San Diego.