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J Biomed Inform. 2019 Aug;96:103239. doi: 10.1016/j.jbi.2019.103239. Epub 2019 Jun 22.

HemOnc: A new standard vocabulary for chemotherapy regimen representation in the OMOP common data model.

Author information

1
Vanderbilt University Medical Center, Nashville, TN, United States; HemOnc.org, LLC, Lexington, MA, United States. Electronic address: jeremy.warner@vumc.org.
2
Odysseus Data Services, Inc., Cambridge, MA, United States.
3
IQVIA, Cambridge, MA, United States.
4
Northwestern University, Chicago, IL, United States.
5
University of Pittsburgh, Pittsburgh, PA, United States.
6
University of Illinois at Chicago College of Pharmacy, Chicago, IL, United States.
7
Memorial Sloan Kettering Cancer Center, New York, NY, United States.
8
Tufts University, Medford, MA, United States.
9
HemOnc.org, LLC, Lexington, MA, United States; Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Abstract

Systematic application of observational data to the understanding of 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, we 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, we 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 >73,000 concepts and >177,000 relationships in the full vocabulary. Content related to the definition and composition of chemotherapy regimens has been released within the ATHENA tool (athena.ohdsi.org) for widespread utilization by the OHDSI membership. Here, we describe the rationale, data model, and initial contents of the HemOnc vocabulary along with several use cases for which it may be valuable.

KEYWORDS:

Knowledge engineering; Neoplasms; Ontologies

PMID:
31238109
PMCID:
PMC6697579
[Available on 2020-08-01]
DOI:
10.1016/j.jbi.2019.103239

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