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AMIA Annu Symp Proc. 2018 Dec 5;2018:480-489. eCollection 2018.

Clinical Concept Value Sets and Interoperability in Health Data Analytics.

Author information

1
University of Maryland, College Park.
2
Observational Health Data Sciences and Informatics.
3
MD Partners, Lafayette, CO.
4
Mayo Clinic, Rochester, MN.
5
Johns Hopkins University, Baltimore, MD.
6
Illinois State University; Normal, IL.
7
National Library of Medicine, Bethesda, MD.
8
Columbia University, New York, NY.
9
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD.
10
University of North Carolina, Chapel Hill, NC.

Abstract

This paper focuses on value sets as an essential component in the health analytics ecosystem. We discuss shared repositories of reusable value sets and offer recommendations for their further development and adoption. In order to motivate these contributions, we explain how value sets fit into specific analytic tasks and the health analytics landscape more broadly; their growing importance and ubiquity with the advent of Common Data Models, Distributed Research Networks, and the availability of higher order, reusable analytic resources like electronic phenotypes and electronic clinical quality measures; the formidable barriers to value set reuse; and our introduction of a concept-agnostic orientation to vocabulary collections. The costs of ad hoc value set management and the benefits of value set reuse are described or implied throughout. Our standards, infrastructure, and design recommendations are not systematic or comprehensive but invite further work to support value set reuse for health analytics. The views represented in the paper do not necessarily represent the views of the institutions or of all the co-authors.

PMID:
30815088
PMCID:
PMC6371254

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