Tracking health disparities through natural-language processing

Mark L. Wieland, Stephen T. Wu, Vinod C. Kaggal, Barbara P. Yawn

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Health disparities and solutions are heterogeneous within and among racial and ethnic groups, yet existing administrative databases lack the granularity to reflect important sociocultural distinctions. We measured the efficacy of a naturallanguage- processing algorithm to identify a specific immigrant group. The algorithm demonstrated accuracy and precision in identifying Somali patients from the electronic medical records at a single institution. This technology holds promise to identify and track immigrants and refugees in the United States in local health care settings.

Original languageEnglish (US)
Pages (from-to)448-449
Number of pages2
JournalAmerican journal of public health
Volume103
Issue number3
DOIs
StatePublished - Mar 2013

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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