1. Tracking Health Disparities Through Natural-Language Processing
- Author
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Mark L. Wieland, Stephen Wu, Barbara P. Yawn, and Vinod C. Kaggal
- Subjects
Research and Practice ,Minnesota ,Somalia ,Refugee ,media_common.quotation_subject ,Immigration ,Ethnic group ,Somali ,Health care ,Electronic Health Records ,Humans ,Medicine ,Natural Language Processing ,media_common ,Refugees ,business.industry ,Medical record ,Public Health, Environmental and Occupational Health ,Health Status Disparities ,Public relations ,language.human_language ,Health equity ,language ,Tracking (education) ,business ,Algorithms - 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 natural-language–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.
- Published
- 2013
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