Tracking Health Disparities Through Natural-Language Processing.

• Autores: Mark L. Wieland, Stephen T. Wu, Vinod C. Kaggal, Barbara P. Yawn
• Localización: American journal of public health, ISSN 0090-0036, Vol. 103, Nº. 3, 2013, págs. 448-449
• Idioma: inglés
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• Resumen

  • 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. [ABSTRACT FROM AUTHOR]