Natural language processing to advance EHR-based clinical research in Allergy, Asthma, and Immunology.
Juhn, Young;Liu, Hongfang;
the journal of allergy and clinical immunology2019
378
juhn2019naturalthe
Abstract
The wide adoption of electronic health record systems (EHRs) in health care generates big real-world data that opens new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing (NLP) techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in EHRs. This capability of NLP potentially enables automated chart review for identifying patients with distinctive clinical characteristics in clinical care and reduces methodological heterogeneity in defining phenotype obscuring biological heterogeneity in research concerning allergy, asthma, and immunology. This brief review discusses the current literature on the secondary use of EHR data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of NLP techniques.