Leveraging unstructured data to identify hereditary angioedema patients in electronic medical records

Leveraging unstructured data to identify hereditary angioedema patients in electronic medical records

Abstract Background The epidemiologic impact of hereditary angioedema (HAE) is difficult to quantify, due to misclassification in retrospective studies resulting from non-specific diagnostic coding. The aim of this study was to identify cohorts of patients with HAE-1/2 by evaluating structured and u...

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Bibliographic Details
Main Authors: Emily S. Brouwer, Emily W. Bratton, Aimee M. Near, Lynn Sanders, Christina D. Mack
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Allergy, Asthma & Clinical Immunology
Subjects:
Electronic medical records
Epidemiology
Feasibility study
Hereditary angioedema
Real-world data
Unstructured data
Online Access:https://doi.org/10.1186/s13223-021-00541-6

Internet

https://doi.org/10.1186/s13223-021-00541-6

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