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AllergyMap: An Open Source Corpus of Allergy Mention Normalizations.
Wang, Amy Y; Osborne, John D; Danila, Maria I; Naidech, Andrew M; Liebovitz, David M.
Affiliation
  • Wang AY; University of Alabama at Birmingham Informatics Institute, Birmingham, Alabama.
  • Osborne JD; University of Alabama at Birmingham Informatics Institute, Birmingham, Alabama.
  • Danila MI; University of Alabama at Birmingham Informatics Institute, Birmingham, Alabama.
  • Naidech AM; Northwestern University, Chicago, Illinois.
  • Liebovitz DM; Northwestern University, Chicago, Illinois.
AMIA Annu Symp Proc ; 2020: 1249-1257, 2020.
Article in En | MEDLINE | ID: mdl-33936501
ABSTRACT
Allergy mention normalization is challenging because of the wide range of possible allergens including medications, foods, plants, animals, and consumer products. This paper describes the process of mapping free-text allergy information from an electronic health record (EHR) system in a university hospital to standard terminologies and migration of those data into an enterprise EHR system. The review, mapping, and migration revealed interesting issues and challenges with the free-text allergy information and the mapping in preparation for implementation in the new EHR system. These findings provide insights that can form the basis of guidelines for future mapping and migration efforts involving free-text allergy data. As part of this process, we generate and make freely available AllergyMap, a mapping between free-text entered allergy medication to standard non-proprietary ontologies. To our knowledge, this is the first such mapping available and could serve as a public resource for allergy mention normalization and system evaluation.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Natural Language Processing / Allergens / Electronic Health Records / Data Mining / Hypersensitivity Limits: Humans Language: En Journal: AMIA Annu Symp Proc Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Natural Language Processing / Allergens / Electronic Health Records / Data Mining / Hypersensitivity Limits: Humans Language: En Journal: AMIA Annu Symp Proc Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article