ArticleThe journal of allergy and clinical immunology. Global2023
Development of a machine learning algorithm based on administrative claims data for identification of ED anaphylaxis patient visits.
Article in The journal of allergy and clinical immunology. Global, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Epidemiologic studies of anaphylaxis commonly rely on Objective: We sought to develop and assess the accuracy of a machine learning algorithm using Methods: We conducted a retrospective review of ED visits from January 2013 to September 2017. Potential ED anaphylaxis visits were identified using 3 methods: anaphylaxis Results: A total of 699 of 2191 (31.9%) potential ED anaphylaxis visits were classified as anaphylaxis. The sensitivity and specificity of method 1 were 49.1% and 87.5%, respectively. Method 1 used in combination with method 2 resulted in a sensitivity of 53.9% and a specificity of 68.7%. Method 1 used in combination with method 3 resulted in a sensitivity of 98.4% and a specificity of 15.1%. The sensitivity and specificity of the machine learning algorithm were 87.3% and 79.1%, respectively. Conclusions:
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