Development of a machine learning algorithm based on administrative claims data for identification of ED anaphylaxis patient visits.

Background: Epidemiologic studies of anaphylaxis commonly rely on () codes to identify anaphylaxis cases, which may lead to suboptimal epidemiologic classification.

Objective: We sought to develop and assess the accuracy of a machine learning algorithm using codes and other administrative data compared with code-only algorithms to identify emergency department (ED) anaphylaxis visits.

Methods: We conducted a retrospective review of ED visits from January 2013 to September 2017.