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

ABSTRACT:

Background

Epidemiologic studies of anaphylaxis commonly rely on International Classification of Diseases (ICD) 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 ICD codes and other administrative data compared with ICD 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. Potential ED anaphylaxis visits were identified using 3 methods: anaphylaxis ICD diagnostic codes (method 1), ICD symptom-based codes with or without a code indicating an allergic trigger (method 2), and

SUBMITTER: Campbell RL 

PROVIDER: S-EPMC10509887 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature