Algorithm for the diagnosis of anaphylaxis and its validation using population-based data on emergency department visits for anaphylaxis in Florida

Abstract

Background: Epidemiologic studies of anaphylaxis have been limited by significant underdiagnosis.

Objective: The purpose of this study was to develop and validate a method for capturing previously unidentified anaphylaxis cases by using International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) based datasets.

Methods: Florida emergency department data for the years 2005 and 2006 from the Florida Agency for Health Care Administration were used. Patients with anaphylaxis were identified by using ICD-9-CM codes specifically indicating anaphylaxis or an ICD-9-CM algorithm based on the definition of anaphylaxis proposed at the 2005 National Institute of Allergy and Infectious Disease and the Food Allergy and Anaphylaxis Network symposium. Cases ascertained with the algorithm were compared with the traditional case-ascertainment method. Comparisons included demographic and clinical risk factors, proportion of monthly visits, and age/sex-specific rates. Cases ascertained with anaphylaxis ICD-9-CM codes were excluded from those ascertained with the algorithm.

Results: One thousand one hundred forty-nine patients were identified by using anaphylaxis ICD-9-CM codes, and 1,602 patients were identified with the algorithm. The clinical risk factors and demographics of cases were consistent between the 2 methods. However, the algorithm was more likely to identify older subjects (P < .0001), those with hypertension or heart disease (P < .0001), and subjects with venom-induced anaphylaxis (P < .0001).

Conclusion: This study introduces and validates an ICD-9-CM-based diagnostic algorithm for the diagnosis of anaphylaxis to capture subjects missed by using the ICD-9-CM anaphylaxis codes. Fifty-eight percent of anaphylaxis cases would be missed without the use of the algorithm, including 88% of venom-induced cases.