Identification and Validation of Anaphylaxis Using Electronic Health Data in a Population-based Setting
- PMID: 33591057
- DOI: 10.1097/EDE.0000000000001330
Identification and Validation of Anaphylaxis Using Electronic Health Data in a Population-based Setting
Abstract
Background: Anaphylaxis is a life-threatening allergic reaction that is difficult to identify accurately with administrative data. We conducted a population-based validation study to assess the accuracy of ICD-10 diagnosis codes for anaphylaxis in outpatient, emergency department, and inpatient settings.
Methods: In an integrated healthcare system in Washington State, we obtained medical records from healthcare encounters with anaphylaxis diagnosis codes (potential events) from October 2015 to December 2018. To capture events missed by anaphylaxis diagnosis codes, we also obtained records on a sample of serious allergic and drug reactions. Two physicians determined whether potential events met established clinical criteria for anaphylaxis (validated events).
Results: Out of 239 potential events with anaphylaxis diagnosis codes, the overall positive predictive value (PPV) for validated events was 64% (95% CI = 58 to 70). The PPV decreased with increasing age. Common precipitants for anaphylaxis were food (39%), medications (35%), and insect bite or sting (12%). The sensitivity of emergency department and inpatient anaphylaxis diagnosis codes for all validated events was 58% (95% CI = 51 to 65), but sensitivity increased to 95% (95% CI = 74 to 99) when outpatient diagnosis codes were included. Using information from all validated events and sampling weights, the incidence rate for anaphylaxis was 3.6 events per 10,000 person-years (95% CI = 3.1 to 4.0).
Conclusions: In this population-based setting, ICD-10 diagnosis codes for anaphylaxis from emergency department and inpatient settings had moderate PPV and sensitivity for validated events. These findings have implications for epidemiologic studies that seek to estimate risks of anaphylaxis using electronic health data.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Comment in
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Re. Identification and Validation of Anaphylaxis Using Electronic Health Data in a Population-based Setting.Epidemiology. 2022 Jan 1;33(1):e2. doi: 10.1097/EDE.0000000000001427. Epidemiology. 2022. PMID: 34847086 No abstract available.
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The Authors Respond.Epidemiology. 2022 Jan 1;33(1):e2-e3. doi: 10.1097/EDE.0000000000001426. Epidemiology. 2022. PMID: 34847087 No abstract available.
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