Abstract
BackgroundThe epidemiologic impact of hereditary angioedema (HAE) is difficult to quantify, due to misclassification in retrospective studies resulting from non-specific diagnostic coding. The aim of this study was to identify cohorts of patients with HAE-1/2 by evaluating structured and unstructured data in a US ambulatory electronic medical record (EMR) database.MethodsA retrospective feasibility study was performed using the GE Centricity EMR Database (2006–2017). Patients with ≥ 1 diagnosis code for HAE-1/2 (International Classification of Diseases, Ninth Revision, Clinical Modification 277.6 or International Classification of Diseases, Tenth Revision, Clinical Modification D84.1) and/or ≥ 1 physician note regarding HAE-1/2 and ≥ 6 months’ data before and after the earliest code or note (index date) were included. Two mutually exclusive cohorts were created: probable HAE (≥ 2 codes or ≥ 2 notes on separate days) and suspected HAE (only 1 code or note). The impact of manually reviewing physician notes on cohort formation was assessed, and demographic and clinical characteristics of the 2 final cohorts were described.ResultsInitially, 1691 patients were identified: 190 and 1501 in the probable and suspected HAE cohorts, respectively. After physician note review, the confirmed HAE cohort comprised 254 patients and the suspected HAE cohort decreased to 1299 patients; 138 patients were determined not to have HAE and were excluded. The overall false-positive rate for the initial algorithms was 8.2%. Across final cohorts, the median age was 50 years and > 60% of patients were female. HAE-specific prescriptions were identified for 31% and 2% of the confirmed and suspected HAE cohorts, respectively.ConclusionsUnstructured EMR data can provide valuable information for identifying patients with HAE-1/2. Further research is needed to develop algorithms for more representative HAE cohorts in retrospective studies.
Highlights
The epidemiologic impact of hereditary angioedema (HAE) is difficult to quantify, due to misclassification in retrospective studies resulting from non-specific diagnostic coding
Hereditary angioedema type 1/2 (HAE-1/2) is a rare genetic disease that, from a systematic review of studies in European countries, is estimated to impact ~ 1 in 67,000 individuals [4], but much remains unknown about its prevalence, and there are likely many undiagnosed
A total of 138 patients were removed from the 2 initial cohorts because HAE-1/2 diagnosis was mentioned as a rule-out diagnosis in the physician notes, or only a family history of HAE was mentioned (Fig. 2)
Summary
The epidemiologic impact of hereditary angioedema (HAE) is difficult to quantify, due to misclassification in retrospective studies resulting from non-specific diagnostic coding. Gaining real-world insights to improve diagnosis rates and Hereditary angioedema type 1/2 (HAE-1/2) is a rare genetic disease that, from a systematic review of studies in European countries, is estimated to impact ~ 1 in 67,000 individuals [4], but much remains unknown about its prevalence, and there are likely many undiagnosed. Symptoms of HAE that overlap with more common disorders, such as allergic angioedema and appendicitis, can make accurate and rapid diagnosis challenging [5, 6]. The epidemiologic impact of HAE is difficult to quantify due to the challenges of diagnosis combined with the necessity of using non-specific diagnosis codes, impacting the accuracy of studies that leverage existing data
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