Validation of a suspicion index to identify patients at risk for hereditary angioedema

Hereditary angioedema (HAE) is a genetic condition characterized by dysregulation of the contact (kallikrein-bradykinin) pathway, leading to recurrent episodes of angioedema. This project sought to determine whether a suspicion index screening tool using electronic health record (EHR) data can identify patients with an increased likelihood of a diagnosis of HAE. A suspicion index screening tool for HAE was created and validated by using known patients with HAE from the medical literature as well as positive and negative controls from HAE-focused centers. Through the use of key features of medical and family history, a series of logistic regression models for 5 known genetic causes of HAE were created. Top variables populated the digital suspicion scoring system and were run against deidentified EHR data. Patients at 2 diverse sites were categorized as being at increased, possible, or no increased risk of HAE. Prediction scoring using the strongest 13 variables on the “real-world” EHR-positive control data identified all but 1 patient with C1 inhibitor deficiency and patient with non–C1 inhibitor deficiency without false-positive results. The 2 missed patients had no documented family history of HAE in their EHR. When the prediction scoring variables were expanded to 25, the screening algorithm approached 100% sensitivity and specificity. The 25-variable algorithm run on general population EHR data identified 26 patients at the medical centers as being at increased risk for HAE. These results suggest that development, validation, and implementation of suspicion index screening tools can be useful to aid providers in identifying patients with rare genetic conditions.