Identifying ventricular arrhythmia and sudden cardiac arrest in clinical notes of an electronic health record database

Abstract

Aim: Validating an operational algorithm for identifying ventricular arrhythmia and sudden cardiac arrest (VA/SCA) in electronic health record (EHR) data may be useful to minimize measurement bias in studies characterizing real-world VA/SCA risk; however, validation studies require an appropriate reference standard. We aimed to assess if adequate information is documented in unstructured clinical notes of a large EHR database to serve as a reference standard for future validation studies of VA/SCA. Methods: Twenty potential VA/SCA events were randomly selected from unstructured clinical notes of a large EHR database, TriNetX Dataworks–USA. These notes were reviewed to assess if key clinical elements were documented to confirm the occurrence of VA/SCA and describe their clinical features. These included explicit documentation of an acute event, electrocardiogram (ECG) findings, urgent medical interventions, and other elements. Results: Explicit documentation of an acute event was recorded for 17 patients (85.0%) and ECG findings were documented for 15 patients (75.0%). Generally, unstructured clinical notes also contained information about signs and symptoms, care setting, medical interventions administered, and event resolution. Conclusions: The unstructured clinical notes of a large EHR database contained the information necessary to serve as a reference standard for validation studies of a VA/SCA operational algorithm in EHR data.