Future cardiology · 2025
Identifying ventricular arrhythmia and sudden cardiac arrest in clinical notes of an electronic health record database.
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Dhopeshwarkar Neil, Dharmani Charles, Fofah Oluwatosin, Tu Nora, Khan Nasser, Kou Tzuyung Douglas, Chan K Arnold
Аннотация
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.
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.