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Identifying ventricular arrhythmia and sudden cardiac arrest in clinical notes of an electronic health record
Neil Dhopeshwarkar1, Charles Dharmani2, Oluwatosin Fofah2
1Research and Data Solutions, TriNetX, LLC, Cambridge, MA, USA.
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.
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