Performance and Integration of Smartphone Wireless ECG Monitoring into the Enterprise Electronic Health Record: First Clinical Experience. Issue 15 (January 2022)

• Record Type: Journal Article
• Authors: Cho, Geoffrey W; Almeida, Shone O; Gang, Eli S; Elad, Yaron; Duncan, Ray; Budoff, Matthew J; Karlsberg, Ronald P
• Is Part Of: Clinical medicine insights. Issue 15(2022)
• Publication Date: 2022-01
• Subjects: Remote monitoring -- atrial fibrillation -- wearables -- ventricular tachycardia -- electrocardiogram -- AliveCor -- KardiaPro -- KardiaMobile -- smartphone EKG -- Kardia; Clinical medicine -- Case studies -- Periodicals; Medicine; Clinical medicine; Electronic journals; Case Reports; Periodicals; Case Reports; Fulltext; Internet Resources; Periodicals; Case studies; Periodicals; 616.09
• DOI: 10.1177/11795476211069194
• Languages: English
• ISSNs: 1179-5476

Abstract

Introduction: Patient initiated, remote cardiac monitoring has proved to be a significant advance in the diagnosis and management of arrhythmias. Further improvements in ease of use and access to results will further improve health outcomes and cost-effectiveness. Here we describe a proof-of-concept evaluation to assess the feasibility of successfully implementing a cloud-based management system using KardiaPro (KP) for remote electrocardiogram (ECG) monitoring to interface into EPIC, an enterprise electronic health record (EHR) system. Methods: The KP management system was embedded using hypertext markup language (HTML) code directly into the EHR. Encrypted credentials and patient data were bundled with an application programming interface key allowing linkage of remote monitoring from patients' smartphones. During the time of implementation, a total of 322 patients and 32 179 ECGs were recorded. Results: The KP-EHR interface provided full functionality, allowing detection, interpretation and documentation of atrial fibrillation (AF), flutter events, ventricular tachycardia, and complete heart block. Our study focused on KP's detection of AF, and 16.7% of tracings were classified as probable AF with only 2.3% of tracings not analyzed by the KP algorithm because of tracings that were too noisy or truncated. Enhanced management was facilitated with clinical information immediately accessible. Blinded physician ECG review validated the KP proprietary algorithm interpretation and ECGs. Conclusions: Direct integration of KP into EHR was successful and practical. It allows for historical, point of care and immediate retrieval of remote ambulatory monitoring data and documentation into the electronic health record. KP EHR integration warrants further study as it has the potential to improve cost-effectiveness and clinical diagnostic value, leading to improvements in delivery of patient care.