From Clinic to Cloud: Efficacy of AI‐Assisted Remote Monitoring of Patients With Implantable Cardiac Devices.
The integration of telehealth, particularly remote monitoring (RM), has profoundly improved the care of patients with cardiac implantable electronic devices (CIEDs). The recent COVID‐19 pandemic has further accelerated the adoption of RM systems. The implementation of RM to standard clinical care ha...
| Publicado en: | Pacing & Clinical Electrophysiology Vol. 48; no. 10; pp. 1106 - 1114 |
|---|---|
| Autores principales: | , , , , , , |
| Formato: | pictorial review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188520608&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188520608 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01478389 4F8 jtl: Pacing & Clinical Electrophysiology issn: 01478389 maglogo: Y pubinfo: dt: Oct2025 vid: 48 iid: 10 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188520608 187427132 188520608 188520608 10.1111/pace.70036 188520608 ppf: 1106 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: From Clinic to Cloud: Efficacy of AI‐Assisted Remote Monitoring of Patients With Implantable Cardiac Devices. aug: au: Chiu, Cheyenne S. L. Gerrits, Willem Guglielmo, Marco Cramer, Maarten J. van der Harst, Pim van Es, René Meine, Mathias affil: Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht, the Netherlands sug: subj: Artificial Intelligence Telehealth Defibrillators, Implantable Workload Cloud Computing Treatment Outcomes Monitoring, Physiologic Workflow Health Resource Allocation Cardiology Pacemaker, Artificial COVID-19 Pandemic Early Diagnosis Health Care Delivery, Integrated Heart Failure Telemedicine ab: The integration of telehealth, particularly remote monitoring (RM), has profoundly improved the care of patients with cardiac implantable electronic devices (CIEDs). The recent COVID‐19 pandemic has further accelerated the adoption of RM systems. The implementation of RM to standard clinical care has been accompanied by a surge of device transmissions. Especially unscheduled transmissions have resulted in an overwhelming workload for clinicians. As the number of device transmissions is expected to increase further while clinical resources remain limited, workflow optimization is crucial. Artificial intelligence (AI) presents a promising solution. This review outlines recent advances in RM and AI applications for CIEDs. It explores the potential of AI to streamline RM workflows, reduce clinician workload, and enhance heart failure care by enabling early detection of clinical deterioration and timely intervention. In addition, key barriers to implementation are addressed, including data standardization and regulatory considerations. Beyond improving monitoring efficiency and patient outcomes, AI‐supported RM may also help expand access to care through more effective resource allocation and contribute to a more sustainable, future‐proof healthcare system. pubtype: Academic Journal doctype: pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|