Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization

BACKGROUND: Insertable cardiac monitors (ICMs) are essential for managing arrhythmias but often generate large numbers of transmissions and false alerts. Integrating artificial intelligence (AI) as part of the ICM workflow can reduce this burden. However, its impact on clinic workflow and resource utilization must be better understood. OBJECTIVES: The aim of the study was to assess the impact of AI-enhanced ICMs on clinic workflow and resource utilization. METHODS: A cross-sectional analysis was conducted using real-world, deidentified ICM remote monitoring data from Octagos Health, which included 140 U. S. device clinics between July 2022 and April 2024. Nonactionable alerts (NAAs) were defined as false or repetitive alerts transmitted on the remote monitoring platforms but dismissed by device technicians and not forwarded to clinicians for review. We compared NAAs generated by AI-enhanced vs non-AI-enhanced ICMs and estimated associated staffing hours, resources, and costs extrapolated for a clinic managing 600 ICM patients. RESULTS: Among 19, 320 patients (mean age: 69 ± 13. 5 years; 47. 3% male), 68% had non-AI-enhanced ICMs, and 32% had AI-enhanced ICMs. The mean annual NAA volume per 600-ICM clinic was 5, 078 for non-AI-enhanced ICMs and 2, 110 for AI-enhanced ICMs, resulting in 559 fewer staffing hours (956 vs 397 hours; 95% CI: 513-605 hours; P value < 0. 001) and 29, 470 in annual savings (20, 929 vs 50, 399; 95% CI: 27, 035-31, 904; P value < 0. 001). CONCLUSIONS: Compared to non-AI-enhanced ICMs, AI-enhanced ICMs significantly reduce NAAs, leading to a projected decrease in clinic workload and associated costs, potentially improving workflow and health care efficiency.