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

Area of Science:

• Cardiology
• Medical Technology
• Artificial Intelligence

Background:

• Insertable cardiac monitors (ICMs) are crucial for arrhythmia management but generate numerous transmissions and false alerts.
• Integrating artificial intelligence (AI) into ICM workflows can mitigate this burden.
• The impact of AI-enhanced ICMs on clinic workflow and resource utilization requires further investigation.

Purpose of the Study:

• To evaluate the effect of AI-enhanced ICMs on clinic workflow and resource utilization.
• To quantify the reduction in nonactionable alerts (NAAs) with AI integration.

Main Methods:

• A cross-sectional analysis of real-world ICM remote monitoring data from 140 U.S. clinics (July 2022-April 2024).
• Comparison of NAAs between AI-enhanced and non-AI-enhanced ICMs.
• Estimation of associated staffing hours, resources, and costs for a 600-ICM patient clinic.

Main Results:

• AI-enhanced ICMs reduced annual NAAs from 5,078 to 2,110 per 600-patient clinic.
• This reduction resulted in 559 fewer staffing hours and $29,470 in annual cost savings.
• AI-enhanced ICMs were used by 32% of the 19,320 patients studied.

Conclusions:

• AI-enhanced ICMs significantly decrease NAAs compared to traditional ICMs.
• This reduction leads to decreased clinic workload and associated costs.
• AI integration in ICMs shows potential for improving healthcare efficiency and patient management.