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Use of an Artificial Intelligence Algorithm to Increase Productivity in Implantable Loop Recorder Monitoring: A

Cherry Alexander¹, Alan Robertson², Sophie Bagnall³

¹Department of Cardiology, Queen Elizabeth University Hospital Glasgow, Glasgow, GBR.

|May 25, 2026

Summary

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Pulse rhythm

Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac muscle...

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Artificial intelligence (AI) significantly reduced insertable loop recorder (ILR) alerts in a real-world study. This AI implementation freed up valuable staff time for patient care.

Area of Science:

Cardiology
Medical Technology
Artificial Intelligence in Healthcare

Background:

Insertable loop recorder (ILR) services face challenges with high volumes of non-actionable transmitted episodes.
Cloud-based AI algorithms offer a solution to suppress false atrial fibrillation (AF) alerts and preserve clinically relevant events.
This study presents the first real-world impact of an AI algorithm across a multicentre ILR cohort.

Purpose of the Study:

To evaluate the real-world impact of an AI algorithm on insertable loop recorder (ILR) alert burden.
To assess the effect of AI on clinician-facing transmitted alerts in a multicentre setting.
To quantify the potential release of staff capacity due to AI-driven alert reduction.

Main Methods:

A retrospective, multicentre before-and-after cohort analysis was conducted.

Keywords:

atrial fibrillation management deep learning artificial intelligence disruptive innovation implantable loop recorder (ilr)unexplained syncope

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The study compared 12 months of ILR monitoring before and after AI platform activation (Medtronic AccuRhythm AI).

Alert counts were analyzed, with secondary analyses on alert concentration and workflow impact using established time-and-motion data.

Main Results:

Total transmitted alert volume decreased by 29% post-AI activation (4,261 pre-AI vs. 2,509 post-AI).
A statistically significant mean reduction of -3.94 alerts per patient was observed (p<0.05).
The reduction translated to an estimated 185-218 hours of physiologist review time released annually.

Conclusions:

AI activation in routine practice significantly reduced ILR alert burden.
A clinically meaningful release of staff capacity was achieved, equivalent to approximately four hours per week.
Optimizing management of high-alert patients and connectivity can further enhance operational benefits.