Scaling Device Clinics Without Adding Staff

This is part 5 of an 8-part series.

From Alert Overload to Intelligent Care is a data-driven series examining how cardiac remote monitoring is evolving to meet the realities of modern care. As alert volumes grow and care teams face increasing clinical and operational pressure, this series explores the evidence behind smarter monitoring workflows – including AI-assisted triage – and what they mean for patient safety, clinician well-being, and long-term sustainability. Each article focuses on real-world challenges, validated data, and practical insights.

As remote monitoring programs grow, many clinics struggle to scale without increasing staff. Traditional workflows require significant time to review transmissions, document findings, and coordinate follow-up.¹

AI-assisted triage improves efficiency by automating routine review. In the Atlas AI study, more than one-quarter of all transmissions were handled without human review.³ For escalated alerts, clinicians received curated summaries rather than raw data, further reducing review time.¹

These efficiencies allow device nurses, APPs, and electrophysiologists to manage larger patient populations without proportional increases in workload. Professional society guidance recognizes automation and third-party support as reasonable strategies for sustaining remote monitoring programs at scale.³

Curious how clinics are scaling monitoring programs without increasing staff? Request a demo.

References

1. Varma N, et al. Workflow efficiency and staffing considerations in remote monitoring. Heart Rhythm.
2. Boriani G, et al. Time and resource utilization in remote ICD follow-up. Europace.
3. HRS/EHRA Expert Consensus Statement on Remote Device Clinics. 2023.

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Next in the series → The Financial Impact of Intelligent Remote Monitoring