Does poor quality data affect your ability to diagnose and treat your patients?

There’s a better way.

The most
advanced AI in cardiac monitoring.1,2,3,4

Zio is the only solution to combine 14 days of uninterrupted ECG data with the most advanced AI in cardiac monitoring.1,2,3,4 Now, you can diagnose patients accurately the first time.
READ THE NATURE
MEDICINE STUDY ON AI
ai-matrix

4 million+
patient records5

34 layer
deep neural
network

1 billion+ hours
of heart
rhythm data

High-quality, actionable data
helps you:

Reach a
definitive diagnosis
73% of patients who wore Zio were diagnosed with an arrhythmia vs. 20% with Holter monitoring.6
Decrease
time to treatment
Achieve a 5-week decrease in time to diagnosis with Zio.7
Improve
patient access
Reduce backlog and diagnose 5x more patients with the Zio service vs. other modalities.8

Zio has the only FDA-cleared, deep learned algorithm that’s as accurate as human, expert-level interpretation.2,3,4,9

Over 1 billion hours of curated ECG data, Deep learned, Machine learned, Expert rule, Human, expert-level interpretation, Algorithm Timeline, Average Sensitivity

Data on file, iRhythm Technologies, 2022.

Hannun, AY. et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nature Medicine, 2019.

Deep learned algorithm is only available in the United States.


FDA 510K clearance.

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Bensimhon-portrait-2022

“AI is really important . . . I have all this really good data behind me to back up what I’m telling you.”

Daniel Bensimhon, MD
Cardiologist, specializing in heart failure
Greensboro, NC

Let’s talk.

We’d love to know how we can help you and your patients.
  1. Over 4 million patient records, over 1 billion hours of heart rhythm data, 34 layer deep neural network. Data on file. iRhythm Technologies, 2022.
  2. Hannun, AY. et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nature Medicine, 2019.
  3. FDA 510K clearance.
  4. Deep learned algorithm is only available in the United States.
  5. iRhythm Technologies, 2020. Form 10-K 2019. Retrieved from https://investors.irhythmtech.com/sec-filings/sec-filing/10-k/0001388658-20-000034.

  1. Case study data was gathered in partnership with the health system featured. The name and identifying details of the health system have been changed to protect the privacy of patients and practices. Healthcare System C. Source: Data on file. iRhythm Technologies. Diagnostic yield increased: 73.4% of patients received a definitive diagnosis vs. 20% with Holter monitoring.
  2. Healthcare System D, Partnering to improve processes and performance of a cardiovascular program: case study.
  3. Case study. New Mexico Heart Institute. Data on file at iRhythm 2018–2021. Analysis comparing Holter to Zio with no additional staff added. iRhythm Technologies, 2021.
  4. Data on file. iRhythm Technologies 2020.