Support
Support
Search

The Total Package

The right mix of clinical accuracy,1-4 outstanding patient compliance,5 and elegant implementation to streamline your practice like never before.2,3

Physician talking with patient

Advanced monitors

Our state-of-the-art monitors are designed with patients in mind,6-9 resulting in astounding patient compliance,5 ensuring the data captured are continuous and uninterrupted.8,9

Efficient solutions

The iRhythm monitoring service helps to streamline the use of healthcare resources and support your efforts in building a world-class cardiovascular program.1-3,10 

Exceptional accuracy

We bring precision you can trust4 to your practice through our monitoring services that provide the highest diagnostic yield, the lowest likelihood for retest,2,3,11,12 and end-of-wear reports with 99% physician agreement.1   
Physician showing information to patient

An end-to-end cardiac monitoring service

The iRhythm monitoring service provides you with everything your practice needs. From our advanced, yet simple-to-use Zio® ECG monitors13 to our elegant data management solutions, we are transforming the world of cardiac monitoring with every heartbeat.

Explore the iRhythm service
User researching iRhythm on computer

Advanced AI with a human touch

Our FDA-cleared, deep-learned AI algorithm is proven to be as accurate as expert cardiologists,14-17 enabling you to confidently diagnose arrhythmias including atrial fibrillation.4 The iRhythm monitoring service delivers accurate and succinct reports13 that are curated and verified by our Certified Cardiac Technicians.14-17

Keep reading

Clinical Article
Reynolds et al, American Heart Journal, 2023.
Comparative Effectiveness of ACM Strategies (CAMELOT Study)
A retrospective study of variations in ACM strategies, clinical outcomes and health care costs in diagnostic-naïve patients
Read more
Clinical Article
Eysenck et al., Journal of Interventional Cardiac Electrophysiology, 2019.
Comparison of 4 ACMs to Permanent Pacemaker AF Detection
A prospective, randomized study to compare ACM AF burden and AF episodes in patients implanted with a pacemaker with known AF
Read more
Clinical Article
Hannun et al., Nature Medicine, 2019.
Deep Neural Network to Detect and Classify Arrhythmias
To assess if a deep learning approach can classify a broad range of arrhythmias with diagnostic performance of cardiologists
Read more
Continue the conversation
Man with child on his shoulders
Woman on a headset

Full support

Questions about products, billing, or our services? We have you covered.

iRhythm offers dedicated support to help with issues like inventory management and customer satisfaction. We even have a specialized billing team to help manage revenue cycle questions and billing inquiries available 24/7/365. 

Contact us
Patient FAQs
Healthcare professionals FAQs

WEB0185.01

  1. 99% of physicians agree with the comprehensive end-of-wear report. Based on a review of all online Zio XT, Zio monitor, and Zio AT end-of-wear reports. Data on file. iRhythm Technologies, 2023.
  2. Reynolds et al. Comparative effectiveness and healthcare utilization for ambulatory cardiac monitoring strategies in Medicare beneficiaries. Am Heart J. 2024;269:25-34. doi.org/10.1016/j.ahj.2023.12.002
  3. Based on previous generation Zio XT device data. Zio monitor utilizes the same operating principles and ECG algorithm. Additional data on file.
  4. Data on file. iRhythm Technologies, 2022-2023.
  5. Data on file. iRhythm Technologies, 2022.
  6. Zio AT Clinical Reference Manual. iRhythm Technologies, 2022. 
  7. ​Zio AT does not require battery changes or charging. Zio AT has wear-time transmission limits and is contraindicated for critical care patients. Refer to the Zio AT Clinical Reference Manual for additional information.
  8. Zio XT Clinical Reference Manual. iRhythm Technologies, 2019.
  9. Zio monitor Instructions for Use. iRhythm Technologies, 2023.
  10. ZioSuite Clinical Reference Manual. iRhythm Technologies, 2022.
  11. In testing for specified arrhythmias defined by Hierarchical Condition Categories (HCC) 96.
  12. Among continuous cardiac monitoring services.
  13. Data on file. iRhythm Technologies, 2023.
  14. Data on file. iRhythm Technologies, 2020.
  15. Hannun et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat Med. 2019;25:65-69. doi.org/10.1038/s41591-018-0268-3
  16. Deep-learned algorithm is only available in the United States, European Union, Switzerland, and United Kingdom.
  17. FDA 510K clearance, CE mark, and UKCA mark.

WEB0002.01

Contact us