Overview

Overview

Our Mission:

To bridge the gap between digital health technologies and clinical practice through research and education by assessing these technologies and wearable devices, providing guidance to patients and health care providers and the community at large.

Ninety percent of Americans are connected to the internet, and 77% of them own a smartphone. These trends have laid the foundation for a digital health revolution to transform healthcare delivery, especially in cardiovascular care. Cardiovascular digital technology products include wearable and/or portable devices and apps used to monitor cardiovascular measurements.

Of issue is a substantial gap between technology advancements and changing behavior, and the expansion of digital health has not been matched by proper testing or oversight. Additionally, this unprecedented acceleration in technology raises the question of our patients’ ability to adapt to these constantly evolving tools used in their daily care. Most importantly, there is an urgent need to understand if these products can change outcomes, rather than simply record data.

Objectives

The objectives of the HVI Center for Digital Health Technologies are to:

  • Explore and evaluate cardiovascular digital technology products, including wearable devices, smart phone-enabled devices and apps
  • Assess patient adoption of new technology
  • Measure acceptance and outcomes of cardiovascular digital technology
  • Determine the impact of digital technology on healthcare providers, including changes in clinical care, workflow and the ability to keep up with the pace of technology advancements
  • Provide guidance regarding use of devices for patients, healthcare providers and the healthcare system in general

The HVI Center for Digital Health Technologies will connect technology and innovation with testing and research and, most importantly, the clinical experts and patients to improve patient care, safety and experience in the future.

Our Team

Our Team

The HVI Center for Digital Health Technologies includes a multidisciplinary team of medical experts who are committed to enhancing digital health in a variety of cardiovascular settings.

Director: Khaldoun Tarakji, MD, MPH – Electrophysiology and Pacing

Additional experts from a variety of Cleveland Clinic resources including informatics and technology, research and legal departments assist in the evaluation and application of products, providing an atmosphere of innovation and collaboration.

Research & Publications

Research & Publications

  1. Hu PT, Hilow H, Patel D, et al. Use of Virtual Visits for the Care of the Arrhythmia Patient [published online ahead of print, 2020 May 10]. Heart Rhythm. 2020;S1547-5271(20)30432-X. doi:10.1016/j.hrthm.2020.05.011 https://pubmed.ncbi.nlm.nih.gov/32438016/
  2. Seshadri DR1, Bittel B2, Browsky D2, Houghtaling P2, Drummond CK1, Desai MY2, Gillinov AM2. Accuracy of Apple Watch for Detection of Atrial Fibrillation. Circulation. 2020 Feb 25;141(8):702-703. doi: 10.1161/CIRCULATIONAHA.119.044126. Epub 2020 Feb 24.  https://www.ncbi.nlm.nih.gov/pubmed/32091929 
  3. Mehta S, Mehta N, Tang WH, Young J. Cardiologists' Perceptions of Wearable Device in Patients with HF. J Gen Intern Med. 02 January 2020
    DOI: 10.1007/s11606-019-05390-z https://link.springer.com/article/10.1007/s11606-019-05390-z
  4. Seshadri DR1, Bittel B2, Browsky D2, Houghtaling P2, Drummond CK1, Desai M2, Gillinov AM2. Accuracy of the Apple Watch 4 to Measure Heart Rate in Patients With Atrial Fibrillation. IEEE J Transl Eng Health Med. 2019 Dec 13;8:2700204. doi: 10.1109/JTEHM.2019.2950397. eCollection 2020. https://www.ncbi.nlm.nih.gov/pubmed/32128290 
  5. Levy AE, Biswas M, Weber R, Tarakji K, Chung M, Noseworthy PA, Newton-Cheh C, Rosenberg MA. Applications of machine learning in decision analysis for dose management for dofetilide. PLoS One. 2019 Dec 31;14(12):e0227324.
    doi: 10.1371/journal.pone.0227324. eCollection 2019. https://www.ncbi.nlm.nih.gov/pubmed/31891645.
  6. Cameron T. Lambert, MD1; Joseph M. Bumgarner, MD1; Khaldoun G. Tarakji, MD, MPH1. Atrial Fibrillation Detection With Wearable Devices. JAMA. 2019;321(23):2367-2368. doi:10.1001/jama.2019.4538 https://jamanetwork.com/journals/jama/fullarticle/2735811.
  7. Slotwiner DJ1, Tarakji KG2, Al-Khatib SM3, Passman RS4, Saxon LA5, Peters NS6, McCall D7; Advisors. Transparent sharing of digital health data: A call to action. Heart Rhythm. 2019 May 8. pii: S1547-5271(19)30371-6.  doi:
    10.1016/j.hrthm.2019.04.042. https://www.sciencedirect.com/science/article/pii/S1547527119303716?via%3Dihub.
  8. Hussein AA1, Lindsay B1, Madden R1, Martin D1, Saliba WI1, Tarakji KG1, Saqi B1, Rausch DJ1, Dresing T1, Callahan T1, Chung MK1, Baranowski B1, Bhargava M1, Cantillon D1, Rickard J1, Kanj M1, Tchou P1, Wilkoff BL1, Nissen SE1, Wazni OM1. New Model of Automated Patient-Reported Outcomes Applied in Atrial Fibrillation. Circ Arrhythm Electrophysiol. 2019 Mar;12(3):e006986.
    doi: 10.1161/CIRCEP.118.006986. https://www.ahajournals.org/doi/full/10.1161/CIRCEP.118.006986?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dpubmed.
  9. Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines. Feeny AK, Rickard J, Patel D, Toro S, Trulock KM, Park CJ, LaBarbera MA, Varma N, Niebauer MJ, Sinha S, Gorodeski EZ, Grimm RA, Ji X, Barnad J, Madabhushi A, Spragg DD, Chung MK. Circulation: Arrhythmia and Electrophysiology https://www.ahajournals.org/doi/abs/10.1161/CIRCEP.119.007316. 2019 Jul;12(7):e007316.
  10. The gap between what patients know and desire to learn about their cardiac implantable electronic devices. Patel D1, Hu P1, Hilow H1, Lambert CT1, Moufawad M1, Poe S1, Hussein AA1, Baranowski B1, Bhargava M1, Rickard JW1, Cantillon DJ1, Saliba W1, Wilkoff BL1, Wazni O1, Tarakji KG1. Pacing Clin Electrophysiol. 2019 Nov 28.
    doi: 10.1111/pace.13850. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/31782195.
  11. Smartwatch Algorithm for Automated Detection of Atrial Fibrillation. Bumgarner JM, Lambert CT, Hussein AA, Cantillon DJ, Baranowski B, Wolski K, Lindsay BD, Wazni OM, Tarakji KG.
    J Am Coll Cardiol. 2018 May 29;71(21):2381-2388.
    doi: 10.1016/j.jacc.2018.03.003. Epub 2018 Mar 10
  12. Assessing the Accuracy of an Automated Atrial Fibrillation Detection Algorithm Using Novel Smartphone Technology (iREAD STUDY).  Amila D. William MD, Majd Kanbour MD, Thomas Callahan MD, Mandeep Bhargava MD, Ayman Hussein MD, Niraj Varma MD, John Rickard MD, Walid Saliba MD, Kathy Wolski MPH, Oussama M. Wazni MD, Khaldoun G. Tarakji MD MPH.
    Heart Rhythm. 2018 Aug 16. pii: S1547-5271(18)30661-1.
    doi: 10.1016/j.hrthm.2018.06.037.
  13. Success of pacemaker remote monitoring using app based technology: does patient age matter?  Tarakji KG, Vives CA, Patel AS, Fagan DH, Sims JJ, Varma N.
    Pacing Clin Electrophysiol. 2018 Jul 28.
    doi: 10.1111/pace.13461. [Epub ahead of print]
  14. Variable Accuracy of Wearable Heart Rate Monitors during Aerobic Exercise.  Gillinov S, Etiwy M, Wang R, Blackburn G, Phelan D, Gillinov AM, Houghtaling P, Javdikasgari H, Desai MY.
    Med Sci Sports Exerc. 2017 Aug;49(8):1697-1703.
    doi: 10.1249
  15. Accuracy of Wrist-Worn Heart Rate Monitors.  Wang R, Blackburn G, Desai M, Phelan D, Gillinov L, Houghtaling P, Gillinov M.  JAMA Cardiol. 2017 Jan 1;2(1):104-106.
    doi: 10.1001/jamacardio.2016.3340.
  16. Home monitoring of heart failure patients at risk for hospital readmission using a novel under-the-mattress piezoelectric sensor: A preliminary single centre experience.  Bennett MK, Shao M, Gorodeski EZ.  J Telemed Telecare. 2017 Jan;23(1):60-67.
    doi: 10.1177/1357633X15618810. Epub 2016 Jul 9
  17. Using a novel wireless system for monitoring patients after the atrial fibrillation ablation procedure: the iTransmit study.  Tarakji KG, Wazni OM, Callahan T, Kanj M, Hakim AH, Wolski K, Wilkoff BL, Saliba W, Lindsay BD.  Heart Rhythm. 2015 Mar;12(3):554-559.
    doi: 10.1016/j.hrthm.2014.11.015. Epub 2014 Nov 18.
  18. Feeny AK, Chung MK, Madabhushi A, et al. Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology [published online ahead of print, 2020 Jul 6]. Circ Arrhythm Electrophysiol. 2020;10.1161/CIRCEP.119.007952. doi:10.1161/CIRCEP.119.007952
News

News

Consult QD

Contact

Contact

If you would like to learn more about the HVI Center for Digital Health Technologies or collaborate on innovative digital technologies for cardiovascular care, please contact:

Khaldoun Tarakji, MD, MPH
HVI Center for Digital Health Technologies
Cleveland Clinic
9500 Euclid Ave.
Desk J2-2
Cleveland, OH 44195
216.445.9225