Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.

Konstantinos Sideris^1,2, Charlene R Weir^1,3, Carsten Schmalfuss^4,5, Heather Hanson^1,2, Matt Pipke⁶, Po-He Tseng⁶, Neil Lewis^7,8, Karim Sallam^9,10, Biykem Bozkurt^11,12, Thomas Hanff^1,2, Richard Schofield^4,5, Karen Larimer⁶, Christos P Kyriakopoulos^1,2, Iosif Taleb^1,2, Lina Brinker^1,2, Tempa Curry^4,5, Cheri Knecht^4,5, Jorie M Butler^1,3, Josef Stehlik^1,2

¹Cardiology Section, Medical Service, George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT 84148, United States.

²Division of Cardiovascular Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT 84112, United States.

³Department of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT 84108, United States.

⁴Cardiology Section, Medical Service, Malcom Randall VA Medical Center, Gainesville, FL 32608, United States.

⁵Division of Cardiovascular Medicine, Department of Internal Medicine, University of Florida College of Medicine, Gainesville, FL 32610, United States.

⁶PhysIQ, Inc., Chicago, IL 60563, United States.

⁷Cardiology Section, Medical Service, Hunter Holmes McGuire Veterans Medical Center, Richmond, VA 23249, United States.

⁸Department of Internal Medicine, Division of Cardiovascular Disease, Virginia Commonwealth University, Richmond, VA 23249, United States.

⁹Cardiology Section, Medical Service, VA Palo Alto Health Care System, Palo Alto, CA 94304, United States.

¹⁰Division of Cardiovascular Medicine, Department of Internal Medicine, Stanford University School of Medicine, Stanford, CA 94305, United States.

¹¹Cardiology Section, Medical Service, Michael E. DeBakey VA Medical Center, Houston, TX 77030, United States.

¹²Section of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, United States.

PubMed PMC DOI PDF

Abstract

OBJECTIVES: We conducted an implementation planning process during the pilot phase of a pragmatic trial, which tests an intervention guided by artificial intelligence (AI) analytics sourced from noninvasive monitoring data in heart failure patients (LINK-HF2). MATERIALS AND METHODS: A mixed-method analysis was conducted at 2 pilot sites. Interviews were conducted with 12 of 27 enrolled patients a…

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Mentioned Companies

physIQ
affiliation

NIH Funding

Grant #11239118
Continuous Wearable Monitoring Analytics to Improve Outcomes in Heart Failure - LINK-HF2 multicenter implementation study
VA SALT LAKE CITY HEALTHCARE SYSTEM

Other Funding

HSRD VA(I01 HX002922)
United States
NCATS NIH HHS(UM1 TR004409)
United States

MeSH Terms

Humans0Ambulatory Care Facilities0Artificial Intelligence*Communication0Heart Failure*Information Technology0

Keywords

artificial intelligencecomputerized decision supportheart failurehome monitoringimplementation

Article Info

PMID: 38341800
PMCID: PMC10990545
DOI: 10.1093/jamia/ocae017
Received: August 25, 2023
Accepted: January 17, 2024

How to Cite

Sideris K et al. Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial. J Am Med Inform Assoc2024;31(4):919-928. doi:10.1093/jamia/ocae017

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