Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association

Overview

Journal Circ Genom Precis Med

Specialties Cardiology & Vascular Diseases
Genetics

Date 2024 May 23

PMID 38779844

Authors

Antonis A Armoundas

Faraz S Ahmad

Derrick A Bennett

Mina K Chung

Leslie L Davis

Jessilyn Dunn

Sanjiv M Narayan

David J Slotwiner

Kevin Keith Wiley Jr

Rohan Khera

Affiliations

Soon will be listed here.

Abstract

Wearable devices are increasingly used by a growing portion of the population to track health and illnesses. The data emerging from these devices can potentially transform health care. This requires an interoperability framework that enables the deployment of platforms, sensors, devices, and software applications within diverse health systems, aiming to facilitate innovation in preventing and treating cardiovascular disease. However, the current data ecosystem includes several noninteroperable systems that inhibit such objectives. The design of clinically meaningful systems for accessing and incorporating these data into clinical workflows requires strategies to ensure the quality of data and clinical content and patient and caregiver accessibility. This scientific statement aims to address the best practices, gaps, and challenges pertaining to data interoperability in this area, with considerations for (1) data integration and the scope of measures, (2) application of these data into clinical approaches/strategies, and (3) regulatory/ethical/legal issues.

Citing Articles

Addressing contemporary threats in anonymised healthcare data using privacy engineering.

Narayan S, Kohli N, Martin M NPJ Digit Med. 2025; 8(1):145.

PMID: 40050672 PMC: 11885643. DOI: 10.1038/s41746-025-01520-6.

Consumer-grade wearable devices in arrhythmia diagnostics for clinicians: where we are and where we are going.

Rytkin E, Zotova I, Passman R, Ardashev A, Trachiotis G, Efimov I J Interv Card Electrophysiol. 2025; .

PMID: 39863724 DOI: 10.1007/s10840-025-01994-0.

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases.

DeGroat W, Abdelhalim H, Peker E, Sheth N, Narayanan R, Zeeshan S Sci Rep. 2024; 14(1):26503.

PMID: 39489837 PMC: 11532369. DOI: 10.1038/s41598-024-78553-6.

Cardiovascular care with digital twin technology in the era of generative artificial intelligence.

Thangaraj P, Benson S, Oikonomou E, Asselbergs F, Khera R Eur Heart J. 2024; .

PMID: 39322420 PMC: 11638093. DOI: 10.1093/eurheartj/ehae619.

References

Campbell P, Drazner M, Kato M, Lakdawala N, Palardy M, Nohria A . Mismatch of right- and left-sided filling pressures in chronic heart failure. J Card Fail. 2011; 17(7):561-8. DOI: 10.1016/j.cardfail.2011.02.013. View

Redon P, Shahzad A, Iqbal T, Wijns W . Development of a New Detection Algorithm to Identify Acute Coronary Syndrome Using Electrochemical Biosensors for Real-World Long-Term Monitoring. Bioengineering (Basel). 2021; 8(2). PMC: 7924205. DOI: 10.3390/bioengineering8020028. View

Baig M, Afifi S, GholamHosseini H, Mirza F . A Systematic Review of Wearable Sensors and IoT-Based Monitoring Applications for Older Adults - a Focus on Ageing Population and Independent Living. J Med Syst. 2019; 43(8):233. DOI: 10.1007/s10916-019-1365-7. View

Cho P, Yi J, Ho E, Shandhi M, Dinh Y, Patil A . Demographic Imbalances Resulting From the Bring-Your-Own-Device Study Design. JMIR Mhealth Uhealth. 2021; 10(4):e29510. PMC: 9034431. DOI: 10.2196/29510. View

Mandel J, Kreda D, Mandl K, Kohane I, Ramoni R . SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. J Am Med Inform Assoc. 2016; 23(5):899-908. PMC: 4997036. DOI: 10.1093/jamia/ocv189. View

Frank R, Jarrin R, Pritzker J, Abramoff M, Repka M, Baird P . Developing current procedural terminology codes that describe the work performed by machines. NPJ Digit Med. 2022; 5(1):177. PMC: 9719561. DOI: 10.1038/s41746-022-00723-5. View

Attia Z, Harmon D, Dugan J, Manka L, Lopez-Jimenez F, Lerman A . Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction. Nat Med. 2022; 28(12):2497-2503. PMC: 9805528. DOI: 10.1038/s41591-022-02053-1. View

Sharma A, Mahaffey K, Gibson C, Hicks K, Alexander K, Ali M . Clinical events classification (CEC) in clinical trials: Report on the current landscape and future directions - proceedings from the CEC Summit 2018. Am Heart J. 2022; 246:93-104. DOI: 10.1016/j.ahj.2021.12.012. View

Hermans A, Gawalko M, Dohmen L, van der Velden R, Betz K, Duncker D . Mobile health solutions for atrial fibrillation detection and management: a systematic review. Clin Res Cardiol. 2021; 111(5):479-491. PMC: 8454991. DOI: 10.1007/s00392-021-01941-9. View

10.

Nelson B, Allen N . Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study. JMIR Mhealth Uhealth. 2019; 7(3):e10828. PMC: 6431828. DOI: 10.2196/10828. View

11.

Avram R, Olgin J, Kuhar P, Hughes J, Marcus G, Pletcher M . A digital biomarker of diabetes from smartphone-based vascular signals. Nat Med. 2020; 26(10):1576-1582. PMC: 8483886. DOI: 10.1038/s41591-020-1010-5. View

12.

Tang P, Ash J, Bates D, Overhage J, Sands D . Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption. J Am Med Inform Assoc. 2005; 13(2):121-6. PMC: 1447551. DOI: 10.1197/jamia.M2025. View

13.

Xiao H, Qasem A, Butlin M, Avolio A . Estimation of aortic systolic blood pressure from radial systolic and diastolic blood pressures alone using artificial neural networks. J Hypertens. 2017; 35(8):1577-1585. DOI: 10.1097/HJH.0000000000001337. View

14.

Abraham J, Bharmi R, Jonsson O, Oliveira G, Artis A, Valika A . Association of Ambulatory Hemodynamic Monitoring of Heart Failure With Clinical Outcomes in a Concurrent Matched Cohort Analysis. JAMA Cardiol. 2019; 4(6):556-563. PMC: 6537799. DOI: 10.1001/jamacardio.2019.1384. View

15.

Svennberg E, Friberg L, Frykman V, Al-Khalili F, Engdahl J, Rosenqvist M . Clinical outcomes in systematic screening for atrial fibrillation (STROKESTOP): a multicentre, parallel group, unmasked, randomised controlled trial. Lancet. 2021; 398(10310):1498-1506. DOI: 10.1016/S0140-6736(21)01637-8. View

16.

Irizarry T, DeVito Dabbs A, Curran C . Patient Portals and Patient Engagement: A State of the Science Review. J Med Internet Res. 2015; 17(6):e148. PMC: 4526960. DOI: 10.2196/jmir.4255. View

17.

McGraw D, Mandl K . Privacy protections to encourage use of health-relevant digital data in a learning health system. NPJ Digit Med. 2021; 4(1):2. PMC: 7782585. DOI: 10.1038/s41746-020-00362-8. View

18.

Sharma M, Kumar K, Kumar P, Tan R, Rajendra Acharya U . Pulse oximetrysignal for automated identification of sleep apnea: a review and future trends. Physiol Meas. 2022; 43(11). DOI: 10.1088/1361-6579/ac98f0. View

19.

Gallas B, Badano A, Dudgeon S, Elfer K, Garcia V, Lennerz J . FDA Fosters Innovative Approaches in Research, Resources, and Collaboration. Nat Mach Intell. 2024; 4(2):97-98. PMC: 10895477. DOI: 10.1038/s42256-022-00450-2. View

20.

Adler-Milstein J, Nong P . Early experiences with patient generated health data: health system and patient perspectives. J Am Med Inform Assoc. 2019; 26(10):952-959. PMC: 7647206. DOI: 10.1093/jamia/ocz045. View