UMMS Affiliation

Division of Cardiovascular Medicine, Department of Medicine; Department of Quantitative Health Sciences

Publication Date

2019-03-01

Document Type

Article

Disciplines

Cardiology | Cardiovascular Diseases | Diagnosis | Telemedicine

Abstract

BACKGROUND: New models of scalable population-based data collection that integrate digital and mobile health (mHealth) data are necessary.

OBJECTIVE: The aim of this study was to describe a cardiovascular digital and mHealth electronic cohort (e-cohort) embedded in a traditional longitudinal cohort study, the Framingham Heart Study (FHS).

METHODS: We invited eligible and consenting FHS Generation 3 and Omni participants to download the electronic Framingham Heart Study (eFHS) app onto their mobile phones and co-deployed a digital blood pressure (BP) cuff. Thereafter, participants were also offered a smartwatch (Apple Watch). Participants are invited to complete surveys through the eFHS app, to perform weekly BP measurements, and to wear the smartwatch daily.

RESULTS: Up to July 2017, we enrolled 790 eFHS participants, representing 76% (790/1044) of potentially eligible FHS participants. eFHS participants were, on average, 53+/-8 years of age and 57% were women. A total of 85% (675/790) of eFHS participants completed all of the baseline survey and 59% (470/790) completed the 3-month survey. A total of 42% (241/573) and 76% (306/405) of eFHS participants adhered to weekly digital BP and heart rate (HR) uploads, respectively, over 12 weeks.

CONCLUSIONS: We have designed an e-cohort focused on identifying novel cardiovascular disease risk factors using a new smartphone app, a digital BP cuff, and a smartwatch. Despite minimal training and support, preliminary findings over a 3-month follow-up period show that uptake is high and adherence to periodic app-based surveys, weekly digital BP assessments, and smartwatch HR measures is acceptable.

Keywords

ambulatory, blood pressure monitoring, cohort studies, smartphone, tele-medicine

Rights and Permissions

© David D McManus, Ludovic Trinquart, Emelia J Benjamin, Emily S Manders, Kelsey Fusco, Lindsey S Jung, Nicole L Spartano, Vik Kheterpal, Christopher Nowak, Mayank Sardana, Joanne M Murabito. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 01.03.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

DOI of Published Version

10.2196/12143

Source

J Med Internet Res. 2019 Mar 1;21(3):e12143. doi: 10.2196/12143. Link to article on publisher's site

Journal/Book/Conference Title

Journal of medical Internet research

Related Resources

Link to Article in PubMed

PubMed ID

30821691

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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