City Research Online

Abstract

Digital health is a promising tool to support people with an elevated risk for atherosclerotic cardiovascular disease (ASCVD) and patients with an established disease to improve cardiovascular outcomes. Many digital health initiatives have been developed and employed. However, barriers to their large-scale implementation have remained. This paper focuses on these barriers and presents solutions as proposed by the Dutch CARRIER (ie, Coronary ARtery disease: Risk estimations and Interventions for prevention and EaRly detection) consortium. We will focus in 4 sections on the following: (1) the development process of an eHealth solution that will include design thinking and cocreation with relevant stakeholders; (2) the modeling approach for two clinical prediction models (CPMs) to identify people at risk of developing ASCVD and to guide interventions; (3) description of a federated data infrastructure to train the CPMs and to provide the eHealth solution with relevant data; and (4) discussion of an ethical and legal framework for responsible data handling in health care. The Dutch CARRIER consortium consists of a collaboration between experts in the fields of eHealth development, ASCVD, public health, big data, as well as ethics and law. The consortium focuses on reducing the burden of ASCVD. We believe the future of health care is data driven and supported by digital health. Therefore, we hope that our research will not only facilitate CARRIER consortium but may also facilitate other future health care initiatives.

Publication Type:	Article
Additional Information:	©Bart Scheenstra, Anke Bruninx, Florian van Daalen, Nina Stahl, Elizabeth Latuapon, Maike Imkamp, Lianne Ippel, Sulaika Duijsings-Mahangi, Djura Smits, David Townend, Inigo Bermejo, Andre Dekker, Laura Hochstenbach, Marieke Spreeuwenberg, Jos Maessen, Arnoud van 't Hof, Bas Kietselaer. Originally published in JMIR Cardio (https://cardio.jmir.org), 17.10.2022. 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 JMIR Cardio, is properly cited. The complete bibliographic information, a link to the original publication on https://cardio.jmir.org, as well as this copyright and license information must be included.
Publisher Keywords:	ASCVD; CVRM; atherosclerotic cardiovascular disease; big data; cardiovascular risk management; clinical prediction models; digital Health; eHealth; federated data infrastructure; personalized e-coach
Subjects:	R Medicine > RC Internal medicine T Technology > T Technology (General)
Departments:	The City Law School > Academic Programmes
SWORD Depositor:	Symplectic Administrator

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