Abstract
The tools of digital health are facilitating a much-needed paradigm shift to a more patient-centric health care delivery system, yet our health care infrastructure is firmly rooted in a 20th-century model that was not designed to receive medical data from outside the traditional medical environment. COVID-19 has accelerated this adoption and illustrated the challenges that lie ahead as we make this shift. The diverse ecosystem of digital health tools share 1 feature in common: they generate data that must be processed, triaged, acted upon, and incorporated into the longitudinal electronic health record. Critical abnormal findings must be identified and acted upon rapidly, while semi-urgent and noncritical data and trends may be reviewed within a less urgent timeline. Clinically irrelevant findings, which presently comprise a significant percentage of the alerts, ideally would be removed to optimize the high-cost, high-value resource (ie, the clinicians' attention and time). We need to transform our established health care infrastructure, technologies, and workflows to be able to safely, effectively, and efficiently manage the vast quantities of data that these tools will generate. This must include new technologies from industry as well as expert consensus documents from medical specialty societies, including the Heart Rhythm Society. Ultimately, research will be fundamental to inform effective development and implementation of these tools.