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Review
. 2020 Dec 1;76(22):2650-2670.
doi: 10.1016/j.jacc.2020.09.606.

Gerotechnology for Older Adults With Cardiovascular Diseases: JACC State-of-the-Art Review

Affiliations
Review

Gerotechnology for Older Adults With Cardiovascular Diseases: JACC State-of-the-Art Review

Ashok Krishnaswami et al. J Am Coll Cardiol. .

Abstract

The growing population of older adults (age ≥65 years) is expected to lead to higher rates of cardiovascular disease. The expansion of digital health (encompassing telehealth, telemedicine, mobile health, and remote patient monitoring), Internet access, and cellular technologies provides an opportunity to enhance patient care and improve health outcomes-opportunities that are particularly relevant during the current coronavirus disease-2019 pandemic. Insufficient dexterity, visual impairment, and cognitive dysfunction, found commonly in older adults should be taken into consideration in the development and utilization of existing technologies. If not implemented strategically and appropriately, these can lead to inequities propagating digital divides among older adults, across disease severities and socioeconomic distributions. A systematic approach, therefore, is needed to study and implement digital health strategies in older adults. This review will focus on current knowledge of the benefits, barriers, and use of digital health in older adults for cardiovascular disease management.

Keywords: arrhythmia; barriers; cardiac rehabilitation; clinical trials; diabetes mellitus; digital health; dyslipidemia; gerotechnology; heart failure; hypertension; obesity; older adults; palliative care; telehealth.

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Conflict of interest statement

Author Disclosures Dr. Dorsch is supported by R18 HS026874 and R21 HS026322 from the Agency for Health Research and Quality, R01 AG062582 from the National Institutes of Health (NIH)/National Institute of Aging, and the American Health Association Health IT Research Network; has received honoraria from Janssen; and has received research funding from Bristol Myers Squibb/Pfizer and Amgen in the past 2 years. Dr. Dodson is supported by K23 AG052463 from the NIH/National Institute of Aging, and R01 AG062520 from the NIH/National Institute of Aging. Dr. Masterson Creber is supported by NIH/National Institute of Nursing Research R00NR016275, and NIH/National Heart, Lung, and Blood Institute R01HL152021. Dr. Kitsiou is supported by the NIH/National Institute of Nursing Research R01NR017635 and R21NR018281, NIH/National Heart, Lung, and Blood Institute R61HL139454, and NIH/National Institute on Aging P30AG022849. Dr. Goyal is supported by the National Institute on Aging (NIA) grant R03AG056446 and American Heart Association grant 18IPA34170185. Dr. Maurer has received grant support from National Institutes of Health R01HL139671-01, R21AG058348, and K24AG036778; has received consulting income from Pfizer, GlaxoSmithKline, EIdos, Prothena, Akcea, and Alnylam; and his institution has received clinical trial funding from Pfizer, Prothena, Eidos, and Alnylam. Dr. Batsis is supported in part by the National Institute on Aging of the National Institutes of Health under Award Number K23AG051681 and R01-AG067416; and has part ownership in a patent developed for the Instrumented Resistance Exercise Device (Dartmouth Patent application # 62/672,827). Dr. Turakhia has received grants unrelated to this work from Apple, Janssen, Bayer, AstraZeneca, Boehringer Ingelheim, the American Heart Association, and Bristol Myers Squibb; has been a consultant to Medtronic, Biotronik, Pfizer, Bayer, Novartis, Sanofi, Johnson & Johnson, Myokardia, and Milestone Pharmaceuticals unrelated to this work; and is an editor for JAMA Cardiology. Dr. Forman is supported by the NIH National Institute on Aging R01AG060499-01, R01AG058883, and P30AG024827, and the NIH Common Fund U01AR071130. Dr. Bernacki is supported by T32HL125195-04 from the NIH/National Heart, Lung, and Blood Institute. Dr. Peterson has received research funding from AstraZeneca, Janssen, Amgen, and Sanofi unrelated to this work. Dr. Freeman does nonpromotional speaking for Boehringer Ingelheim; has served on Advisory Boards for The Medicines Company and Regeneron; and has served as a consultant for Actelion, none of which are related to the work submitted. Dr. Bhavnani has served as a scientific advisor to Analytics 4 Life and Blumio; has served as a consultant to Bristol Myers Squibb and Pfizer; and has received research support from Scripps Clinic, Alliance Healthcare Foundation, and the Qualcomm Foundation outside of the present work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. The views expressed in this paper are by members of the American College of Cardiology’s Innovation Council, Cardiovascular Team Council and the Geriatric Cardiology Section Leadership Council and do not necessarily reflect the views of the Journal of the American College of Cardiology or the American College of Cardiology.

Figures

FIGURE 1
FIGURE 1
Temporal Trend in U.S. Mobile Technology Use (A) Mobile cellular subscriptions (131); (B) Internet usage (131).
FIGURE 2
FIGURE 2. Real-World Examples of Remote Patient Monitoring With Digital Health Technologies in Hypertension and Atrial Fibrillation
(A and B) A 86-year-old woman with a history of sick sinus syndrome, pacemaker implantation, and hypertension on an angiotensin-converting enzyme (ACE) inhibitor and calcium-channel blocker with uncontrolled blood pressure (BP) enrolled in remote patient monitoring in January 2019. Collection and transmission of patient-generated BP data on a daily basis, entered on a smartphone application, and direct upload to her electronic medical record. Monthly review of digital data with titration and initiation of antihypertensive therapy (blue arrows) between February 2019 and May 2019 (A) achieving sustained BP reduction to February 2020 (B). (C and D) A 78-year-old man with a history of paroxysmal atrial fibrillation and hypertensive heart disease. Enrolled in remote patient monitoring in February 2019 with the smartphone ECG. Symptomatic recurrence of PAF (red circles) captured in November 2019 (C) and medication initiation with conversion to sinus rhythm (blue circles). Recurrence in April 2020 (D, red arrow) that coincided with an upper respiratory tract infection. Both examples highlight long-term digital engagement in older adult patients.
CENTRAL ILLUSTRATION
CENTRAL ILLUSTRATION
Identify goals of care: Includes disease-based and overarching goals of care. Consider patient-centered outcome sought as a function of treatment burden. Assess barriers to digital health use: Engineering, decision support, and human barriers (physical, cognitive, other age-related barriers, privacy, tech anxiety, motivational inertia, decreased trust in individual abilities, accessibility, family member integration, socioeconomic). See Table 2. Optimize patient technology match: Matching what matters most, individual preference, individual barriers to specific technology. Support participant and caregiver(s): Easy to read/understand instructions, ensure HELP-line available, in-person and virtually. Reassess impact: On patient-centered, disease-based, and overarching goals of care and quality of life. Adapted with permission from (75).

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