E-Health in Hypertension Management: an Insight into the Current and Future Role of Blood Pressure Telemonitoring

Current Hypertension Reports(2020)

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摘要
Purpose of Review Out-of-office blood pressure (BP) monitoring techniques, including home and ambulatory BP monitoring, are currently recommended by hypertension guidelines worldwide to confirm the diagnosis of hypertension and to monitor the appropriateness of treatment. However, such techniques are not always effectively implemented or timely available in the routine clinical practice. In recent years, the widespread availability of e-health solutions has stimulated the development of blood pressure telemonitoring (BPT) systems, which allow remote BP tracking and tighter and more efficient monitoring of patients’ health status. Recent Findings There is currently strong evidence that BPT may be of benefit for hypertension screening and diagnosis and for improving hypertension management. The advantage is more significant when BPT is coupled with multimodal interventions involving a physician, a nurse or pharmacist, and including education on lifestyle and risk factors and drug management. Several randomized controlled studies documented enhanced hypertension management and improved BP control of hypertensive patients through BPT. Potential additional effects of BPT are represented by improved compliance to treatment, intensification, and optimization of drug use, improved quality of life, reduction in risk of developing cardiovascular complications, and cost-saving. Applications based on m-health and making use of wearables or smartwatches integrated with machine learning models are particularly promising for the future development of efficient BPT solutions, and they will provide remarkable support decision tools for doctors. Summary BPT and telehealth will soon disrupt hypertension management. However, which approach will be the most effective and whether it will be sustainable in the long-term still need to be elucidated.
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关键词
E-health,Blood pressure telemonitoring,Hypertension,Telemedicine,M-health,Machine learning
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