Heart failure is linked to serious health problems, high medical expenses, and fatality. A promising approach to enhance the clinical care of heart failure patients and intervene prior to an overt decompensation is remote monitoring technology. Remote Monitoring technologies have shown potential in managing and carrying out medical therapy to improve the health and outcomes for heart failure patients. This review highlights the evidence on currently available remote monitoring technologies and avenues for heart failure patients and discusses the benefits and gaps thereof. The paper specifically focuses on the different categories of interventions, namely technology based, care-program based or a combination of the two, and delves into their outcomes and limitations. Out of the 47 publications included with a minimum sample size of 104 patients, 37 papers demonstrated successful patient compliance and clinical outcomes, while 10 papers hardly demonstrated any successful outcomes. Studies have shown that the use of remote patient monitoring devices lowers patient mortality and re-hospitalization rates while reducing hospitalisations by more than 65%. According to the review research, short- to medium-term advantages such as higher survival rates, lower hospital utilisation, and lower costs are mostly maintained over time. The results demonstrated that patients who used a hybrid (which included both care and technology) strategy of virtual, in-person, and asynchronous care had more convenience, access, improved clinical outcomes, and overall Quality of Life. In addition to these results, remote cardiac monitoring has also been associated with significant cost reductions.


The global population of heart failure (HF) patients climbed from 33.5 million in 1990 to 64.3 million in 2017. The 2017 Heart-disease and Stroke statistics update from the AHA (American Heart Association) indicates that the number of patients with heart failure are surging and is estimated to increase by 46% by 2030, with more than 8 million cases worldwide. Some estimates state that once admitted, 25% of patients are readmitted within 1 month and 50% within 6 months 1. In 2012, the total economic cost of HF was anticipated to be $108 billion annually 2; this cost is expected to have multiplied over the previous ten years. HF is associated with frequent hospitalisations due to episodes of HF decompensation, many of which can be prevented 3. Hence, in recent times, there has been an increased focus towards developing evidence-based interventions for reducing the socioeconomic burden of HF. Remote patient monitoring (RPM) entails the gathering and transfer of clinical-data between a physician and a patient at a remote location via an interface so that the clinician may analyse the data and treat accordingly. Figure 1 shows the general workflow of RPM systems. Symptom monitoring is a key aspect of RPM interventions.

With advancements in sensor technology and computing, parameters like heart rate, respiration rate, oxygen saturation, blood pressure, electrocardiogram, physical activity, sleep quality, body weight, etc. can be assessed by several standalone technological solutions. These include an array of devices such as holter devices, ECG patches, multi-parameter monitors, wearables, mobile applications and web based dashboards. Substantively, these data could show early warning signs of decompensation, better adherence to dietary and medication regimens, and interventions that, if addressed, could avoid or lessen the need for HF hospitalisation and enable early detection of deteriorating disease while the patient is still at home. The COVID-19 outbreak has caused a paradigm change in patient management outside of traditional settings. Patients are becoming selfdriven and engaged in the management of their own health.

The increased usage of digital health management tools and overall focus on making healthcare more accessible, reducing frequent hospital visits, improving patient compliance and outcomes and reducing costs has made healthcare providers as well as policy makers interested in virtual care and remote patient management. Therefore, this paper aims to delve into the recent trends in remote patient monitoring for HF patients and discuss their applications as well as limitations.



The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used to perform and report a systematic review of the literature.

Eligibility criteria

Studies were considered as acceptable for inclusion if they satisfied the following requirements: evaluated a program, technology or a combination of the two for home monitoring of Heart Failure patients, had more than 100 participants older than 18 years, and were published in the last 10 years. Review articles, letters, articles without full texts, non-English articles and conference abstracts were excluded from the scope of the review. The outcomes of interest ranged from validation, feasibility (e.g. user experience, acceptability, patient compliance, usability, device fidelity, etc.), patient outcomes, and clinical interventions/escalations, costs (cost-effectiveness, cost-benefit, cost-utility) and the identified gaps and limitations of the interventions.

Search Strategy

A systematic literature search was conducted on PubMed, with the last search run on 3rd July 2022. The references of the retrieved studies were also manually screened to identify any other rele vant studies. The search terms used on PubMed are as follows: "Home"[Title/Abstract] Failure"[Title/ Abstract] AND "Monitoring" [Title/Abstract]; and "Home"[Title/Abstract] AND "Cardiac" [Title/Abstract] [Title/Abstract]. The fo AND "Monitoring" llowing filters were also applied to get papers that met the inclusion criteria: ● ● ● Article Type: Randomised Controlled Trial, Clinical Trial Publication Date: Last 10 years Language: English All the hits received in the keyword search were checked for AND "Heart duplicates and consolidated in an excel file. The abstracts of individual references were independently screened against the inclusion and exclusion criteria. Studies that had fewer than 100 subjects were rejected. Full textreferences that articles of the matched the inclusion criteria were downloaded and read independently by the authors to determine eligibility (Fig. 2).

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