The principal findings from the present study show that the mTelehealth RPM Kit is a feasible and highly acceptable platform with which to monitor modifiable risk factors in HCT survivors at risk for CVD. The mean weekly compliance rate was ≥80%, and at least two-thirds of the participants successfully performed ≥3 readings per week using all devices for 4 consecutive weeks. In fact, the majority of participants provided more than the requested readings, resulting in some compliance rates theoretically above 100%. The BP monitor was used slightly more than other devices. Considering that 67% of the participants had hypertension, the BP data might have been of increased interest to the study population. A major challenge in previous telehealth studies is a “honeymoon period” of high use, followed by a steep dropoff [13]. Even though our study lasted only 1 month, we were still surprised to find no dropoff. Moreover, the compliance rate increased after the first week. This may be explained by an initial learning curve followed by increasing confidence and motivation and greater levels of self-efficacy. Self-efficacy, a confidence in the ability to perform specific tasks or behaviors, which in turn influences the willingness to perform them, is considered an important driver of sustained behavioral change [11]. This may be especially relevant to our older population (age 53 to 74 years), who might not be as technologically proficient as a younger cohort.

More than 85% of participants agreed that the study allowed them to be more active in managing their health and kept them motivated and involved in their health care. According to the nurse’s log, 1 participant agreed to bring his study blood glucose readings to his physician, and another participant confirmed that he would find a dietician after consistently elevated blood glucose readings. All participants were glad they participated in the study and felt comfortable taking their own readings. It is important to note that for the present study, a nurse reviewed all patient-generated data and followed up on any readings that exceeded established thresholds. This “feedback loop” between a patient and a health care provider has been shown to improve the health status in chronically ill individuals [14]. It reinforces key messages and can encourage follow-up actions. For instance, the study nurse answered dietary concerns for 1 participant and encouraged him to meet with a dietician. Another participant was reminded to rest before taking her BP, teaching the importance of proper BP technique. Multiple participants were asked to take their home medications and then remeasure their BP, reinforcing the link between medication adherence and improved BP. Ideally, participants can then make these necessary adjustments independently in the future. As individuals become increasingly engaged in their care, the patient-provider relationship can evolve into one of improved collaboration.

It is noteworthy that the majority of alerts generated by the RPM platform were not actionable. That said, there was minimal alert burden on the monitoring provider, given that 73% of the alerts self-corrected and only 27% required follow-up calls by the study management and nursing team. Certain participants triggered regular alerts because of preestablished study thresholds; for example, 3 of the 4 participants with diabetes were on corticosteroid therapy. Their blood glucose levels were outside the fixed threshold but were appropriate for their current treatment. Another participant had weight fluctuations that were nonpathological. For this study, the thresholds were based on best practice values; future efforts would benefit from individualization of these thresholds. Interestingly, there was marked discrepancy in all 9 patients who had home and clinic BP readings on the same day, with the clinic readings often higher than the home average readings. It is widely recognized that clinic BP measurements can be misleading in a considerable portion of individuals, owing to a phenomenon known as “white coat hypertension,” in which BP can be elevated in the clinical setting, or to an opposite effect, known as “masked hypertension” 15, 16, 17, 18. Therefore, out-of-clinic BP monitoring may therefore be necessary to provide accurate information on steady-state BP readings [19]. Home BP monitoring has been shown to lead to better BP control, better compliance with antihypertensive therapy [20], and improved health-seeking behaviors 21, 22, 23. Since clinic time provides only a brief snapshot of the HCT survivors’ health care journey, longitudinal data from their home environment may provide a more comprehensive and holistic perspective. The current RPM strategy allows for more accurate projections of survivors’ physiological health, setting the stage for more comprehensive management of modifiable risk factors.

The primary limitations of our study are its small sample size and short study duration, which may limit the generalizability of our findings. A further limitation is that our findings are specific to the mTelehealth RPM platform and might not apply to all RPM technology. Importantly, home-based monitoring may need to be routinely validated with in-person clinic assessments, allowing healthcare providers to reinforce proper measurement techniques and to limit the likelihood of erroneous remote readings over time. Finally, it is important to note that RPM entails upfront costs and might not be feasible for all clinical settings in which HCT survivors are routinely seen. That said, these initial costs may be offset by the reduction of in-person clinic visits and complications associated with these risk factors, including CVD. Additional studies are needed to evaluate the cost-effectiveness and impact on patient outcomes using RPM and telemedicine in this population.

In conclusion, this study provides important information regarding the feasibility and acceptability of implementing a telehealth platform to monitor CV risk factors in HCT survivors at risk for CVD. Our preliminary findings may facilitate the development of population-based CVD interventions in large cohorts of survivors at a fraction of the cost and resources necessary to deliver preventive and long-term survivorship care. Importantly, it may set the stage for innovative delivery of care that encourages patients to be active participants in their health and reduces the burden of CVD in this growing population of patients. This paradigm of health care delivery could also be applied in acute care settings (eg, postoperative, outpatient HCT) across a range of scenarios for patients undergoing HCT and in long-term survivors.