Remote monitoring has become an integral component of heart failure (HF) management, aiming to reduce rehospitalizations and improve chronic disease control. Early telemonitoring trials such as Tele-HF (Telemonitoring to Improve Heart Failure Outcomes), TIM-HF (Telemedical Interventional Monitoring in Heart Failure), and TIM-HF2 (Telemedical Interventional Management in Heart Failure 2) predominantly enrolled relatively younger and less frail populations, limiting the generalizability of their findings to very old adults with multimorbidity and geriatric syndromes. More recent large-scale real-world programs, such as TELESAT-HF, have demonstrated heterogeneous but clinically meaningful results, strongly influenced by program structure, patient selection, and response workflows [1-3].

Much of the evidence base and many telemonitoring workflows were initially developed and validated in populations that were younger and less frail. In parallel, several studies have shown that a substantial proportion of older adults experience “telemedicine unreadiness,” driven by cognitive impairment, sensory limitations, and reduced digital literacy [4-6]. Together, these observations suggest that existing telemonitoring models may not be fully aligned with the characteristics and needs of very old and frail populations, in whom HF is closely intertwined with multimorbidity, functional decline, and dependency.

Frailty is a well-established clinical construct reflecting reduced physiological reserve and increased vulnerability to stressors. Seminal work by Fried et al [7] and Rockwood et al [8] defined frailty as a measurable and clinically meaningful condition, later expanded by Clegg et al [9] as a major determinant of health outcomes at the population level. In HF, frailty has been consistently associated with higher risks of hospitalization, disability, and mortality, often outperforming traditional cardiac markers in prognostic accuracy among older adults [10-13]. At the same time, the global burden of HF continues to rise with population aging [14]. However, frailty remains largely absent from the design of most telemonitoring strategies, including patient selection, alert thresholds, and care pathways.

Although several studies have shown that older adults can successfully engage in telemonitoring when appropriately supported [4-6], adherence, comprehension, and responsiveness vary substantially according to frailty level.

This viewpoint argues that frailty should be considered a primary determinant of remote monitoring design in older adults with HF, rather than a secondary modifier. We propose a structured frailty-adaptive framework based on 4 major clinical trajectories—robust, prefrail, frail, and palliative—each associated with distinct monitoring objectives, clinical responses, and organizational requirements.

By reframing remote monitoring as a stratified, patient-centered strategy rather than a purely technological intervention, this approach aims to improve clinical relevance, optimize resource allocation, and promote digital health equity. Integrating frailty into telemonitoring design is essential to ensure that digital interventions remain accessible, effective, and safe across the full spectrum of aging and vulnerability.

The proposed framework defines 4 distinct frailty-based trajectories—robust, prefrail, frail, and palliative—each associated with specific monitoring objectives, workflow adaptations, and clinical responses.

Figure 1 provides a schematic overview of the frailty-adaptive telemonitoring framework, illustrating how patient stratification translates into differentiated monitoring strategies and care pathways.

Table 1 provides a structured overview of how remote-monitoring strategies can be aligned with frailty status to optimize clinical relevance, feasibility, and resource allocation.

Robust older adults, characterized by preserved mobility, intact cognition, and low comorbidity burden, are the population most closely represented in early telemonitoring trials. In this group, remote monitoring primarily supports optimization of HF management, including early detection of congestion, reinforcement of adherence, lifestyle optimization, and guideline-directed medical therapy titration.

Evidence from trials such as Tele-HF, TIM-HF, TIM-HF2, and MORE-CARE, as well as meta-analyses, suggests that benefits in this population depend on program responsiveness and integration into multidisciplinary HF care [2,3,18,19].

Patients typically perform self-reporting independently, with high adherence and stable engagement. In this context, telemonitoring functions as a preventive strategy aimed at maintaining clinical and functional stability.

Prefrail individuals represent a transitional stage characterized by early vulnerability, including mild sarcopenia, reduced gait speed, fatigue, or early cognitive changes.

In this trajectory, the primary role of remote monitoring is the early detection of subtle clinical or functional deterioration. Changes in symptom patterns—such as increased fatigue, reduced activity tolerance, progressive dyspnea for similar exertion, or reduced ability to complete questionnaires independently—may signal early decompensation or loss of functional reserve. Increased caregiver involvement or delayed responses to alerts may also reflect declining autonomy.

Although direct evidence that telemonitoring prevents transition to frailty is lacking, early detection of clinical deterioration and timely intervention may contribute to preserving functional status and reducing hospitalization risk. This supports a model of slightly intensified monitoring, simplified alert systems, and closer coordination with primary care, nursing teams, and caregivers.

In frail older adults, HF is embedded within multimorbidity, polypharmacy, cognitive impairment, and functional dependency. These patients experience frequent exacerbations, high hospitalization rates, and reduced ability to engage independently in self-monitoring. Frailty has been consistently identified as a major predictor of hospitalization and mortality in populations with HF [11-13,17,20].

In this group, the effectiveness of telemonitoring depends less on patient digital capacity than on organizational structure. Proxy-assisted reporting by caregivers or health care professionals is common and enables continued participation despite functional limitations [4-6,21,22].

Remote monitoring therefore operates as a stabilization tool within an integrated care pathway. Key components include nurse-led triage, structured clinical verification of alerts, and rapid access to in-person reassessment. Typical interventions include intravenous diuretics, iron repletion, medication adjustment, and comprehensive geriatric assessment. Integrated cardiogeriatric models have demonstrated improved symptom control and reduced hospital utilization in this population [12,22,23].

The primary objective in this trajectory is crisis avoidance through early intervention and rapid care escalation rather than patient-driven self-management.

Patients in the palliative trajectory typically present with advanced HF, severe frailty, refractory symptoms, and limited life expectancy. Many express a preference to avoid hospitalization and remain at home. However, in practice, a large proportion still die in hospital, often following acute decompensation events [24,25].

When adapted to patient goals, remote monitoring may support symptom-guided care, early identification of distress, and avoidance of unnecessary emergency department visits. Monitoring strategies in this group are simplified and often rely on caregiver-driven reporting, with alert systems focused on symptom burden rather than disease optimization.

Evidence from palliative telehealth and home-based HF care suggests that such approaches can improve symptom control, reduce acute care use, and support home-based end-of-life care [26-28]. In this trajectory, remote monitoring shifts from disease management to a supportive role aimed at maintaining comfort and enabling care aligned with patient preferences.

These four trajectories illustrate how remote monitoring can be operationalized as a stratified, frailty-responsive care strategy rather than a uniform digital intervention.