Heart failure (HF) is a progressive disease that is associated with repeated exacerbations and hospitalizations. The rapid increase in the number of HF patients is a global health problem now referred as the "heart failure pandemic". Despite remarkable advances in drug therapy for HF, the residual HF-related morbidity, mortality and hospitalizations remain substantial, and significant proportions of patients with HF remain symptomatic despite optimal best tolerated drug therapy. In particular, there remain significant unmet clinical needs in patients with moderate to severe HF (Stage C and D).
Novel device-based interventions have emerged as a potential therapy for various phenotypes of HF. The concept of interventional heart failure (IHF) considers heart recovery and prevention of worsening of heart failure via multidisciplinary treatment using surgical, catheter interventions, and mechanical circulatory support devices. There are 3 major phases, namely 1) Life-saving intervention in acute cardiogenic shock, 2) intervention for the underlying aetiology and pathophysiology of heart failure and 3) bridging therapy mainly with hemodynamic support for patients with end-stage heart failure who are transitioning to an implantable left ventricular assist device (LVAD) or waiting for cardiac transplantation.
Telemedicine is potentially a way of escalating HF multidisciplinary integrated care. Many HF patients' stages of instability could be avoided if their follow-ups were improved both in the vulnerable post-hospital discharge phase and in the medium and long term phases. The widespread adoption of mobile technologies offers an opportunity for a new approach to post-discharge care patients. By enabling remote monitoring and two-way real time communication between the clinic and home-based patients, as well as a host of other capabilities, mobile technologies have a potential to significantly improve remote patient care and outcomes.
Given the increased amount of data generated by virtual healthcare technologies, artificial intelligence (AI) is being investigated as a tool to aid decision making in the context of primary diagnostics, identifying disease phenotypes and predicting treatment outcomes for HF. Opportunities of telemedicine application in HF patients should be explored and adopted. There is a need for evidence-based integration in the workflow of HF management. Support for patients and clinicians wishing to use these technologies is important, along with consideration of data validity and privacy and appropriate recording of decision-making.
