Heart failure algorithms for remote monitoring in people with cardiac implantable electronic devices

Reviewing current services

Patients with HF typically experience episodes of decompensation requiring admission to hospital. Early treatment of deteriorating HF with medications at home can stabilise their condition and avoid potentially preventable hospital admissions.

Current practice places responsibility on people to contact their HF team or seek medical attention when they experience worsening symptoms. However, people often experience symptoms too late, do not recognise the signs of worsening HF, or do not seek medical attention until their condition has reached a critical point.

Remote monitoring technologies offer a solution. Cardiac devices (cardiac resynchronisation therapy and implantable defibrillators) can detect pre-clinical signs of HF decompensation using an algorithm combining multiple physiological parameters (for example, thoracic impedance, heart rate and rhythm, and physical activity). If a significant change in health data is detected, the device can be programmed to send a HF alert to the clinical care teams, notifying them of people who are at high risk of hospitalisation in the next 30 days.

Despite good evidence of predictive value, previous clinical studies examining remote monitoring in HF proved ineffective, halting any change to guidance. However, these earlier studies used older technology and did not utilise algorithms.

Fast forward to 2016 and technology had moved on. Anecdotally we could see this data was clinically useful, predicting HF hospitalisations before the symptoms were present, but it was being ignored. People admitted to hospital with fulminant decompensated HF suffered long lengths of stay and poor outcomes. We identified a clear opportunity for improving patient care by actioning high-risk remote monitoring data (previously referred to as HF alerts), improving organisational efficiency by using a data-driven approach to divert resources to people at high risk, facilitating early specialist intervention, and avoiding potentially preventable hospitalisations.

Implementation

The TriageHF Plus clinical pathway, a pragmatic early warning system using device alerts to trigger clinical reviews, was developed in 2016 to combine HF alerts from cardiac devices with a structured phone-based assessment by a HF specialist, most often a nurse.

Devices capable of remote monitoring are programmed to send a HF alert to the hospital if a person's risk score crosses the 'high' threshold dictated by the TriageHF algorithm. Upon receiving a HF alert, the HF nurse contacts the patient to undertake a phone-based clinical assessment. Acute issues are identified and actioned and a management plan put in place, for example a change to medications. All people are additionally followed up after 30 days to assess the impact of the intervention.

The pathway was developed at Manchester Royal Infirmary, and a clinical study involving 3 Greater Manchester sites was launched in 2019. This was gradually expanded to include 6 sites by 2024. The TriageHF Plus study (NCT04177199) aimed to evaluate the clinical efficacy of the pathway and cost-effectiveness of its implementation. In 2024, we published our first set of results from phase 1, demonstrating a 58% reduction in hospitalisations compared with usual care. We submitted a cost-effectiveness report to the NICE Diagnostic Assessment Programme, which published its recommendation in October 2024 that TriageHF (and HeartLogic) are used "as options for algorithm-based remote monitoring in people with cardiac implantable electronic devices (CIEDs) who have heart failure". This new guidance allowed us to present our case to the local commissioning group to ensure long-term adoption of the pathway which is embedded into usual clinical care.