Abstract
Background: Heart Failure (HF) affects > 26 million people worldwide, with prevalence increasing due to ageing population. This additional burden on already overstretched healthcare resources, in staff and costs, is unsustainable. A change is warranted in how optimal healthcare is provided. Maximising patients’ self-care is mandatory, however current HF-eHealth products are ‘add-ons’ to standard care, and can result in minimal benefits to patients or healthcare professionals.
Aim: To co-design an e-Health product to maximise the self-care of patients with heart failure
Methods: The international PASSION-HF consortium, of which QUB is a partner, is developing an integrated eHealth-product enabling self-care and self-prescription of medication. It includes novel features such as a decision support engine of treatment algorithms based on international HF guidelines integrated with self-learning AI algorithms, feedback systems and affiliated comorbidities. An interactive physician avatar interface and serious gaming tools will stimulate and improve compliance. Qualitative interviews with patients and caregivers have been conducted, with data informing development. The PASSION-HF prototype is currently being pilot tested for acceptability and proof of concept.
Effects: Data from interview with patients with HF and their caregivers (n=82) identified three key themes: - Reassurance, Personalised and Transparency. The PASSION-HF next-generation eHealth product will enable personalised patient self-care. It will be easily accessible, providing support 24/7 with all decisions made available to the healthcare professional. Predicted results are a reduction of more than 70% of pressure on the health care system, nearly 50% less costs while improving patient care and potentially outcomes.
Aim: To co-design an e-Health product to maximise the self-care of patients with heart failure
Methods: The international PASSION-HF consortium, of which QUB is a partner, is developing an integrated eHealth-product enabling self-care and self-prescription of medication. It includes novel features such as a decision support engine of treatment algorithms based on international HF guidelines integrated with self-learning AI algorithms, feedback systems and affiliated comorbidities. An interactive physician avatar interface and serious gaming tools will stimulate and improve compliance. Qualitative interviews with patients and caregivers have been conducted, with data informing development. The PASSION-HF prototype is currently being pilot tested for acceptability and proof of concept.
Effects: Data from interview with patients with HF and their caregivers (n=82) identified three key themes: - Reassurance, Personalised and Transparency. The PASSION-HF next-generation eHealth product will enable personalised patient self-care. It will be easily accessible, providing support 24/7 with all decisions made available to the healthcare professional. Predicted results are a reduction of more than 70% of pressure on the health care system, nearly 50% less costs while improving patient care and potentially outcomes.
Original language | English |
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Publication status | Published - 05 Sep 2022 |
Event | British Society of Cardiovascular Research Conference - Queen's University Belfast, Belfast, United Kingdom Duration: 05 Sep 2022 → 06 Sep 2022 |
Conference
Conference | British Society of Cardiovascular Research Conference |
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Country/Territory | United Kingdom |
City | Belfast |
Period | 05/09/2022 → 06/09/2022 |