Project description
An innovative platform for accurate, effective and exploitable monitoring of heart failure patients
Heart failure (HF) is one of the chronic diseases that medicine struggles to effectively prevent, diagnose and treat. Yet, it remains the leading global cause for disability and premature death. A significant reduction of hospitalisations is a crucial step for the maintenance of patients' life quality as well as for its burdening impact on the entire healthcare system's efficiency. The EU-funded RETENTION project aims to develop an innovative platform supporting clinical decision-making and evidenced-based personalised interventions for HF patients. Through an automatised collection and analysis of patient data, the innovative solution will focus on reducing patients' mortality and enhancing their quality of life.
Objective
Heart failure (HF) is a prominent chronic disease, despite efforts in improving its prevention, diagnosis and treatment, represents the leading cause of disability and premature death throughout the world, while being is a heavy burden on health systems due to the multiple, prolonged hospitalizations required for patients suffering from it and the related management costs. Nevertheless, studies have shown that routine patient-physician or patient-nurse communication following discharge can result in significant reduction of hospitalizations. The pertinent collected patient data may include simple yet important information (e.g. patient weight), as well as previously difficult to obtain information such as routine ECG, ICD/CRT-D interrogation and pulmonary arterial pressure monitoring, which are now within reach due to technological progress. Motivated by the above, RETENTION aims to develop and deliver an innovative platform supporting enhanced clinical monitoring and interventions aimed at improving the clinical management of patients with chronic HF, reducing their mortality and hospitalisation rates, and improving their quality of life, safety, and well-being. The RETENTION platform will support clinical decision making and evidenced based personalised interventions for HF patients by: (a) continually monitoring and collecting medical, clinical, physiological, behavioural, psychosocial, and real-world data for such patients, (b) analysing these data using innovative model-driven big data analytics, statistical, artificial intelligence and machine learning techniques, (c) detecting patterns in the HF disease progression and the quality of life of patients, (d) cross checking and validating them against the clinical literature, and (e) offering transparent, explainable and verifiable decision making capabilities that leverage the evidence produced by the underlying data analysis and augment clinical studies targeting HF and other CVDs.
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Funding Scheme
RIA - Research and Innovation actionCoordinator
106 82 ATHINA
Greece