RETENTION | heaRt failurE paTient managEment and iNTerventIOns usiNg continuous patient monitoring outside hospitals and real world data

Summary
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. The RETENTION approach and it
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/965343
Start date: 01-05-2021
End date: 30-04-2025
Total budget - Public funding: 5 983 244,00 Euro - 5 983 243,00 Euro
Cordis data

Original description

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.

Status

SIGNED

Call topic

SC1-DTH-12-2020

Update Date

26-10-2022
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Horizon 2020
H2020-EU.3. SOCIETAL CHALLENGES
H2020-EU.3.1. SOCIETAL CHALLENGES - Health, demographic change and well-being
H2020-EU.3.1.0. Cross-cutting call topics
H2020-SC1-2020-Single-Stage-RTD
SC1-DTH-12-2020 Use of Real-World Data to advance research on the management of complex chronic conditions