THE CONCEPT

THE RETENTION PROJECT

is an innovative platform supporting enhanced clinical monitoring and interventions aimed at improving the clinical management of patients with chronic Heart Failure, reducing their mortality and hospitalisation rates, and improving their quality of life, safety, and well-being

THE PLATFORM

The platform supports clinical decision making and evidenced based personalised interventions for HF patients by:
– Continuous monitoring of medical, clinical, physiological, behavioural, psychosocial, and real-world data for the patients
– Data analytics using innovative model-driven big data methods, statistical approaches, artificial intelligence and machine learning techniques.
– Patterns detection in the HF disease progression and the quality of life of patients
– Cross checking and validation against the clinical literature
– Applying transparent, explainable and verifiable decision making capabilities that leverage the evidence produced by the underlying data analysis and augment clinical studies targeting HF and, potentially, other CVDs

A Real World Data-Driven Approach

An Innovative Model based on Real World Data

from a variety of monitoring sources collected from Heart Failure patients daily life, Innovative model driven big data analytics, statistical, artificial intelligence and machine learning techniques are deployed to offer user friendly verifiable decision making capabilities regarding interventions and their effectiveness by generating new insights into disease patterns to continuously refine its patient management capabilities.

THE DIFFERENT TYPE
OF DATA

That RETENTION will collect and analyse include:
– standard demographic data (e.g., age, sex, marital status, home address, socio-economic status)
– medical history data
– data from baseline clinical testing relevant to the particular conditions and patients targeted by the project (e.g., N-terminal pro-B-type natriuretic peptide) and periodic patient clinical testing (electrocardiography/ECG, blood tests, cardio-pulmonary exercise testing)
– subjective patient assessments (depression and quality of life questionnaires)
– daily collected data including patient’s weight body fat, skeletal muscle and body water, blood pressure (excluding patients with VAD), heart rate, peripheral capillary oxygen saturation, deep and light sleep phases and sleep interruptions, fluid balance (intake/diuresis), adherence to prescribed medication, nutrition intake, circadian rhythm, physical activity data (steps, distance, floors climbed, calories burned).

The above data will be complemented and correlated

with Real World Data (RWD) derived from non-medical sources including:
– patient living space data (ambient light, temperature and humidity, indoor locations)
– patient living environment data (extreme temperatures and weather conditions, pollutants obtained from Copernicus services), and
– patient outdoor movement and location data and sunlight exposure.