EU Awards 2,6 Million Euros for Patients with Chronic Cardiorenal Disease

To help patients manage their (potential) chronic heart and kidney disease, the European Commission has awarded 2,6 million euros to the CARRE project. A group of interdisciplinary researchers will compile personalised alerting, planning and educational services. This will empower patients, and both professionals and patients will be able to make shared informed decisions on the disease.

Cardiorenal syndrome is the condition characterised by simultaneous kidney and heart failure while the primarily failing organ may be either the heart or the kidney. Very often the dysfunction occurs when the failing organ precipitates the failure of the other.

Current studies estimate that 9-16% of the overall population is at risk or at the onset of chronic kidney disease, while chronic heart failure amounts to 1-2% of total healthcare costs and end-stage renal disease for more than 2% of total healthcare.

Challenging
Managing or even preventing this complex but common situation can be challenging: Comorbidities require care provision by different medical specialities while addressing a chronic patient trying to lead a normal life.

According to Robert Johnstone of the International Alliance of Patient Organizations there is a clear need for "patients to get up off their knees"!

Interlinked clinical information
To tackle this problem, the European Commission has decided to fund the CARRE project. This project will use internet aware sensors and other sources of medical information to provide dynamically interlinked clinical information personalized to the patient.

Patients and clinicians will be able to visualise, understand and interact with this linked knowledge via a set of decision support service in an all-inclusive and integrated approach the patient with (or at risk of) cardiorenal disease and comorbidities.

Partners
The CARRE consortium consists of 6 partners from 4 countries (Greece, United Kingdom, Lithuania and Poland) and is coordinated by the Democritus University of Thrace in Alexandroupoli, Greece.

The project is driven by two partners from the medical domain, namely the Democritus University of Thrace and the Vilnius University Hospital Santariškių Klinikos (LT), with a clear long experience in medical research in cardiorenal disease and comorbidities as well as with a long record of developing and deploying successful informatics interventions in the real healthcare setting.

The core semantic model and interlinking is performed by The Open University (UK) a leading expert in semantic technologies, while the University of Bedfordshire (UK) undertakes the work on visual analytics and cloud computing - both partners also contribute their long experience in semantic information extraction from unstructured data sources and web service oriented architectures.

Personal sensors
Kaunas University of Technology (LT), with a long proven innovation experience in personal sensors and sensor networks for cardiorenal disease tackles the integration of personalized sensor data. Finally, the Industrial Research Institute for Automation and Measurements (PL), an established partner in security and automation systems, brings in the required expertise on decision support systems and on systems security and data privacy.

The overall aim of the CARRE project is to show the potential of semantic interlinking of heterogeneous data to construct dynamic personalized models of complex comorbid medical conditions with disease progression pathways and comorbidity trajectories. Also, to show that visual analytics based on such models can support patient understanding of personal complex conditions (projected against ground knowledge and statistical views of similar patient population) and be the basis for shared decision support services for the management of comorbidities.

Freely available
All CARRE outcomes will be available as open source, protected under Creative Commons or GNU-GPL and other similar appropriate licensing schemes. CARRE project outcomes will thus be freely available for use and re-use by any interested party. Proof-of-concept will be shown via deployment and evaluation in two different healthcare settings.

The CARRE project is expected to reinforce the cardiorenal patients' understanding of the disease and the complex interdependencies of existing or projected comorbidities, supporting personalized treatment stratification, monitoring alerts, education and shared informed decision making.

Through these outcomes, CARRE strengthens the EU resolution to put the chronic patient at the center.

For further information, please visit:
http://www.carre-project.eu

About CARRE project
The CARRE project investigates information and communication technologies for empowering patients with comorbidities (multiple co-occurring medical conditions), or persons with increased risk of such conditions, especially in the case of chronic cardiac and renal disease patients. The CARRE project has received a 3-year EC funding from the European Community 7th Framework Programme FP7-ICT-2013 work programme under grant agreement no. 611140.

Most Popular Now

ChatGPT can Produce Medical Record Notes…

The AI model ChatGPT can write administrative medical notes up to ten times faster than doctors without compromising quality. This is according to a new study conducted by researchers at...

Alcidion and Novari Health Forge Strateg…

Alcidion Group Limited, a leading provider of FHIR-native patient flow solutions for healthcare, and Novari Health, a market leader in waitlist management and referral management technologies, have joined forces to...

Greater Manchester Reaches New Milestone…

Radiologists and radiographers at Northern Care Alliance NHS Foundation Trust have become the first in Greater Manchester to use the Sectra picture archiving and communication system (PACS) to report on...

Can Language Models Read the Genome? Thi…

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code. That code...

Study Shows Human Medical Professionals …

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations...

Advancing Drug Discovery with AI: Introd…

A transformative study published in Health Data Science, a Science Partner Journal, introduces a groundbreaking end-to-end deep learning framework, known as Knowledge-Empowered Drug Discovery (KEDD), aimed at revolutionizing the field...

Bayer and Google Cloud to Accelerate Dev…

Bayer and Google Cloud announced a collaboration on the development of artificial intelligence (AI) solutions to support radiologists and ultimately better serve patients. As part of the collaboration, Bayer will...

Shared Digital NHS Prescribing Record co…

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed...

Ask Chat GPT about Your Radiation Oncolo…

Cancer patients about to undergo radiation oncology treatment have lots of questions. Could ChatGPT be the best way to get answers? A new Northwestern Medicine study tested a specially designed ChatGPT...

Wanted: Young Talents. DMEA Sparks Bring…

9 - 11 April 2024, Berlin, Germany. The digital health industry urgently needs skilled workers, which is why DMEA sparks focuses on careers, jobs and supporting young people. Against the backdrop of...

North West Anglia Works with Clinisys to…

North West Anglia NHS Foundation Trust has replaced two, legacy laboratory information systems with a single instance of Clinisys WinPath. The trust, which serves a catchment of 800,000 patients in North...

Can AI Techniques Help Clinicians Assess…

Investigators have applied artificial intelligence (AI) techniques to gait analyses and medical records data to provide insights about individuals with leg fractures and aspects of their recovery. The study, published in...