This is a Research and development project funded by the European Commission under Framework Programme 7 – ICT-2007.5.2: Advanced ICT for Risk Assessment and Patient Safety
The European Commission describes:
“Knowledge lies at the heart of the European Union’s Lisbon Strategy to become the “most dynamic competitive knowledge-based economy in the world”. The ‘knowledge triangle’ – research, education and innovation – is a core factor in European efforts to meet the ambitious Lisbon goals. Numerous programmes, initiatives and support measures are carried out at EU level in support of knowledge. The Seventh Framework Programme (FP7) bundles all research-related EU initiatives together under a common roof playing a crucial role in reaching the goals of growth, competitiveness and employment.”
The Background
Intensive Care patients can experience Adverse Events associated with sudden episodes of low blood pressure. These Adverse Events may impact all of the main organs resulting in longer lengths of stay, increased care costs and reducing quality of outcomes. Existing technologies enable to clinicians to know when these events have occurred and treat the effects.
Medical techniques for avoiding Adverse Events currently exist, but clinicians don’t have a reliable way to predict the occurrence, so there’s no opportunity for intervention.
Research indicates average lengths of stay can be reduced by up to 30%, and outcomes improved for a similar proportion of patients, if these Adverse Events can be avoided through prediction and intervention. Potential savings across the EU exceed 5 billion euros, annually.
A model for predicting Adverse Events offers potential for improving outcomes across a wide range of conditions and or illnesses.
The Objectives
The main objectives of the project are
- Understanding the association between multiple patient parameters and arterial hypotension (sudden drop in blood pressure).
- Development of a software application to predict the occurrence of arterial hypotension based on recognition of the associations described above
- Validation of the solution in clinical trials
- Exploitation model for the commercialisation of the software in product/service sales across international markets
The Resources
The main research will focus on combining resources:
- Historic patient care data from 22 specialist brain injury units across Europe
- Grid technologies for secure data access across multiple specialist units and hospitals
- Baysian Artificial Neural Network (BANN) techniques for analysing data
- Specialists in treating TBI from 6 leading hospitals, in Sweden, Germany, Italy, Spain, Lithuania and Scotland
- C3 Amulet’s expertise in device monitoring, data analysis and reporting, and software development, distribution and support
The Outputs
C3 Amulet has exclusive access to the results of the research for commercial exploitation in products and services. Potential opportunities for that exploitation include
- Monitoring of Intensive Care Patient treatment
- Clinical trials of both drugs and medical devices
- BANN techniques for asset performance management and environmental monitoring and control
Consortium Members
Pera Innovation Ltd,
Uppsala Universitet,
Universitätsklinikum Heidelberg,
Azienda Ospedaleria San Gerardo Di Monza,
Kauno Technologijos Universitetas,
The University Of Glasgow,
Greater Glasgow Health Board,
Hospital Universitari Vall d’Hebron,
