Objective
The threat of mass casualty incidents or medical surges to healthcare systems has always been present. Preparing essential parts of the healthcare system such as hospitals and their partners to prevent, respond, and rapidly recover from these threats is critical for protecting and securing the entire health infrastructure. Large-scale disaster situations causing mass casualty incidents are characterised by large numbers of same-type injuries which require immediate and simultaneous medical intervention and means of support such as ambulances, surgeries, specialists, diagnostic equipment and others.
These characteristics underline the need for enhanced communication between medical institutions and other organisations involved in disaster management. At the same time, the surge of demand for services to patients points to the need for better organisation within hospitals concerning the deployment of specialists and the availability of medical supplies, transportation, rooms and equipment.
While a variety of incidents may necessitate an emergency response, different types of such incidents (natural disasters, explosions, humanitarian crises and others) mean a different framework for responders. While health responders are ubiquitous in their involvement with the response to an emergency situation, the parameters regarding how they are involved greatly differ with the type of threat represented.
The COncORDE project will develop a Decision Support System (DSS) to improve preparedness and interoperability of medical services during an emergency which affects the health of the population at local, regional or cross-border level. The project will incorporate existing operational assets related to security, trust and infrastructure and leverage them within the DSS.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Call for proposal
FP7-SEC-2013-1
See other projects for this call
Funding Scheme
CP-FP - Small or medium-scale focused research projectCoordinator
CB2 0QQ Cambridge
United Kingdom
See on map
Participants (15)
15125 Marousi Athina
See on map
4450-309 Matosinhos
See on map
34450 Istanbul
See on map
1678 Nicosia
See on map
542 48 THESSALONIKI
See on map
3927CN RENSWOUDE
See on map
013685 BUCURESTI
See on map
2411 ELVERUM
See on map
02150 Espoo
See on map
Participation ended
02044 VTT ESPOO
See on map
15341 Agia Paraskevi
See on map
A91 RW26 DUNDALK CO LOUTH
See on map
1000 Bruxelles / Brussel
See on map
1990-506 LISBOA
See on map
Participation ended
WC1N 2PH LONDON
See on map