Carepaths was a EU project that aimed the formalization and deploymen on Clinical pathways in real healthcare scenarios. Our lab was in charge of the Intelligent systems that measure the models deviations by measuring the conformance of the models

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“An intelligent support environment to improve the quality of decision processes in health communities” (CAREPATHS) was a STREP project in the EU’s VI R&D Framework Programme in the area of Information and Health Societies (e-Health), of the IST Thematic Priority


This project was begun in October 2004 and lasted for 30 months. The objective was to create an operational environment which allowed effective decision making while attending patients. In this process, the concept of clinical pathways was implemented.

Clinical pathways are care plans applied to patients with a known diagnosis and a predictable clinical outcome. They define when, how, by who and in what sequence care or attention should be applied, as well as the objectives of each phase. They are a relatively new concept in the medical world, so that the appropriate computer programmes for their application have still not been created.

The idea is to standardise clinical processes and by the use of suitable information systems to design, implement and evaluate clinical pathways, and thus improve health care, efficiency and coordination among health personnel, so that patients will feel satisfied with the attention received.

The resulting system is divided into various functional modules: clinical pathways management, hospital systems connection, variations management, automatic document search, clinical pathways designer, cost analysis and the user management module.

Ten companies and organisations from France, Greece, Italy, Great Britain and Spain are taking part in the project and the work will be validated by the Azienda Ospedaliera of Parma and the Hospital Universitario La Fe of Valencia.

 Our lab contributed on the implementation of care processes and decision support systems and is in charge of developing the cost analysis and variation analysis module. For this task it is using techniques based on artificial intelligence and pattern recognition and will develop algorithms that will allow the different care pathways to be assessed and compared.