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PSIP

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PATIENT SAFETY THROUGH INTELLIGENT PROCEDURES IN MEDICATION

Adverse Drug Events (ADE) due to product safety problems, and medication errors due to human factors (HF) are a major Public Health issue. They endanger the patients' safety and originate considerable extra hospital costs.Healthca... ver más

31/07/2011

RAILENIUM

10M€

Presupuesto del proyecto: 10M€

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RAILENIUM No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 9 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2011-07-31 No tenemos la información de la convocatoria

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9 Participantes

RAILENIUM

0.00€ | Lider

AAU

N.D. | Participante

UMIT TIROL

N.D. | Participante

VIDAL

N.D. | Participante

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Líder del proyecto

RAILENIUM No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 10M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Adverse Drug Events (ADE) due to product safety problems, and medication errors due to human factors (HF) are a major Public Health issue. They endanger the patients' safety and originate considerable extra hospital costs.Healthcare ICT applications should help reducing the prevalence of preventable ADE, by providing healthcare professionals and patients with relevant knowledge (guidelines, recommendations, etc.). But their efficiency is impeded by two major drawbacks:- lack of reliable knowledge about ADE- poor ability of ICT solutions to deliver contextualised knowledge focused on the problem at hand, aggravated by a poor consideration of causative HF.The objective of the project Patient Safety through Intelligent Procedures in Medication (PSIP) is (1) to facilitate the systematic production of epidemiological knowledge on ADE and (2) to ameliorate the entire medication cycle in a hospital environment.The first sub-objective, SO, is to innovatively produce knowledge on ADE: to know, as exactly as possible, per hospital, their number, type, consequences and causes, including HF. Data Mining of the structured hospital data bases, and Semantic Mining of Data Collections of free-texts (letters, reports), will give a list of observed ADEs, with frequencies and probabilities, thus giving a better understanding of potential risks.The second SO is to develop a set of innovative knowledge based on the mining results and to deliver a contextualised knowledge fitting the local risk parameters, in the form of alerts and decision support functions. This knowledge will be implemented in a PSIP-platform independently of existing ICT applications. These applications will connect to the platform to access and integrate the knowledge in their local system. The design and development cycle of the PSIP solution will be HF oriented.Dissemination plans will be developed taking into account other uses (medical devices, primary and tertiary Healthcare).

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