Improvement of Patient Safety:
The project will demonstrate that the (continuous, real-time) secondary use of large amounts of clinical data can become a key base to improve direct patient care in hospital as well as in ambulatory settings, and indirectly also the quality of healthcare systems through better monitoring of diseases and also of the quality of care provided. This will be of great benefit for all European citizens.
Implementation of a European wide examplary healthcare support system:
The project will use existing, over the project life time developing and, where needed, own specifications and standards, ontologies and information models to implement a European wide decision and healthcare support system for case-based and population-based issues related to patient safety, risk management and better quality of care. The scope is limited to infectious diseases to render it feasible to undertake such an endeavour, both in terms of size of the medical domain, and in terms of time and validation, noting that most infectious diseases have fast onset and outcomes.
For the first time it will provide a pan-European, exemplary interoperability platform to establish a clinical data repository, which will be adaptable to many other conditions or prevention related issues.
Perhaps the key longer-term outcome will be the envisaged installation and maintenance of the system not only by the participating partners, their associated hospitals and clients, or in the case of industrial actors their present and future clientele. It might be also at the European and even global level by making the overall system to be developed available via the European Centre for Disease Prevention and Control (ECDC) in Stockholm. Here, initial contacts have already been established, but the ECDC is not permitted to participate in EU-sponsored projects. It could be at WHO level, respectively one of its collaborating centres. National Authorities or an Open Source solution will be others options to be investigated.
Implementation of knowledge tools and Decision Support Systems for Medicine:Through the knowledge tools and decision support system (DSS) medical practice dealing with infectious diseases and antibiotics will greatly benefit from improved service delivery.
Furthermore, this project will setup the theoretical foundation base for large clinical research projects based on the secondary usage of raw clinical data integrated across many health services actors in several countries, data which are not generated by very expensive randomized clinical trials, but become more and more available as organisation-centred, local, regional and national EHR systems diffuse across Europe. The scientific framework will allow these data to be matched to existing ontologies within information models that can be contextualised to the domain of interest.
Public health will benefit form faster, even up-to-date surveillance and control information.
Cost saving and service efficiency:Reducing the length of treatment, the avoidance of complications and crises, and/or fewer adverse events by improving the adequacy of antibiotics therapy to the pathogens' profile and improved workflow processes will lead to considerable direct (such as use of drugs, need for infusions) and indirect (such as promoting resistances) cost savings that have proven to have important economical impact.
The empirical evidence to be collected will underpin these expected outcomes.
Health Information Technology Science:This project will produce:
- ontology of harm patterns in infectious diseases expressed as an OWL file
- a description framework to characterize the quality, reliability, accessibility of data and data sources to improve secondary usage of raw clinical data;
- a platform containing mapping tools to collect data from heterogeneous clinical data sources
- a flexible information model based on archetypes and using existing standards, adapted to support, in addition to usual clinical data, information about pathogens, workflows and contexts
- robust new knowledge-driven multimodal data mining techniques suited to analyze raw data coming from the clinical world
- a common, extensible and shareable knowledge repository about infectious diseases
For eHealth Industries:
- new tools and software for decision support implementable in numerous CIS that will improve quality of care
- a base from which to develop systems for other disease fields.