![]() ![]() ![]() The objective is to harvest large volumes of data that we could use as raw materials for analyzing health care patterns and outcomes. “Data Farming” is a realistic and functional conceptualization for shaping expectations of the type of work and commitment needed to construct reliable databases supporting practice quality improvement and clinical translational research. To reach that goal we have to overcome technical, cultural, and clinical process barriers. It should be the rule rather than the exception, that we seamlessly use this information about past experience to help today’s patients. We enter a wealth of information into electronic health records (EHR) and radiation oncology information systems (ROIS) on a daily basis. It should be common for clinics to have the ability to rapidly assemble datasets to address practice quality improvement (PQI), routine clinical translational research (CTR), and other arising questions to aid patients in our clinics today. Set new and durable standards for cardiovascular big-data science for the next decades.Transforming radiation therapy through "big data" analytics.Ensure proper, wide dissemination of the framework and project results, to maximise impact and speed at which the results will be broadly implemented in the EU, and so that they may serve as a template or inspiration for the rest of the world.Involve all relevant stakeholders (including policymakers and insurers) to ensure full support for this new framework.Leverage unique database access and big data science expertise to validate (and tweak) the novel frameworks through a number of pilot studies with high and immediate social relevance. ![]() Create novel frameworks for disease definitions based on up-to-date scientific evidence.Develop and expand on this distributed data for further analysis.Create systems to leverage existing state-of-the-art solutions from different sources to enable combination for high-power identification, harmonisation, access and analysis of distributed data.Create a responsive and agile research framework to address the objectives.Assemble an unparalleled array of big-data sets.Ultimate goal is to develop a Big Data-driven translational research platform of unparalleled scale and phenotypic resolution in order to deliver clinically relevant disease phenotypes, scalable insights from real-world evidence and insights driving drug development and personalised medicine through advanced analytics. ![]()
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