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Background: To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models. Methods: The holistic and evidence-based CEHRES Roadmap, used to create eHealth solutions through participator...
This article describes the procedure of definition and design of a process for the continuity care unit to improve the attention to the patient and his/her ecosystem providing a novel alternative to the conventional methods. This work was done under the framework of the MiniQ project, funded by EIT Health to improve the management of poly-medicated...
Background: Continuous glucose monitoring (CGM) devices measure interstitial glucose concentrations (normally every 5 minutes), allowing observation of glucose variability (GV) patterns during the whole day. This information could be used to improve prescription of treatments and of insulin dosages for people suffering diabetes. Previous efforts h...
Heuristic Evaluation (HE) is a well-known method for usability evaluation. HE allows the identification of the most generic and severe usability issues with a reduced effort and very quickly. This approach allows the quick iteration of prototypes and the update of the usability of the system before to run a usability study with the final users. Thi...
Type 2 Diabetes screening and risk stratification tools could benefit from the incorporation of predictive systems based on computer modelling. The adoption of User Centered Design techniques is fundamental in order to integrate these systems in an effective and successful way. The work presented in this paper describe the methodologies used in the...
The emerging of new Information and Communications Technologies (ICT), the aging population and the increased number of people suffering from chronic diseases are changing the health structure of developed countries. Given this situation, it is crucial that research based on demographics data is promoted and researchers can access large amounts of...
"Cancers of the Head and Neck Region (HNC) are the 6th more deadly cancers worldwide: in Europe ~150.000 new cases are detected and ~70.000 patients die every year. The main reasons for high mortality are the fact that the majority of cases are diagnosed in advanced Stage and the intrinsic heterogeneity of such tumors. At present the only adopted treatment decision method is based on TNM (Tumor-lymph-Nodes-Metastasis) prognostic system, that considers only a few risk factors such as smoking, alcohol abuse and more recently HPV. The TNM system is therefore inadequate to capture the patient-specific biomolecular characteristics of the tumor. HNC treatments can have hard impact on patient’s aesthetics and functionalities and, due to their toxicity, can cause severe morbidity and greatly deteriorate patient’s quality of life. A more precise prognostic prediction than the current TNM system is needed that allows implementing the first-line treatment that maximizes the therapeutic result and minimizes the impacts of therapy. BD2Decide DSS provides clinicians with the "means" and all the necessary information to tailor treatment and care delivery pathway to each and any HNC patient during their usual practice, in contrast to current “one-size-fits-all approach”. BD2Decide realizes and validates an Integrated Decision Support System that links population-specific epidemiology and behavioral data, patient-specific genomic, pathology, clinical and imaging data with big data techniques, multiscale prognostic models. Advanced graphical visualization tools are developed for prognostic data disclosure and patient co-participation to the selected treatment. BD2Decide will improve the clinical decision process, uncover new patient-specific patterns that can improve care, and create a virtuous circle of learning. A multicentric clinical study with more than 1.000 patients will be used to validate the system."