MobiGuide: Guiding Patients Anytime Everywhere
Research project in the area of Media Processing.
Keywords: clinical Decision-Support Systems, Computer-Interpretable Guidelines, Body Area Networks, Personalized Medicine, Information Visualization, Personal Health Record, Monitoring Devices, Visual Analytics.
About this Project
MobiGuide (MG) will develop a patient guidance system that integrates hospital and monitoring data into a Personal Health Record (PHR) accessible by patients and care providers and provide personalized secure clinical-guideline-based guidance also outside clinical environments. MG's ubiquity will be achieved by having a Decision Support System (DSS) at the back end, and on the front end by utilizing Body Area Network (BAN) technology and developing a coordinated light-weight DSS that can operate independently. Personalization will be achieved by considering patient preferences and context. Retrospective data analysis will be used to assess compliance and to indicate care pathways shown to be beneficial for certain patient context. MG will be validated on pre-selected clinical domains with intensive vs. sparse monitoring to demonstrate the generality of the design and assess functionality, feasibility, and impact. MG addresses EU priorities: increasing patient safety, ubiquitous secure access to health care, patient empowerment, developing a common platform for healthcare services, and competitiveness of Europe. The time is right for MG in view of Europe's vast interest in national PHRs and patient empowerment. MG will leverage this momentum to create a solution that goes beyond local proprietary and stand-alone EMR, DSS, and BAN. Our team includes complementary partners with diverse experience in: patient guideline-based DSS, focusing on reasoning with patient guideline intentions and temporal patterns, decision-theoretic models, knowledge-data integration, and information visualization Health BAN, telemedicine data analysis for diabetes, telemedicine applications for cardiology and expertise in large system integration to create the secure PHR.
Funding provided by