| dc.description.abstract | Ubuiquitous computing can be defined as information at anytime, anywhere and its grows as a reality on people‘s activities and daily tasks through the diversification and popularization of mobile devices and networks. So, it‘s important create models that allow not only share clinical data, but increase its quality, making it indifferent to technology and context aware. In this case, the present paper, called PEPContextual, is about a model that makes use of situation awareness, exploring environment related information and/or its own users, where several types of contexts are combined looking a richer, complex and smart visualization, creating several possibilities and, among that, the inferrence of associated risks to patients. The main contribution of this paper is related to make use of PHR data and situation awareness in order to inferrence symptoms and some diagnoses. The model was evaluated by two distinct ways: The first evaluation by case study has confirmed the proposal that situation awareness, based on Endsley model, makes possible that the model is capable to find associated risks through ubiquity; The second
evaluation measured the usability of the model, as the ease of use and utility where most of users had considered that inferrence information can help on daily treatments. | en |
