A pervasive approach to a real-time intelligent decision support system in intensive medicine

The decision on the most appropriate procedure to provide to the patients the best healthcare possible is a critical and complex task in Intensive Care Units (ICU). Clinical Decision Support Systems (CDSS) should deal with huge amounts of data and online monitoring, analyzing numerous parameters and providing outputs in a short real-time. Although the advances attained in this area of knowledge new challenges should be taken into account in future CDSS developments, principally in ICUs environments. The next generation of CDSS will be pervasive and ubiquitous providing the doctors with the appropriate services and information in order to support decisions regardless the time or the local where they are. Consequently new requirements arise namely the privacy of data and the security in data access. This paper will present a pervasive perspective of the decision making process in the context of INTCare system, an intelligent decision support system for intensive medicine. Three scenarios are explored using data mining models continuously assessed and optimized. Some preliminary results are depicted and discussed.Fundação para a Ciência e a Tecnologia (FCT

Enabling ubiquitous data mining in intensive care: Features selection and data pre-processing

Ubiquitous Data Mining and Intelligent Decision Support Systems are gaining interest by both computer science researchers and intensive care doctors. Previous work contributed with Data Mining models to predict organ failure and outcome of patients in order to support and guide the clinical decision based on the notion of critical events and the data collected from monitors in real-time. This paper addresses the study of the impact of the Modified Early Warning Score, a simple physiological score that may allow improvements in the quality and safety of management provided to surgical ward patients, in the prediction sensibility. The feature selection and data pre-processing are also detailed. Results show that for some variables associated to this score the impact is minimal.Fundação para a Ciência e a Tecnologia (FCT

An intelligent information forwarder for healthcare big data systems with distributed wearable sensors

© 2016 IEEE. An increasing number of the elderly population wish to live an independent lifestyle, rather than rely on intrusive care programmes. A big data solution is presented using wearable sensors capable of carrying out continuous monitoring of the elderly, alerting the relevant caregivers when necessary and forwarding pertinent information to a big data system for analysis. A challenge for such a solution is the development of context-awareness through the multidimensional, dynamic and nonlinear sensor readings that have a weak correlation with observable human behaviours and health conditions. To address this challenge, a wearable sensor system with an intelligent data forwarder is discussed in this paper. The forwarder adopts a Hidden Markov Model for human behaviour recognition. Locality sensitive hashing is proposed as an efficient mechanism to learn sensor patterns. A prototype solution is implemented to monitor health conditions of dispersed users. It is shown that the intelligent forwarders can provide the remote sensors with context-awareness. They transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage. The system functions unobtrusively, whilst giving the users peace of mind in the knowledge that their safety is being monitored and analysed

Patient-centered care process enabled by Integrative Social Media Platform in an outpatient setting

As an effort to guide patients toward being more informed and more involved as healthcare decision makers in the clinical processes, health care organizations have adopted a new technology referred to as an integrative social media platform (ISMP). This ISMP combines features of mobile technology and those of social media technology, integrating healthcare systems in order to support a more patient-centered healthcare process. However, users, both physicians and patients, have showed varied usages of ISMP, as a results, have shown mixed results of ISMP. To provide a better understanding of the use of ISMP, especially the interaction between patients and physicians, I turned to the concept of affordances. Affordances describe the possibilities for goal-oriented actions that a technical object offers to a user. Using a mixed-method approach with real archival event log data, conversation texts, documents, interview, and focus-group data from a large hospital which had adopted an ISMP, I confirmed three types of affordance: perceived affordance, behavioral affordance, and interactive affordance. I identified two key affordances of ISMP that lead to patient-centered care, namely ubiquitous access and virtual healthcare consultation, which represent a behavioral affordance and an interactive affordance, respectively. I also explored how different types of affordances are actualized and how they interact with each other to contribute to patient-centered care