Towards a situation awareness for eHealth in ageing society

Situation awareness is a renowned approach leading to a decision. The results obtained by measuring the awareness of stakeholders in healthcare can provide valuable inputs on the decision-making process. In the world of an ageing society, artificial intelligence in eHealth plays an essential role in the decision-making process of the users and their behaviors. In particular, clinical pathways, as evidence-based patient-care algorithms, describe the process of care for specific medical conditions within a localized setting. In clinical practice, patient-care journeys are generally subject to the recommended treatment interventions which are regulated in clinical pathways. However, unexpected scenarios occur in patient-care journeys and have a dramatic impact on health service delivery of clinical pathways, often when patients are discharged from the hospital and continue to be followed at home. In order to be able to quickly adapt to arising problems or deviations during the execution of clinical pathways, it is very important to be able to monitor clinical pathways in a near real-time manner so as to obtain a current overview of patient care. For this reason, telemedicine, along with the medical and wearable devices, that can now be employed to gather large amounts of data and perform data modeling through artificial intelligence techniques, may improve the clinical pathway management and reduce costs. Therefore, in this paper we introduce a novel Edge Computing framework that encompasses the different applications of telemedicine, ranging from the modeling and adherence to the clinical pathway to the early discovery of clinical deterioration conditions, allowing diagnosis and/or remote treatment through a set of artificial intelligence tools, also assessing the security and privacy issues that may occur during the health data transmission process, thus yielding a situation awareness for eHealth.