User-tailored E-health services

This thesis describes a method to offer personalised healthcare. It is motivated by a desire for more efficient healthcare, as population ages and care demand and costs increase. Developing and testing individually tailored health services using ICT fits in this motivation, as it leads to more adequate information provided to care receivers and caregivers, a shift in tasks from caregiver to care receiver, and most of all: health services that empower as they are personalised towards individual needs. In this research, a platform is realised and tested to provide user-tailored e-health services. Tailored means client-specific, i.e different care receivers can consume varying care services of different vendors from the same platform. E-health services are electronic health services, or recurring health applications involving communication, mediated by ICT to bridge time and/or distance. The services in the platform apply to care situations like alarming, reminding, taking vital sign measurements, and medication management. Moreover, activity management and interaction between (in)formal caregivers and care receivers are supported. The personalisation of these services can be performed by end users themselves. Hence, the e-health services are user-tailored. To realise this platform, requirements have been elicited involving interviews with end users. Desires and needs have been translated into scenarios and scenario visualisations to discuss refinement. The technical design based on this requirements engineering process, has been implemented. Then it was tested in a nursing home. Finally we researched how, given such a system in use, data can be analysed and leveraged to monitor patients over longer time, to offer decision support and to provide insight into patient behaviour. Results show that is possible to create a platform that enables patientspecific care. The platform provides useful applications in care. These applications can save time for caregivers, and increase self-management in patients. However, it requires investment in the learning process. In sum, the work shows that this platform successfully integrates and tailors heterogeneous sensors, actuators and services from different vendor and technological origins. Moreover, the research shows how collected data can be leveraged for analysis and decision support. Adequate personalisation of selected e-health services saves time, increases health situation awareness, supports interaction and furthers patient empowerment