The research aim underpinning the Healthcare@Home (HH) information system described here was to enable ‘near real time’ risk analysis for disease early detection and prevention. To this end, we are implementing a family of prototype web services to ‘push’ or ‘pull’ individual's health-related data via a system of clinical hubs, mobile communication devices and/or dedicated home-based network computers. We are examining more efficient methods for ethical use of such data in timeline-based (i.e. ‘longitudinal’) data analysis systems. A consistent data collation infrastructure is being created for use along the ‘patient path’ – accessible wherever patients happen to be. This ‘patient-centred’ infrastructure can be applied in the evaluation of disease progression risk (in the light of clinical understanding of disease processes). In this paper we describe the requirements for making multi-data trend management ‘scale-up’, together with some requirements of an ‘end-to-end’ functioning data collection system. A Service-Oriented Architecture (SOA) approach is used to maximise benefits from (1) clinical evidence and (2) computational models of disease progression that can be made available elsewhere on the SOA.
