Cross-boundary knowledge-based decision support in e-health

Abstract

Recent research in pervasive computing and distributed decision support systems aims to enable users to share knowledge easily to support one another in problem solving in a manner that adapts to their varying contexts of work. However, existing approaches, most often, are restricted by formal models of task analysis and, as such, are not able to capture the informal work practices, which workers often adopt in problem solving, and which are largely dependent on workplace context, personal experience, available expertise, tools and technologies, and organisational and regional agenda. As a result, designing context-aware systems to support decision making in cross-boundary e-health poses a huge challenge because of the inherent difficulty in establishing a shared context of work and users adequate for supporting knowledge sharing and decision making among workers across organisational and geographical boundaries. In this paper, we propose a context model, which we refer to as practice ontology, to enable cross-boundary decision support in e-health. We describe how the context model is represented within the framework of an abstract cross-boundary collaboration model. We describe the practice ontology design and a prototype system based on the model using a clinical case study.