Numerous health decision aids (HDAs) have been developed to increase the participation of patients in shared decision-making, but many have limited accessibility and narrow applicability in clinical care. In the e Preference project, we address these limitations in our approach to building HDAs targeted for older adults. Our work is based on a decision-support software architecture that supports generic methods for HDAs. We have formalized a novel knowledge-based decision model (KBDM), using Protégé OWL, that developers and clinicians can instantiate to tailor the components of the architecture for a particular health problem. In this paper, we present the methods used in the architecture and the knowledgebase design, which encompasses influence-diagram concepts, specific health problems, health outcome states, and probabilistic relationships. We discuss how this approach overcomes limitations of prior methods. We also show that our use of computer-interpretable knowledge provides a structured, customizable means of enabling patient-centered decision support.
