Streamlining patient consultations for sleep disorders with a knowledge-based CDSS

© 2015 Elsevier Ltd. Objectives This paper examines the workflow of sleep physicians during a patient consultation and how an innovative clinical decision support system (CDSS) provides efficiency and effectiveness gains. Methods The CDSS tools consisted of two input applications for patient data, with a knowledge based decision support system developed participatively with physicians and an international panel. An argument tree approach was used to produce diagnostic explanations and an evidence-based report for the physician using medically correct and shared terminology. A usability evaluation using a qualitative approach was carried out to ensure that the CDSS met the physicians information needs, as well as the wider needs of a Sleep Investigation Unit. Results The physicians found the CDSS both useful and usable with clear applications in triage and diagnostic decision-making, and in patient education. Conclusion The CDSS both reduces the time and number of visits needed for consultations, and helps focus consultation on better individual patient care through informed explanation of diagnostic and treatment decisions

Meta-design Knowledge for Clinical Decision Support Systems

Knowledge gained from a Decision Support Systems (DSS) design should ideally be reusable by DSS designers and researchers. The majority of existing DSS research has mainly focused on empirical problem solving rather than on developing principles that could inform solution approaches for other user contexts. Design Science Research (DSR) has contributed to effective development of various innovative DSS artifacts and associated knowledge development, but there has been limited progress on new knowledge development from a practical problem context, going beyond product and process descriptions. For DSS applications such as Clinical Decision Support Systems (CDSS) design and development, relevant reusable prescriptive knowledge is of significance not only to understand mutability but also to extend application of theory across domains. In this paper, we develop new design knowledge abstracted from the approach taken in a representative case of innovative CDSS development, specified as an architecture and six design principles. The CDSS design artifact was initially designed for a specific clinical need is shown to be flexible for meeting demands of knowledge production both for diagnosis and treatment. It is argued that the proposed general strategy is applicable to designing CDSS artifacts in similar problem domains representing an important contribution of design knowledge both in DSS and DSR fields