A Scalable Clinical Intelligent Decision Support System

Hua Chu, Yijing Yang, Qingshan Li, Yongfei Xu, Hongpeng Wei

Abstract: It is a known fact that Clinical Decision Support System (CDSS) can help to improve the quality of medical. But the existing CDSSs are mostly focused on a typical disease. Single knowledge base and limited decision support results have a heavy impact on the application of CDSS in clinical medicine. To improve the scalability of extending new diseases to the CDSS, this paper proposes a scalable architecture named Open Clinical Decision Support Platform (OCDSP) that can customize and develop CDSS for any kind of diseases. Using the tool sets of OCDSP, one can configure medical knowledge bases, workflows of clinical paths, and clinic rules. Finally, a concrete CDSS of a specific disease can be customized from OCDSP. The software architecture of OCDSP is discussed detailed. In order to validate the scalability of OCDSP, the case study of how to customize CDSS for fracture and coronary heart disease is put forward.