Information architecture of a clinical decision support system

Abstract

Recent healthcare legislation, the move to electronic health records, and the accelerating pace of medical knowledge discovery combine to create an environment in which clinical decision support systems are a necessary part of most medical processes. Based on a review of current best practices, we present the information architecture of a clinical decision support system comprised of four primary components: patient model, treatment library, intelligent agents, and an authenticated knowledge base. The patient model contains all patient information in the form of measurable parameters, treatment history, and health goals. Information regarding treatment procedures, dosages, and effects is stored in treatment library. Intelligent agents are used to optimize courses of treatments to best achieve desired health goals. Finally, an authenticated knowledge base containing the most recent medical research is used to keep the patient model and treatment library up to date.