Clinicians at the bedside are increasingly overwhelmed by an inundation of information and must rely largely on pattern recognition and professional experience to comprehend complex clinical data and treat their patients in a timely manner. Traditional decision support systems are based on rules and predictive models and often fail to take advantage of increasingly large digital clinical data stores available in real-time. We propose an alternative approach to delivering data-driven decision support based on an interactive system for exploring and visualizing a context of physiologically similar patients from a database. Here we present Sim•TwentyFive, a highly flexible, responsive, intuitive prototype with a comprehensive set of interaction techniques that effectively reduces the cognitive burden of querying, exploring, analyzing and comparing similar past patient episodes. Quantitative performance tests and anonymous summative evaluations from PICU physicians indicated that Sim•TwentyFive is an efficient, intuitive and clinically-useful tool.
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