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A graphic representation of monitored data may provide better support for detection, diagnosis, and treatment. A user-centered design process led to a novel object-oriented graphic display of hemodynamic variables containing emergent features and functional relationships. In a simulated environment, this display appeared to support clinicians' ability to diagnose, manage, and treat a critical cardiovascular event in a simulated environment. We designed a graphic display to show hemodynamic variables. The study provides some support for the hypothesis that providing clinical information graphically in a display designed with emergent features and functional relationships can improve clinicians' ability to detect, diagnosis, mange, and treat critical cardiovascular events in a simulated environment.

The drug display altered simulated clinical practice. These results, which will inform the next iteration of designs and evaluations, suggest promise for this approach to drug data visualization.

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We are living in a world overflowing with information [1]. Millions of labs and scientists across the globe are continually conducting millions of experiments, observations and analyses, producing ever-growing amounts of information. Our ordinary lives have become data traces, too: ATM and credit card transactions, on-line registration of software, cellular phone calls and so on. Security concerns after 9/11 have only intensified this demand for and accumulation of data. The central issue has shifted from getting data to making sense of it.Over 20 years of work in scientific visualization, human factors and semiotics indicates that there exists a direct correlation between how data is represented and the meaning that can be extracted from it. Better representations mean better understanding. In fact, the way that data is presented has an overwhelming weight in how a system or situation is perceived and what ultimately drives decision-making processes, not only for science but for public policy as well [2]. Currently, there is wide agreement that visualization is the best representational method for turning complex data into information [3].Although there has been much work in the visualization design area, scientists and other data producers and end users are only beginning to tap the possibilities of communicating data visually. There are many well-documented examples of inappropriate decisions based upon poorly presented information, often leading to disastrous effects (from the crisis at the Shearon Harris nuclear power plant in 1979 and the Challenger and Chernobyl disasters in 1985 to the breakdown in intelligence-sharing leading to 9/11). Yet more negative effects may be found in the less spectacular but more pervasive