Clinical decision-making using a data-driven display

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DESCRIPTION (provided by applicant): Clinical laboratory data displays organized by physiologic system or concept hierarchies may improve the speed and/or accuracy of clinical decisions as compared with displays organized by laboratory section. Nonmedical cognitive analysis studies indicate that graphical representation of data is associated with improved decision making in comparison with tabular numerical data, particularly in time-pressured situations. We hypothesize that identification and explicit graphical representation of important temporal relationships in clinical laboratory data will improve the ability of clinicians to reach decisions rapidly and correctly. We have developed a framework for identifying statistical patterns in timeseries data and temporal relationships between those patterns. We propose to 1) incorporate our framework into a problem-oriented display that prioritizes and visualizes clinical laboratory data adaptively based on types of temporal patterns in the data, 2) conduct patient case simulations in which clinician subjects access clinical laboratory data using traditional, problem-oriented, and temporal data-driven displays, and 3) evaluate the efficiency and accuracy of decision-making by clinicians under these simulated case conditions with mild time pressure, using "think aloud" techniques in which clinicians are video- and audiotaped during decision-making. The influence of these three user interfaces on decision-making will be evaluated by the accuracy of orders in comparison with an expert clinical gold standard, the relative proportions of information acquisition vs. information evaluation cognitive steps during case analysis, the total cognitive steps (cognitive load) required for case disposition, and the total number of screens and data elements viewed. We anticipate that the problem oriented display will support improved clinical decision-making through increasing the efficiency of information gathering; the temporal data-driven display may enhance decision-making further by focusing attention on, and directly visualizing, important relationships that would ordinarily have to be inferred.