Hypothesis-driven data abstraction with trend templates

We have written a prototype computer program called TrenDx for automated trend detection during process monitoring. The program uses a representation called trend templates that define disorders as typical patterns of relevant variables. These patterns guide the assignment of primary data to abstracted intervals or phases of the monitored process. TrenDx has been applied to the task of pediatric growth monitoring. The results of an exploratory clinical trial are reviewed here. The general utility of TrenDx for clinical trend detection and diagnosis is illustrated with examples from several task domains.