We present an efficient and scalable system to predict emergency department (ED) patient volume in hospitals using publicly available Google Trends search data. Search volume data are retrieved for a selected set of context-relevant query keywords with refinements, on which a series of correlation analyses are performed, and a multiple regression predictive model is constructed. We also develop a software suite to enable convenient access to data visualization and prediction capabilities by

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... cal and administrative staff. A preliminary demonstration of the method and software is presented with data from a large public hospital as a form of validation. This paper enables informed resource and manpower allocation in hospitals and thus improved ability to respond to patient influx surges, and importantly, can serve as a key mitigation measure against worsening ED congestion problems that plague hospitals.