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Mining Hospital Data to Optimize Patient Flow

Health care organizations are increasing expenditures on information technology as a means to improve safety, quality, and access. As hospitals implement more sophisticated information technologies, such as computerized bed management systems and electronic medical records, large data bases are created that could support improved managerial and clinical decision making to improve patient flow, a major issue currently being addressed by hospitals nationally and internationally to improve patient access and quality of care. However, expertise to develop and apply sophisticated data mining and analysis techniques to turn the data into information and knowledge that supports informed decision making for action is lacking by health care organizations, health system vendors, and health system engineers. As a result, increasingly common hospital data bases remain a grossly underutilized strategic resource in hospitals. The purpose of this proposed research is to partner with United Hospital in St. Paul , MN to develop new data mining and analysis methodologies that leverage these common hospital databases. These methods will inform healthcare administrators and clinicians on how to turn available data into information and knowledge to support decision making. They will also inform operations researchers and systems engineers on how to utilize such databases to provide estimates for input parameters needed for sophisticated systems engineering models, such as optimization and computer simulation models.