Exploring methods for identifying related patient safety events using structured and unstructured data

Most healthcare systems have implemented patient safety event reporting systems to identify safety hazards. Searching the safety event data to find related patient safety reports and identify trends is challenging given the complexity and quantity of these reports. Structured data elements selected by the event reporter may be inaccurate and the free-text narrative descriptions are difficult to analyze. In this paper we present and explore methods for utilizing both the unstructured free-text and structured data elements in safety event reports to identify and rank similar events. We evaluate the results of three different free-text search methods, including a unique topic modeling adaptation, and structured element weights, using a patient fall use case. The various search techniques and weight combinations tended to prioritize different aspects of the event reports leading to different search and ranking results. These search and prioritization methods have the potential to greatly improve patient safety officers, and other healthcare workers, understanding of which safety event reports are related.

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