Identifying and defining entities associated with fall risk factors events found in fall risk assessment tools

Abstract

PurposeThe contents of nursing notes play an important role in predicting patient fall risk. Based on data collected from fall risk assessment tools, we aimed to identify and define fall risk factors to support natural language processing, data mining of nursing notes, and automated fall prediction. MethodsThe PRISMA-ScR guidelines were used to summarize entities associated with the fall risk factors described in fall risk assessment tools. Fall risk factors (concepts) and their related words (entities) were extracted from the tools. In order to clarify the meaning of unclear fall risk factors and classify fall risk factor entities, we searched the websites of the World Health Organization and the governments of Victoria, Australia, and New South Wales (up to 20 December 2021). A nurse and a safety expert reviewed and assessed the extracted concepts and entities for clarity and relevance. Then, the NLPfallRisk tool was developed to extract entities associated with fall risk factors. ResultsWe identified 20 validated fall risk assessment tools appropriate for hospitals and healthcare facilities. Using these tools, we extracted 19 especially significant risk factors as the most significant and identified 151 entities related to them. ConclusionWe found that fall assessment tools considered a history of falls more frequently than any other risk factor. However, as fall risk tends to be multifaceted, risk assessments must take many factors into account.