Testing the Use of Natural Language Processing Software and Content Analysis to Analyze Nursing Hand-off Text Data

Abstract

Natural language processing software programs are used primarily to mine both structured and unstructured data from the electronic health record and other healthcare databases. The mined data are used, for example, to identify vulnerable at-risk populations and predicting hospital associated infections and complications. Natural language processing programs are seldomly used in healthcare research to analyze the how providers are communicating essential patient information from one provider to another or how the language that is used impacts patient outcomes. In addition to analyzing how the message is being communicated, few studies have analyzed what is communicated during the exchange in terms of data, information, and knowledge. The analysis of the "how"and "what"of healthcare provider communication both written and verbal has the potential to decrease errors and improve patient outcomes. Here, we will discuss the feasibility of using an innovative within-methods triangulation data analysis to uncover the contextual and linguistic meaning of the nurse-to-nurse change-of-shift hand-off communication. The innovative within-methods triangulation data analysis uses a natural language processing software program and content analysis to analyze the nursing hand-off communication.