Author Affiliations: College of Nursing, University of Arizona (Dr Galatzan), Tucson, and School of Nursing University of Alabama Birmingham, Birmingham, Alabama; College of Nursing University of Florida (Dr Carrington), Gainesville, Florida; and College of Nursing University of Arizona (Dr Gephart), Tucson, Arizona.
Comput Inform Nurs. 2021 May 10;39(8):411-417. doi: 10.1097/CIN.0000000000000732.
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.
自然语言处理软件程序主要用于从电子健康记录和其他医疗保健数据库中挖掘结构化和非结构化数据。挖掘出的数据可用于识别弱势群体和高危人群，并预测医院相关感染和并发症。自然语言处理程序在医疗保健研究中很少用于分析提供者如何将重要的患者信息从一个提供者传递给另一个提供者，或者所使用的语言如何影响患者的结果。除了分析消息是如何传递的之外，很少有研究从数据、信息和知识的角度分析在交流过程中传达了什么。分析医疗保健提供者的书面和口头沟通的“方式”和“内容”有可能减少错误并改善患者的结果。在这里，我们将讨论使用创新的内部方法三角数据分析来揭示护士交接班口头沟通的上下文和语言含义的可行性。创新的内部方法三角数据分析使用自然语言处理软件程序和内容分析来分析护理交接班口头沟通。
