FEATURESTesting the Use of Natural Language Processing Software and Content Analysis to Analyze Nursing Hand-off Text DataGalatzan, Benjamin J. PhD, RN; Carrington, Jane M. PhD, RN, FAAN; Gephart, Sheila PhD, RN, FAAN Author Information 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. The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article. Dr Gephart received training support from the Agency for Healthcare Research and Quality (K08HS022908). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. Corresponding Author: Benjamin J. Galatzan, PhD, RN, School of Nursing, University of Alabama Birmingham, 1701 University Boulevard Birmingham, AL 35294 ([email protected]). CIN: Computers, Informatics, Nursing: August 2021 - Volume 39 - Issue 8 - p 411-417 doi: 10.1097/CIN.0000000000000732 Buy CME Test Metrics 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. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.