Using Qualitative Content Analysis and Natural Language Processing to Explore Nurse Decision-Making in Urgent Patient Care Situations

Acute care nurses use several clinical decision support tools and rely on intuition during urgent patient care decision-making situations. This research explored factors that influence acute care nurses' decision-making during urgent and time-limited patient care situations. Twenty-two nurses on 2 coronavirus units participated in semistructured interviews. To enhance rigor in this study, data analysis included triangulation of research methods through integration of qualitative content analysis and natural language processing. The Practice Primed Decision Model guided the development of some semistructured interview questions, early qualitative content analysis, and categories identified from natural language processing. Three main themes emerged using qualitative description content analysis: the role of experience in urgent patient care decision-making; increased complexity and uncertainty in patient care, leading to novel cognitive, physical, and emotional demands for nurses; and health care team support for an effective response to urgent patient care needs. Natural language processing results included drives and motivations, cognitive processes, and social behaviors and culture. This study provides descriptions of nurses' understanding of patient status, emotional support, team-oriented decision support, and reliance on previous clinical experience during urgent patient care situations, to provide information toward the development of improved clinical decision support systems.