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

Area of Science:

• Health Informatics
• Clinical Communication
• Natural Language Processing

Background:

• Electronic health records and healthcare databases are primarily mined using natural language processing (NLP) for tasks like identifying at-risk populations and predicting hospital-associated infections.
• NLP is rarely used in healthcare research to analyze provider-to-provider communication or the impact of language on patient outcomes.
• Few studies analyze the content (data, information, knowledge) and context (how) of healthcare communication.

Purpose of the Study:

• To discuss the feasibility of using an innovative within-methods triangulation data analysis to examine nurse-to-nurse change-of-shift hand-off communication.
• To uncover the contextual and linguistic meaning within nursing hand-off communication.

Main Methods:

• Utilizing a natural language processing (NLP) software program.
• Employing content analysis.
• Implementing an innovative within-methods triangulation data analysis approach to analyze nursing hand-off communication.

Main Results:

• The study discusses the feasibility of the proposed analytical approach.
• The methodology aims to uncover contextual and linguistic nuances in nurse communication.

Conclusions:

• Analyzing the 'how' and 'what' of healthcare communication has the potential to decrease errors and improve patient outcomes.
• The proposed triangulation method offers a novel approach to understanding nurse-to-nurse communication during hand-offs.