Characterizing the structure and content of nurse handoffs: A Sequential Conversational Analysis approach

Joanna Abraham, Thomas Kannampallil, Corinne Brenner, Karen D. Lopez, Khalid F. Almoosa, Bela Patel, Vimla L. Patel

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Effective communication during nurse handoffs is instrumental in ensuring safe and quality patient care. Much of the prior research on nurse handoffs has utilized retrospective methods such as interviews, surveys and questionnaires. While extremely useful, an in-depth understanding of the structure and content of conversations, and the inherent relationships within the content is paramount to designing effective nurse handoff interventions. In this paper, we present a methodological framework-Sequential Conversational Analysis (SCA)-a mixed-method approach that integrates qualitative conversational analysis with quantitative sequential pattern analysis. We describe the SCA approach and provide a detailed example as a proof of concept of its use for the analysis of nurse handoff communication in a medical intensive care unit. This novel approach allows us to characterize the conversational structure, clinical content, disruptions in the conversation, and the inherently phasic nature of nurse handoff communication. The characterization of communication patterns highlights the relationships underlying the verbal content of nurse handoffs with specific emphasis on: the interactive nature of conversation, relevance of role-based (incoming, outgoing) communication requirements, clinical content focus on critical patient-related events, and discussion of pending patient management tasks. We also discuss the applicability of the SCA approach as a method for providing in-depth understanding of the dynamics of communication in other settings and domains.

Original languageEnglish
Pages (from-to)76-88
Number of pages13
JournalJournal of Biomedical Informatics
StatePublished - Feb 1 2016


  • Care transitions
  • Communication
  • Communication errors
  • Conversational analysis
  • Intensive care
  • Nurse handoffs
  • Sequential analysis
  • Shift report


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