Revealing structures in narratives: A mixed-methods approach to studying interdisciplinary handoff in critical care.

ABSTRACT

OBJECTIVE: To examine a novel mixed-methods approach for studying patterns of clinical communication that could inform future informatics solutions, with a specific focus on handoff within interdisciplinary teams. MATERIALS AND METHODS: Researchers observed, recorded, and transcribed verbal handoff discussions of different members of critical care teams. The transcripts were coded qualitatively, and then analyzed quantitatively for emerging structural patterns using categorical cluster analysis, and for degree of shared mental models (SMM) using the modified Pyramid method. RESULTS: An empirical study using the proposed mixed-methods approach suggested emerging patterns of communication among clinicians. For example, the temporal focus of handoff was often determined by the role of the clinician giving the handoff; the clinical content of handoff was consistent between clinicians, but varied between patients. The SMM index ranged from 0.065 (with the maximum possible overlap score of 1) to 0.007 with a median of 0.026; the overlap was higher in statements concerned with patient presentation (23.6% of these had overlap) and referring to the past (24% overlapped). This calculated SMM index was correlated with the assessment of coherence within the participating teams by independent physicians (r=0.63, p=0.038). CONCLUSIONS: The proposed novel mixed-methods approach helped to reveal emerging patterns in content and structure of handoff communication and highlight differences due to the clinical context, and to the different priorities of clinicians on interdisciplinary patient care teams. The approach for calculating SMM is more ecologically sensitive as it relies on naturally occurring discourse and less intrusive than traditional ways of assessing SMM, and takes initial steps toward establishing empirical foundation for the design of electronic tools to support handoff in interdisciplinary teams.