Combining conversation analysis and event sequencing to study health communication

Area of Science:

• Health communication
• Medical interaction analysis
• Patient-centered care

Background:

• Effective communication is crucial for patient-centered care, particularly in intensive care units (ICUs) where complex decisions are made.
• Clinician-surrogate decision-maker communication significantly impacts treatment outcomes and patient care.
• Understanding interaction dynamics is key to improving healthcare communication strategies.

Purpose of the Study:

• To describe conversation analysis and event sequencing methods.
• To explain how integrating these methods enhances the analysis of clinician-surrogate communication in ICUs.
• To identify communication strategies that lead to positive outcomes in life-sustaining treatment decisions.

Main Methods:

• Conversation analysis (CA) was employed to examine the detailed interaction between clinicians and surrogate decision makers.
• Event sequence analysis (ESA) was used to quantitatively assess the transitional probabilities between communication events.
• A mixed-methods approach combining CA and ESA provided a comprehensive analysis of communication patterns.

Main Results:

• Conversation analysis revealed specific ways clinicians introduced decision-making needs and how surrogates responded.
• Event sequence analysis quantified the likelihood of surrogate resistance or alignment following different clinician introduction types.
• The integrated methods provided deeper insights into communication strategies and their impact on interactional outcomes.

Conclusions:

• Combining conversation analysis with event sequence analysis offers a robust framework for studying health communication.
• This mixed-methods approach can identify beneficial conversational practices for clinicians and surrogate decision makers.
• The findings can inform the design of interventions to improve health communication and patient-centered care in critical care settings.