Improving interprofessional collaboration through data-driven process evaluation of interprofessional case reviews

Abstract Purpose To develop a transparent and reproducible method of evaluating communication within interprofessional educational (IPE) sessions that differentiates talk that is conversational, collaborative, and interprofessional from other types of dialogue, and to statistically model predictors of collaboration. The method and programmatic utility of this approach are detailed. Method Eight 2-h case review sessions (n = 125 participants: 7560 speech turns) were videoes and double coded for speaker, target, speech act, type of collaboration, professions of interlocutors, topic and sex. Length of speech acts were measured to 0.1 s. Data were statistically analyzed using multilevel models to identify predictors of time-in-collaboration. Instances of collaboration were then further analyzed using descriptive statistics. Results Four types of collaborative communication were identified. Subjective assessments overestimated the extent of collaboration. Direct, student-to-student collaboration comprised approximately 5.1% of the total time-in-talk. Using a reproducible, transparent method of assessing student collaboration provided the basis for evidence-directed program enhancements.