Background The lack of machine-interpretable representations of consent permissions precludes development of tools that act upon permissions across information ecosystems, at scale. Objectives To report the process, results, and lessons learned while annotating permissions in clinical consent forms. Methods We conducted a retrospective analysis of clinical consent forms. We developed an annotation scheme following the MAMA (Model-Annotate-Model-Annotate) cycle and evaluated interannotator agreement (IAA) using observed agreement (A o), weighted kappa (κw ), and Krippendorff's α. Results The final dataset included 6,399 sentences from 134 clinical consent forms. Complete agreement was achieved for 5,871 sentences, including 211 positively identified and 5,660 negatively identified as permission-sentences across all three annotators (A o = 0.944, Krippendorff's α = 0.599). These values reflect moderate to substantial IAA. Although permission-sentences contain a set of common words and structure, disagreements between annotators are largely explained by lexical variability and ambiguity in sentence meaning. Conclusion Our findings point to the complexity of identifying permission-sentences within the clinical consent forms. We present our results in light of lessons learned, which may serve as a launching point for developing tools for automated permission extraction.

Physician-nurse relations Oncology nursingBackground: Effective communication between physicians and nurses is crucial to the safety of patients, especially for those with cancer, which is a complex disease requiring multidisciplinary treatment. However, little is known about the factors that contribute to effective communication, which is defined as the development of shared understanding between two or more people. Objective: This qualitative secondary analysis was conducted to identify factors that contribute to shared understanding between physicians and nurses from video-recorded conversations that occurred between them during inpatient rounds on oncology units. Methods: We used inductive grounded theory to identify videos depicting moments of shared understanding. We then searched for preceding events to develop a preliminary conceptual model that described the factors contributing to shared understanding. Results: Four factors emerged as contributors to shared understanding: engagement, clarification, confirmation, and resolution. These factors occurred in sequence with engagement occurring first and resolution occurring last, as the closure of a communication exchange. Conclusions: Existing interventions to improve communication include some of the factors identified as contributing to shared understanding (eg, closed-loop communications require clarification and confirmation).However, nurses may need to pay attention to all four factors to develop shared understanding that will promote effective communication with physicians and thereby