A SYSTEMATIC METHODOLOGY TO CHARACTERIZE COMMUNICATION PATTERNS IN CHRONIC CARE INNOVATION NETWORKS

摘要

This paper describes a methodology to measure communication behaviors in innovation teams. We collected data over two years by mining email communication archives. We applied the methodology to study twelve innovation teams working to re-design the delivery of care for chronically ill children. We used social network analysis and sentiment analysis to calculate network metrics such as group density, group betweenness centrality, actor betweenness centrality, average weighted variance in contribution index, and emotionality ratio. We administered surveys to senior leaders to assess their perception of teams' performance. We conducted "virtual mirroring" sessions with selected teams to share insights gained from analysis of their email interactions. This paper describes the application of this research methodology in the health care innovation context and explores the associations between performance, network density and average weighted variance in contribution index. Our preliminary findings show that high-performing teams tend to interact in less close-knit networks characterized by lower network density and a more balanced exchange of information among team members.