Quantifying the qualitative with epistemic network analysis: A human factors case study of task-allocation communication in a primary care team

Health care is fundamentally about people, and therefore, engineering approaches for studying healthcare systems must consider the perspective, concepts and methods offered by the human factors and ergonomics (HFE) discipline. HFE analysis is often qualitative to provide in-depth description of work systems and processes. To deepen our understanding of care processes, we propose the next level of analysis; i.e., quantification of qualitative data. Here, we describe epistemic network analysis (ENA) as a novel method to quantify qualitative data and present a case study applying ENA to assess communication in a primary care team. One high-performing primary care team, consisting of a physician, nurse, medical assistant and unit clerk, was observed for 15 hours. We analyzed task-allocation communications and identified the sender, receiver, synchronicity and acceptance. We used logistic regression and ENA to evaluate sender, receiver and synchronicity impact on task acceptance. The physician and unit clerk were most successful at allocating tasks. Future work should consider the role of synchronous, interruptive communication as potentially useful in time-critical tasks and further investigate the role of the unit clerk. HFE researchers should consider ENA as a tool to expand and deepen their understanding of care processes by quantifying qualitative data.