EHR audit logs are a highly granular stream of events that capture clinician activities, and is a significant area of interest for research in characterizing clinician workflow on the electronic health record (EHR). Existing techniques to measure the complexity of workflow through EHR audit logs (audit logs) involve time- or frequency-based cross-sectional aggregations that are unable to capture the full complexity of a EHR session. We briefly evaluate the usage of transformer-based tabular language model (tabular LM) in measuring the entropy or disorderedness of action sequences within workflow and release the evaluated models publicly.

翻译：电子病历审计日志是一种高度细粒度的事件流，能够捕捉临床医生的活动，是研究电子健康记录（EHR）中临床工作流程特征的重要领域。现有通过EHR审计日志衡量工作流程复杂度的技术，主要采用基于时间或频率的横截面聚合方法，难以完整反映EHR会话的复杂度。本文简要评估了基于Transformer的表格语言模型（tabular LM）在衡量工作流程中动作序列熵值或混乱度方面的应用，并公开发布了经评估的模型。