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，可捕捉临床医生的活动，是研究通过电子病历表征临床医生工作流程的重要领域。现有通过电子病历审计日志衡量工作流程复杂度的技术依赖于基于时间或频率的横截面聚合方法，无法全面反映电子病历会话的完整复杂性。我们初步评估了基于Transformer的表格语言模型在测量工作流程中动作序列熵值（无序度）方面的应用，并公开了经过评估的模型。