AI 中文总结
研究以电子健康记录审计日志为对象，将其视为多轴事件流，通过基础模型预训练学习可重复使用的表示，阐述了审计日志在表示学习、评估和治理方面的作用及相关规定。
AI 中文摘要
电子健康记录审计日志记录了开展临床工作的带时间戳的行动。作为操作元数据生成的审计日志，目前支持对临床医生工作量、患者结果、护理团队协调和工作流程结构的研究。本观点文章通过将审计日志阐述为多轴事件流，并对表示学习、评估和治理产生影响，来解释其广度。每个记录的行动同时属于多个具有临床意义的关系：临床医生的工作、患者的轨迹、团队的活动和重复的工作流程。这种结构促使基础模型预训练以在原始流上学习可重复使用的表示。将审计日志视为多轴轨迹规定了此类表示必须保留的内容、应如何测试其价值以及应如何管理其使用。
英文摘要
Electronic health record audit logs record timestamped actions through which clinical work is carried out. Generated as operational metadata, they now support research on clinician effort, patient outcomes, care-team coordination, and workflow structure. This Perspective explains that breadth by articulating audit logs as multi-axial event streams and drawing implications for representation learning, evaluation, and governance. Each logged action belongs simultaneously to multiple clinically meaningful relations: a clinician's work, a patient's trajectory, a team's activity, and a recurring workflow. This structure motivates foundation-model pretraining to learn reusable representations over the raw stream. Reading audit logs as multi-axial traces specifies what such representations must preserve, how their value should be tested, and how their use should be governed.
