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.
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