> ## Documentation Index
> Fetch the complete documentation index at: https://medlogprotocol.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Relationship to EHR audit logs

> What a decade of EHR audit log research implies for real-world MedLog deployment.

MedLog also builds on EHR audit logs. EHRs often maintain event or audit logs for record access. These
logs demonstrate that **event-level logging in healthcare is feasible at scale**: audit logs can capture
time-stamped user actions, measure clinical work, and reveal aspects of care delivery that are not
visible from clinical or claims data alone.

## What audit log research has shown

<CardGroup cols={2}>
  <Card title="Workflow efficiency" icon="gauge-high">
    Audit logs have been used to assess hospital workflow efficiency.
  </Card>

  <Card title="Care patterns" icon="users-line">
    Interaction patterns in audit logs have been associated with length of stay and timeliness of care.
  </Card>

  <Card title="Outlier detection" icon="magnifying-glass-chart">
    Audit logs support detection of clinical outliers.
  </Card>

  <Card title="Provider behavior" icon="user-doctor">
    Audit logs have been used to study provider behavior directly.
  </Card>
</CardGroup>

Audit logs have also revealed contextual factors relevant to clinical process outcomes across multiple
sites, even despite site-dependent documentation differences.

## Why this matters for MedLog

These past studies of EHR auditing and logging can provide learnings for real-world deployment of MedLog
beyond the pilots reported in the [MedLog paper](https://arxiv.org/abs/2510.04033). They establish both
the feasibility of health-system-scale event logging and the analytic value of linking time-stamped
events to care delivery.

MedLog [Outcomes](/specification/outcomes) may themselves include traces of how patients or clinicians
interact with the EHR after viewing AI outputs, as recorded in EHR audit logs.