Emergency Physician
Document encounters and navigate the EHR
What You Do Today
Document history, exam, medical decision-making, procedures, and disposition for every patient — often 20-30 per shift — while the documentation requirements keep growing.
AI That Applies
Ambient clinical documentation AI listens to your patient encounters, generates the note from the conversation, and populates the EHR fields — history, exam, MDM, and plan.
Technologies
How It Works
The system ingests conversation as its primary data source. NLP models parse document text into structured data — extracting named entities, classifying sections by type, and flagging content that deviates from expected patterns. The output — note from the conversation — surfaces in the existing workflow where the practitioner can review and act on it. You still review every note for accuracy.
What Changes
This is the single biggest AI impact in the ED right now. Instead of spending 3 hours per shift on documentation, AI drafts notes from your conversations. You review and sign.
What Stays
You still review every note for accuracy. AI mishears, misinterprets, and occasionally fabricates. Your signature on that note carries medicolegal weight — review is non-negotiable.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for document encounters and navigate the ehr, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long document encounters and navigate the ehr takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your department medical director
“What data do we already have that could improve how we handle document encounters and navigate the ehr?”
They set clinical practice guidelines that AI tools must align with
your health informatics lead
“Who on our team has the deepest experience with document encounters and navigate the ehr, and what tools are they already using?”
They manage the EHR integrations and clinical decision support configuration
a nurse informaticist
“If we brought in AI tools for document encounters and navigate the ehr, what would we measure before and after to know it actually helped?”
They bridge the gap between clinical workflow and technology implementation
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.