1 Clinical Documentation AI Agent, Live in Production.
1 live agent automates clinical documentation within healthcare. It runs on demand. It publishes the inputs it needs, the steps it works through and what it hands back.
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Clinical Document Summary
Summarise a discharge summary, consultation note, or referral letter, and emit the problems, medications, and follow-up actions as a structured FHIR bundle alongside the readable version.
Emitting a structured bundle alongside the readable version, not instead of it
Clinical correspondence carries structured information inside unstructured prose. A discharge summary states the problems, the medications on discharge and the follow-up actions required, and all of it arrives as narrative — so it has to be read and re-keyed into the record by someone, or it is not in the record at all. The re-keying is where information is lost, and the loss is invisible: a medication change mentioned in a paragraph rather than a list, a follow-up action attached to a condition, an allergy noted in passing. Structured extraction is the obvious answer and carries an obvious risk, which is that a structured output looks authoritative regardless of whether the extraction was correct.
Clinical Document Summary summarises a discharge summary, consultation note or referral letter and emits the problems, medications and follow-up actions as a structured FHIR bundle alongside the readable version. The word alongside is doing the work. A structured bundle on its own is unverifiable in practice — nobody re-reads the source to check it, so an extraction error becomes a record error. Producing both means the clinician reviewing it can see what the document said and what was extracted from it in the same place. One agent covers this process, it does not alter a record, and its output is for clinical review before anything is filed.
What this moves
- Structured data available from narrative documents
- Problems, medications and follow-up actions are emitted as a FHIR bundle, so information locked in prose becomes usable by the record system.
- Extractions that can be checked
- The readable summary is produced alongside the structured output, so a clinician can verify the extraction against the source rather than trusting it.
Healthcare
How AI agents handle clinical documentation
Drawn from the 1 agent above — what they require, how they run, and what comes back.
What they need
- Clinical document
- Summary settings
What comes back
- Encounter
- Summary
- Problems and diagnoses
- Medications
- Follow-up actions
- Needs attention
- FHIR R4 bundle
How they run
- Run on demand
- 1
- Steps per run
- 4
- Credits per run
- 6
Where clinical documentation fits in healthcare
Documentation takes a large share of every shift and is a leading reason people leave. Drafting it from the record is where the time comes back.
Next Step
Deploying clinical documentation agents
These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.