Support emergency patient triage with an AI chat intake system

Patients describe their symptoms in chat and AI scores urgency, flags the right care pathway, and alerts the medical team.

How the work actually flows

A straight line. A person has to approve before it continues.

Pattern: Sequence (1)

flowchart TD trig>"patient enters symptoms in chat"]:::trig s0["review symptoms against protocols"]:::task s1["verify consent and completeness"]:::task s2["calculate priority score"]:::task s3["determine care pathway"]:::task s4(("notify care team and log record")):::human trig --> s0 s0 --> s1 s2 --> s3 s3 --> s4 hg(("consent and completeness check")):::human s1 --> hg hg -->|"approved"| s2 hg -. "sent back" .-> s1 out[/"prioritized patient record with pathway"/]:::out pay{{"faster consistent triage decisions"}}:::pay s4 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepA personResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsAI Chatbots & AssistantsSpreadsheet & Database Ops
Connects
OpenAIPostgreSQL
Featured in

The problem it solves

During busy periods, your intake team is stretched thin trying to gather symptoms, apply triage protocols consistently, and flag urgent cases fast enough. Inconsistent intake can mean high-priority patients wait longer than they should.

Who it fits

Emergency departments, urgent care centers, and telehealth teams that need consistent, protocol-driven patient intake.

How it works

  1. A patient enters their symptoms and history through a chat interface
  2. AI reviews the information against your clinical triage protocols
  3. The system checks for missing consent or incomplete data before proceeding
  4. It calculates a priority score and determines the next action
  5. The care team is notified and the interaction is logged for the record
What you get

Urgent cases flagged before they're missed

Patients get a consistent, protocol-based intake assessment with a priority score and instant alerts to your care team.

What you get

A prioritized patient record with a recommended care pathway, a team notification, and a logged audit trail.

What you need

An OpenAI API key and integration with your hospital's appointment and notification systems.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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