How to build a Physician Assistant Agent
This agent streamlines the process of gathering patient information and relevant clinical knowledge to generate clear, context-aware summaries for healthcare providers.
Challenge
Physicians and staff often struggle to quickly synthesize patient data and clinical best practices into concise, actionable summaries for decision-making.
Industry
Healthcare
Department
Customer Success
Integrations
OpenAI
OneDrive
Workflow Overview
1. User Inputs
Patient Name (Input Node)
The user (such as a physician or staff member) enters a patient’s name or a clinical question.
Patient Birth Date (Input Node)
The user also provides the patient’s birth date.
2. Patient Data Retrieval
Search Azure Blob Storage (Knowledge Base Node)
The workflow uses the patient’s name and birth date to search for relevant files or records in Azure Blob Storage.
This node acts as a bridge between the user’s input and the patient’s stored data, retrieving relevant information (such as medical records, PDFs, or notes) for the next step.
3. AI Clinical Summary Generation
OpenAI (LLM Node)
The AI assistant receives:
The user’s request (e.g., a question or patient name)
The retrieved patient data from Azure Blob Storage
It then generates a concise, clinically relevant summary for the physician, combining the user’s request and the patient’s data.
The AI is guided by a system prompt to ensure responses are clear, accurate, and contextually appropriate for clinical use.
4. Output to User
Output Node
The AI-generated summary is displayed to the user, providing a clear and actionable clinical summary based on the patient’s information and the user’s query.
How the Nodes Connect
Patient Name and Patient Birth Date → Search Azure Blob Storage
Both user inputs are used to search for the correct patient data.
Search Azure Blob Storage → OpenAI
The retrieved patient data is sent to the AI assistant.
OpenAI → Output
The AI’s summary is shown to the user.
Summary Table
Node Name | Purpose |
|---|---|
Patient Name (Input) | User enters patient name or question |
Patient Birth Date (Input) | User enters patient birth date |
Search Azure Blob Storage | Finds relevant patient files/data |
OpenAI (LLM) | Generates a clinical summary using user input and patient data |
Output | Displays the summary to the user |
Key Points
The workflow is designed for clinical use, helping physicians quickly get relevant patient summaries.
It combines user input with secure data retrieval and advanced AI summarization.
The process is streamlined: user input → data search → AI summary → output.
