No items found.

Healthcare explanations of a patient-doctor match

Summarize why a patient was matched with a specific provider.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Click to interact

This workflow generates a personalized explanation of why a specific healthcare provider is a good match for a patient based on their needs and preferences. It processes patient and provider information to identify matches and create a clear, factual explanation.

How it Works / How to Build It

  1. PII Redaction: This node takes the patient information and redacts any personally identifiable information (PII) to ensure privacy. It outputs a sanitized JSON object containing relevant patient details.
  2. Find Match Evidence: This node analyzes the sanitized patient information and provider information to identify matches. It uses a prompt to categorize the match strength as either 'strong' or 'partial' and returns a JSON array of matched pairs.
  3. Extract Provider Name: This node extracts the provider's name from the provider information, which will be used in the final explanation.
  4. Gen Match Explanation: This node generates a neutral, fact-based explanation of why the provider is a good match for the patient, using the evidence gathered in the previous steps.
  5. Output: This node formats the final explanation into a structured output for the user.

What You Can Use This For

  • Healthcare teams can use this workflow to provide personalized match explanations for patients seeking providers.
  • Patient support services can leverage this to enhance communication and transparency regarding provider recommendations.
  • Insurance companies can utilize it to explain provider options to clients based on their specific needs.

Prerequisites

  • Vellum account
  • JSON schema for patient information and provider information

How to Set It Up

  1. Create a new workflow in your Vellum account.
  2. Add the PII Redaction node and connect it to the input for patient information.
  3. Add the Find Match Evidence node and connect it to the output of the PII Redaction node and the provider information input.
  4. Add the Extract Provider Name node to extract the provider's name from the provider information.
  5. Connect the Gen Match Explanation node to the outputs of both the Find Match Evidence and Extract Provider Name nodes.
  6. Finally, connect the Output node to the Gen Match Explanation node to finalize the workflow.
Created By
Lawrence Perera
Last Updated
August 14, 2025
Categories
Data extraction
Tools
No items found.

Discover more agents

Flag suspicious Stripe transactions in Slack
Automate KYC checks and send reports to Slack
Summarize my clients’ portfolios weekly
Review my contracts and generate risk summaries
Highlight NDA deviations and send alert to Slack
Review DPAs or privacy policies for compliance
Run review when new prior auth packets arrive
Review claims for compliance and errors
Generate personalized care plans from EHR
Pull call objections and update HubSpot contacts
Get weekly HubSpot deal health insights
Review my closed-lost HubSpot deals weekly
sucCCESS STORIES

Hear it from our customers

We know the power of AI, but how do we make it secure and ensure that we're not compromising privacy and security while still providing value? Vellum has been a big part of accelerating that experimentation part, allowing us to validate that a feature is high-impact and feasible.
Pratik Bhat
ai Product manager
We sped up AI development by 50 percent and decoupled updates from releases with Vellum. This allowed us to fix errors instantly without worrying about infrastructure uptime or costs.
Jordan Nemrow
Co-Founder & CTO @ Woflow
Vellum helped us quickly evaluate prompt designs and workflows, saving us hours of development. This gave us the confidence to launch our virtual assistant in 14 U.S. markets.
Sebi Lozano
Sr. Product Manager @ Redfin

FAQ

Build any AI agent with Vellum

Get started today and transform your business with intelligent automation
No items found.