US Health Insurance Cards API
Automate the extraction of critical data from US health insurance cards for streamlined patient onboarding, verification, and more
Extract critical insurance data in seconds
Pull structured data like member ID, group number, and insurance provider from any standard US health insurance card with just one API call.
Handle diverse formats with one model
Our model supports varied layouts, logos, and field placements found on cards from Aetna, Blue Cross, Cigna, UnitedHealthcare, and more.
Front & back processing
Upload both sides of the card in a single request and extract all available fields, including barcodes, issue dates, and plan codes.
Maxime Rihouey
Lead ML Engineer, Spendesk
Designed for software integration:
Built for developers
Developer-first documentation, API keys, webhook events, and testing sandbox included.
Fast and scalable
Handle thousands of insurance card scans daily with sub-second response times.
Custom workflows
Combine with other document types or post-processing rules to trigger downstream actions (e.g. form fill, database update).
Hosted or self-hosted
Use our fully managed cloud API or deploy the model in your own infrastructure.
Mindee helps healthcare teams streamline insurance card processing and minimize manual work:
- Reduce manual data entry in healthcare workflows
- Automate patient registration and insurance validation
- Integrate with your existing patient management systems
- Get consistent results even from low-quality scans or photos
Transform your workflow with:
One-click data capture
Automate form pre-fill from card scan to EMR system in a single step.
Real-time validation
Get immediate feedback if card data is missing, incomplete, or invalid.
Built-in error handling
Fallbacks and confidence scoring let you route edge cases to manual review efficiently.
End-to-end automation
Use with ID cards, prescriptions, and invoices to create full patient onboarding workflows.
Mindee enhances healthcare workflows by extracting key information from US health insurance cards instantly:
- Cut patient intake time in half
- Improve insurance data accuracy
- Ensure faster claims and reimbursement processing
- Free up staff from repetitive admin work
Purpose-built for healthcare
Trained specifically on US health insurance documents—no generic OCR.
99%+ accuracy
Achieve near-human precision in field extraction with continuous model updates.
Plug & play
No ML expertise needed—start extracting insurance data in under 5 minutes.
Scalable pricing
Pay only for what you process, with custom plans for enterprise volume.
Enterprise-grade security
HIPAA compliant, encrypted data in transit and at rest.
Proven in production
Used by healthcare SaaS companies, telemedicine apps, and clinics nationwide.
health insurance card
Start automating your fraud workflow today. Get started with a free trial or schedule a demo to learn more.
Frequently Asked Questions
Common questions about our intelligent document processing solutions.
How can I test the Health insurance card OCR API?
Our Health insurance card API is free to use and available to any user having an account on our platform.
To test our APIs, you only have to create a free account using this link, and you'll be able to drag and drop cards in the live interface to see the data extracted in real-time and JSON response. A demo page is also available here.
Is Mindee's Health insurance card OCR API free to use?
A free plan is available to everyone and allows you to perform 250 images processing per month for free. No credit card is required.
Above 250 images per month, the price per cards processed starts at $0.10 and can decrease to $0.01 per receipt depending on the monthly volume. See the pricing page for more information.
Health insurance card : What are the supported countries?
What are the supported countries?
Our Health insurance card OCR API is based on our computer vision technology that doesn't rely on text to extract the receipt data, but only on the image. This removes the language limitations.
The OCR was trained with Health insurance card from more than 50 countries and works on cards from all around the world for numeric fields, and all Latin alphabet countries for text ones.
Health insurance card : How complicated is it to integrate the API?
How complicated is it to integrate the API?
Mindee's API follows HTTP standards in order to allow any developer to integrate the Health insurance card OCR API into their applications easily.
We also offer a set of client libraries in all the main back-end languages, and an open-source UI toolkit that helps create front-end features. You can check out our open-source repository or our API documentation for more details.
Health insurance card : What is the OCR accuracy?
What is the OCR accuracy?
Our Health insurance card OCR's accuracy is above 90%, with precision above 95% for most of the fields. These performances are computed on a data set including more than 50 countries.
Testing our OCR API is free, all you need is an account. Feel free to drop Health insurance card in the live interface to see the OCR performance on your data.
Health insurance card : What's the average API response time?
What's the average API response time?
The processing time is around 1.3 seconds per page for pdfs and 0.9 seconds for a Health insurance card image.
We often improve this processing time and our target is below 500ms. Our goal is to make sure you can create real-time user experiences in your application.
Health insurance card : Does the OCR work on low-quality images?
Does the OCR work on low-quality images?
Yes, the OCR was trained on a lot of Health insurance card from a wide variety of layouts and image quality and learned to process the most complex ones.
We also use data augmentation to make sure that no blur or ink stains prevent the OCR from reading the data as long as it's readable.
Do you offer technical support?
We have a Slack community where you can ask your questions and chat with our team.
We don't do the integration in your infrastructure ourselves but we can set up a custom level of support on a per-case basis if needed.