Healthcare Document Processing Automation
We turn faxes, scanned forms, PDFs and images into checked data for your EHR, LIS or billing system. The automation reads the document, extracts the fields you need and sends unclear or incomplete records to your team.
Illustration with three made-up documents. The automation reads a referral fax and a superbill PDF, checks their required fields and saves the extracted data. A scanned form has an unreadable service date and goes to staff review. Two records are saved and one needs review.
From uploaded documents to claim-ready records
SuperBill's team reviewed uploaded PDFs and images by hand. We built a workflow that reads the documents, structures the claim data and routes exceptions to specialists.
Measured results
Results from SuperBill's document-processing workflow. The roughly 70% reduction measures preparation time, not payer reimbursement time.
From incoming documents to usable records.
Referrals, requisitions, intake forms, superbills and payer correspondence. We scope the document types and required fields with your team.
01Read
Collect documents from the places you already use.
- Receive files from your existing fax, email or upload process.
- Read text from faxes, scans, PDFs and images.
- Keep the source document with the extracted information.
02Extract
Capture the fields your next task needs.
- Extract patient, provider, insurance and billing details already present in the document.
- Structure the data for the receiving system.
- Use the model and extraction instructions selected for your documents.
03Check
Check the result against your rules.
- Check required fields and formatting.
- Flag unreadable scans, missing fields and conflicting information.
- Route cases that need judgment to staff.
04Write
Save checked data where your team works.
- Transfer the data and source document into your EHR, LIS or billing system.
- Use an API or screen automation for the connection.
- Route the record to the next agreed workflow.
Your team reviews unclear information. Document extraction prepares existing information for the next task; claim submission and authorization decisions remain separate workflows.
Document automation usually pays off when most of these are true.
- Your team reads many faxes, scans or PDFs each day.
- Staff copy the same fields into an EHR, LIS or billing system.
- The required information and validation rules are clear.
- You know which exceptions need staff review.
What affects your savings
- How many documents you process each month
- How long reading and data entry take by hand
- Document quality and the range of formats
- How often a record needs staff review
- Model usage, integration and maintenance costs
The return is different for every organization. We'll discuss the work involved and what we'd need to estimate the cost.
Schedule a callYour documents, models and systems.
Illustration of document processing between three places: your document inbox, the automation and your receiving system. Two documents have readable required fields and their data is saved. The third has an unreadable service date and is sent to staff review.
Monitored and maintained by us. We check the runs and update the workflow when document formats or your systems change.
We adjust extraction instructions and validation rules, then check the results again. The receiving system can use an API or screen automation. Cases the workflow cannot reliably handle go to staff.
Patient data (PHI)
What happens to your patient data
Your data is safe.
- Where it runs
- On a machine you own: usually a virtual machine on your side, or your own AWS or Azure account.
- What we store
- We don't store patient data. The automation reads it, uses it and writes the result back. In the rare case PHI has to be in transaction data, it's encrypted.
- Who can access it
- Only the developer who builds and maintains the automation. On your machine, you decide who else gets access.
- What we sign
- A BAA before we see any patient data. AI runs on AWS, Azure or Google under BAAs, and your data isn't used to train models.
Which documents slow your team down?
Book a 30-minute call with Karl, our CTO. If you'd rather write, send us a message.
Walk me through the documents your team reads by hand and where the data needs to go. We'll discuss what can be automated and what we'd need to estimate the cost.
Karl