Claims Management Automation
We pull the information needed for claims, check it against your billing rules, and send it through your existing submission process. The automation records responses and flags rejected claims or missing updates. Your team handles the cases that need review.
Illustration of a claims run. Three completed encounters enter the claim queue. For two, the automation pulls the patient, provider, service and charge data, checks the required fields, submits the claim and saves the acceptance response. The third is missing a required provider identifier, so it is stopped before submission and sent to staff with the reason. The example ends with 2 accepted for processing and 1 needing information. No payment is shown.
How Gentem Health automated claim preparation
Gentem Health's team copied and corrected billing data from several EHRs. We built a daily transfer into its billing database. The automation pulls the fields needed for claim preparation and formats them for the receiving system.
Measured results
Results from Gentem Health's data-preparation project. These figures do not measure how quickly a payer pays a claim.
SuperBill reduced its document-to-claim cycle from about 24 hours to about 7 hours by turning uploaded documents into claim-ready records. Read the SuperBill case study
The tasks from claim preparation to payer follow-up.
A claim needs complete information, a submission, and a record of what happened next. These are the tasks we automate.
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01Prepare
Pull the information already recorded for the visit.
- Find completed encounters or claims ready for preparation.
- Pull patient, provider, insurance, service, and charge details from your systems.
- Read existing billing documents where information arrives in PDFs or images.
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02Check
Check the required fields before submission.
- Check that required identifiers, service dates, codes, and charges are present.
- Apply the formatting and billing checks agreed with your team.
- Flag missing information, conflicting records, or possible duplicates.
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03Submit
Send the claim and keep its response.
- Transfer claim-ready data into your billing system or clearinghouse.
- Submit through the supported process and capture acknowledgments.
- Save claim references, submission times, and rejection messages.
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04Follow up
Keep the claim record current.
- Check available payer statuses on an agreed schedule.
- Match responses to the right claim and update your records.
- Send rejected claims, missing acknowledgments, and overdue updates to staff.
We set up the workflow for your systems, payers, and rules. Your team handles missing information and cases that need billing or coding review.
A claim accepted for processing has not necessarily been approved or paid. The payer still reviews it.
Claims automation usually pays off when most of these are true.
- Your team prepares or submits many claims each day.
- Staff copy encounter details between EHRs, documents, and billing systems.
- Someone checks clearinghouse and payer responses by hand.
- Most claims follow known steps, and you know which cases need billing or coding review.
What affects your savings
- How many claims and documents you process each month
- How long preparation, submission, and status checks take by hand
- Which EHR, clearinghouse, and payer connections are available
- How often claims need missing information or specialist review
- What it costs to build and maintain
The return is different for every organization. Schedule a call and we'll give you a quick, honest estimate of whether it's worth it for yours.
Schedule a callThe automation moves claim information between your systems and payers.
Your staff keep using the systems they know. We use direct connections and clearinghouses where available, or UiPath and Python for work in portals and desktop apps. AI can read uploaded billing documents. Your team reviews information that is missing, unclear, or needs coding judgment.
Example of the automation between three places. It pulls complete claim records from the EHR or billing system, submits them through the clearinghouse and writes the acknowledgments back. The third claim is missing a provider identifier, so it goes to the staff review queue before submission. Later, a claim status response shows the first claim as pending payer review. No payment is shown.
Monitored and maintained by us. We check the runs and update the workflow when payer connections or your systems change.
Denial appeals and payment posting are separate workflows. Routine correction of rejected claims can be added where the source data and payer rules are clear.
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.
Is automating your claims work worth it?
Book a 30-minute call with Karl, our CTO. If you'd rather write, send us a message.
Walk me through how your team prepares, submits, and tracks claims. Within the first 15 minutes, we can usually tell whether automation makes sense. We'll discuss the work involved and what we'd need to estimate the cost.
Karl