Automate Insurance Verification and Payment Collection with AI Agents

Most small healthcare practices rely on the built-in tools within their Practice Management System (PMS) like DrChrono or Kareo. These systems offer eligibility checks, but they are often batch-processed overnight. This fails when a patient books a same-day appointment, forcing staff into a manual, multi-step process of logging into individual payer portals, re-entering patient data, and copy-pasting coverage details back into the PMS.

Consider a 10-person physical therapy clinic trying to verify a patient's Aetna plan. The front desk staff member opens a new browser tab, navigates to the Aetna portal, logs in, searches for the patient, and manually transcribes copay and deductible information. This 15-minute task, repeated dozens of times a day, is prone to data entry errors that lead to claim denials weeks later. For payment collection, the office manager receives a 20-page PDF Explanation of Payment from Medicare. They must manually read through the document, identify the patient responsibility for each line item, and then create individual patient invoices in the billing system. One typo can result in an incorrect bill and an angry phone call from a patient.

The structural problem is that PMS platforms are built as systems of record, not real-time automation engines. Their integrations are not designed for the on-demand, per-patient workflows that a busy front desk requires. Generic automation tools that scrape web pages are not a solution either. They are brittle, breaking silently whenever a payer updates their website's design, and they lack the specific logic to interpret complex healthcare documents like an EDI 835 remittance file.

The engagement would begin with an audit of your top 10-15 payers. We'd map out which ones offer real-time eligibility APIs (like Availity), which have web portals requiring browser automation, and which only provide PDF EOBs. This initial 3-day audit, using your sample data, determines the specific automation strategy for each payer and surfaces any data quality issues upfront.

The core system would be a HIPAA-compliant FastAPI service running on AWS Lambda. For payers with APIs, the service uses httpx for asynchronous calls, retrieving eligibility data in under 500ms. For portal-based checks, a Playwright script reliably navigates the payer website. The Claude API would be used to parse incoming PDF EOBs or EDI 835 files, extracting patient responsibility amounts and denial codes with over 98% accuracy. All data is stored in a Supabase Postgres database with row-level security to maintain a full audit trail.

The delivered system provides a simple web interface for your staff or an API that can integrate with your existing scheduler. Staff would enter a patient ID and see a clear summary of coverage, copay, and deductible status within 30 seconds. As remittance files arrive, the system automatically processes them and stages patient statements for a final human review before sending. You receive the complete Python source code and a detailed runbook for maintenance.