Increase Medical Billing Accuracy with Custom AI

Most small healthcare practices use a Practice Management System (PMS) like Kareo or DrChrono for billing. These platforms are excellent for managing patient schedules and submitting structured claim forms (the CMS-1500). Their weakness is the gap between the doctor's unstructured clinical notes and the structured codes required for reimbursement. The PMS cannot read a three-page operative report and determine if a -22 modifier for increased procedural services is justified.

Consider a 15-person orthopedic group where a biller processes 70 claims a day. For each claim, they must manually read the physician's notes to ensure the billed CPT codes are fully supported. If a surgeon documents an 'unusually difficult dissection' but the biller misses it, the practice loses out on legitimate revenue. Conversely, if the biller incorrectly adds a modifier without clear documentation, the claim is denied, delaying payment by 30 to 90 days and requiring hours of rework.

The structural problem is that PMS and EMR systems are databases with forms on top. Their architecture is designed to store and retrieve structured data, not to interpret the nuances of human language in clinical narratives. They rely entirely on the biller to perform the cognitive work of translating a complex medical story into a precise set of codes. This manual process is slow, prone to error, and creates a significant compliance risk.

The first step is a discovery process focused on your denial patterns. Syntora would start by auditing a de-identified set of your 100 most recent claim denials to pinpoint the most frequent and costly error types. We would map your entire workflow, from the moment a physician finalizes a note in your EMR to the point a claim is sent to the clearinghouse. This audit produces a clear plan targeting your specific revenue leaks.

The technical approach involves a HIPAA-compliant pipeline built on AWS. An AWS Lambda function would trigger when a new clinical note is saved. The note's text is sent to the Claude API, which is covered by a Business Associate Agreement (BAA), to extract key medical entities, procedures, and diagnoses. A FastAPI service then cross-references this extracted information against a Supabase database of CPT/ICD-10 codes and payer-specific rules. The entire process, from note ingestion to code suggestion, would take under 5 seconds.

The delivered system is a secure web application where your billers review claims before submission. The interface displays the clinical note side-by-side with AI-suggested codes. Each suggestion is linked to the exact sentences in the note that provide justification. Billers can accept, reject, or modify suggestions before pushing the finalized claim to your PMS. This provides a full audit trail and keeps your expert staff in control.