Hire the Right AI Developer to Integrate Your Healthcare Systems

Small practices often rely on manual data entry between their EHR (like Practice Fusion or Kareo) and their billing software. These platforms offer limited, point-to-point integrations that break easily. For example, a built-in scheduler integration might sync patient demographics but fail to pull insurance eligibility, forcing staff to re-enter data from a separate portal.

Consider a 15-person physical therapy clinic using an EHR for clinical notes and a separate system for billing. A patient updates their insurance information at check-in. The front desk staff updates the EHR, but must then manually log into the billing portal to update the same information. If they forget or make a typo, the claim gets rejected a week later, delaying payment by 30 days and requiring an hour of administrative work to fix.

The core problem is that each system has its own data schema and is not built for interoperability. EHRs are designed to be systems of record, not open platforms. Their APIs, if they exist, are often an afterthought and cannot handle the custom logic needed to map an appointment type in your scheduler to a specific CPT code in your billing system.

This manual "human API" costs thousands in wasted staff hours and introduces critical data entry errors that delay revenue collection. It pulls skilled workers away from patient care to perform repetitive data management tasks.

The first step is an audit of your existing systems. Syntora would map the data flow for a specific workflow, like patient intake or referral management. We identify what data lives where, how to access it (API, SFTP, database query), and the specific business rules for transformation. You receive a detailed architecture diagram and scope document before any code is written.

For system integration, a central FastAPI service running on AWS Lambda provides a secure, auditable hub. This service ingests data from one system, transforms it according to your rules using Python scripts, and sends it to the destination system. For processing unstructured data like referral faxes, the Claude API can extract structured information like patient name and reason for visit with over 98% accuracy. All data is encrypted in transit and at rest, and Supabase provides a HIPAA-compliant database for audit logs.

The delivered system is a private, automated pipeline that connects your tools. When a new patient appointment is created in your scheduler, the system would automatically query your billing platform for insurance eligibility within 2 seconds. You receive the complete source code, a runbook for maintenance, and a dashboard to monitor transaction volume. The system typically costs under $50 per month to operate on AWS.