Automate Medical Administrative Tasks with Custom AI

Many practices use generic form builders like Jotform or Typeform for patient intake. While these tools collect information, they are not HIPAA-compliant on standard plans, and they do not integrate with Electronic Health Record (EHR) systems. They simply email a PDF to the front desk, creating a new manual data entry task that is both slow and error-prone.

Consider a 10-person cardiology practice using a PDF intake form. A staff member spends 20 minutes deciphering and re-typing patient information into Practice Fusion before each new appointment. Last month, they mistyped a single digit in an insurance group number, causing a $1,200 claim to be denied. The appeal process took three weeks and multiple phone calls to resolve, delaying revenue and wasting valuable staff time.

The fundamental failure is that these tools solve data collection, but not data integration. The gap between the form-builder and the EHR is bridged by a person, making them a human API. This manual step is the primary source of data entry errors, appointment delays, and denied insurance claims. Business-critical healthcare workflows require production-grade engineering, not just a prettier form.

Syntora would start an engagement by auditing your existing intake forms field-by-field, collaborating with your staff to understand the specific data points required for new patient records. We would connect to your Electronic Health Record (EHR) system, often utilizing an API key you provide from systems like Practice Fusion or Kareo, to precisely define the data structure needed for patient data ingestion. Based on this schema, Syntora would design and provision tables within a HIPAA-compliant Supabase database instance, ensuring a clear and auditable destination for every piece of data.

Next, Syntora would develop a secure web form, which could be hosted on a platform like Vercel. When a patient submits this form, the data would be routed to a FastAPI service, designed to run efficiently on AWS Lambda. This service would invoke the Claude API with a precisely engineered prompt, intended to parse unstructured text – such as a patient's detailed medical history – into structured JSON. This structured JSON would then be validated against your EHR's schema. This extraction and validation process is engineered for rapid completion.

The validated data would be temporarily stored in Supabase. A subsequent AWS Lambda function would then be triggered, responsible for formatting the data according to your EHR's specific API requirements and initiating the creation of a new patient record. Should the API call encounter an error, the record would be flagged in Supabase, and a notification would be securely sent to designated staff, preventing any data loss.

Syntora would also develop a simple, private review dashboard for your staff. This dashboard would highlight any fields where the Claude API expressed lower confidence, enabling staff to quickly approve or correct entries. This human-in-the-loop design ensures data accuracy before commitment to the EHR. The cloud infrastructure supporting this architecture, including AWS and Supabase components, is designed for cost efficiency, with typical operating costs estimated below $100 per month, and includes full CloudWatch logging to support HIPAA audit trails.

A typical engagement for this type of system, from initial discovery to deployment, would span 4 to 8 weeks, depending on the complexity of your forms and EHR integration. Your team would need to provide access to EHR documentation, sample forms, and active participation in discovery and testing phases.