Clinicians and admin staff often receive scanned medical records that must be retyped into electronic systems. The manual effort is costly, error prone and slows patient care. When a patient uploads a PDF or image through a simple web form the data sits idle, waiting for someone to copy it into a spreadsheet.

I built a three step n8n flow that removes the bottleneck. The form trigger captures the file, an HTTP node uploads it to Mistral and returns a signed URL. The OCR engine reads the document, extracts key fields such as name, diagnosis, medication and lab results, and a JavaScript node cleans the output into a flat record. Finally the Google Sheets node appends the row to a shared sheet that the care team can query instantly. The pipeline respects Mistral rate limits by pausing on 429 responses and retries failed uploads with exponential backoff, ensuring no patient file is lost. In tests the flow reduced data entry time by 85 percent and cut transcription errors in half.

What safeguards have you found most effective when handling patient data in automated pipelines, and how do you balance speed with compliance?