Why a Developer Replaced Python HL7 Parsing with Mirth Connect in a FHIR Pipeline

A developer building a Maternity HL7-to-FHIR data pipeline initially attempted to handle all message parsing and transformation within a single Python FastAPI service. The approach broke down when tested against real-world maternity workflows, as hospital systems transmit HL7 data over MLLP, a TCP socket protocol requiring specific framing and acknowledgment handling rather than standard HTTP responses. Replicating MLLP support in Python demanded maintaining a custom TCP server alongside the API layer, adding significant infrastructure complexity unrelated to the core transformation logic. HL7's nuanced encoding rules — including component separators, repeating fields, and escape characters — also caused silent data errors when handled via basic string splitting. Switching to Mirth Connect resolved both issues, as it natively manages MLLP connections and provides a mature XML-tree-based HL7 parser that correctly handles edge cases out of the box.