Post detail financial transaction - expanded

Use the HL7v2 message parser to extract the typed structure. The parsed message gives you direct access to every segment and field by name.

from zato.hl7v2 import HL7Message

raw = 'MSH|^~\&|SENDER|FACILITY|RECEIVER|DEST|20260401120000||DFT^P11^DFT_P11|MSG00001|P|2.9\rEVN|P11|20260401120000\rPID|1||MRN-10045||JOHNSON^SARAH^M||19880612|F|||100 Oak Lane^^Portland^OR^97201\rPRT|1||AT^Attending||1234^CHEN^DAVID^L^^^MD\rPD1|||Family Health Clinic^^12345\rROL|1|AD|AT^Attending^HL70443|1234^CHEN^DAVID^L^^^MD\rDB1|1||N\rDRG|'
msg = HL7Message.parse(raw)

name = msg.pid.patient_name
dob = msg.pid.date_time_of_birth

Beyond the mandatory MSH header, the required segments are: EVN, PID, ORC, TQ1, OBR, OBX, DG1, IN1. Optional segments provide additional detail when available.

Zato connects to any system that speaks HL7v2 over MLLP or FHIR over REST. This includes Epic, Cerner, Meditech, Allscripts, and other EHR platforms.

Yes, Zato has built-in MLLP support for sending and receiving HL7v2 messages. MLLP channels handle the framing protocol automatically.

Zato supports HL7 v2.9, which is backward compatible with earlier versions including v2.3, v2.5, and v2.7. Standard segments and datatypes are available as typed Python classes.

Yes. Zato handles both HL7v2 and FHIR natively, so you can parse v2 messages and build FHIR resources with IG-specific extensions in the same service. Typed Python classes are available for both protocols, including extensions from US Core, UK Core, Da Vinci, and other Implementation Guides.