Message type

Add personnel record

Manages personnel records in the staff master file. The STF segment carries staff identification and demographic details. Human resources and credentialing systems consume this.

14segments

3required

0groups

v2.9HL7 version

# Zato
from zato.hl7v2 import HL7Message

# An incoming message ..
raw = 'MSH|^~\&|SENDER|FAC|RCV|DEST|20260701||' \
      'PMU^B01^PMU_B01|MSG001|P|2.9\r' \
      'STF|STF001||CHEN^DAVID^L|MD'

# .. parsed into a Python object ..
msg = HL7Message.parse(raw)

# .. whose fields we can now access.
staff_id = msg.stf.primary_key_value_stf
staff_name = msg.stf.staff_name

Python examples

Build and parse PMU^B01 messages in Python

How to construct, send, receive, and extract fields from real-world PMU^B01 messages.

Parse an incoming PMU^B01 message

Demonstrates receiving and extracting key fields from a add personnel record transaction

# Zato
from zato.hl7v2 import HL7Message

# An incoming message ..
raw = 'MSH|^~\&|SENDER|FAC|RCV|DEST|20260701||' \
      'PMU^B01^PMU_B01|MSG001|P|2.9\r' \
      'STF|STF001||CHEN^DAVID^L|MD'

# .. parsed into a Python object ..
msg = HL7Message.parse(raw)

# .. whose fields we can now access.
staff_id = msg.stf.primary_key_value_stf
staff_name = msg.stf.staff_name

Tutorials

Learn by building

Step-by-step guides for working with HL7 v2 in Zato.

MLLP

Receive and parse HL7 v2 messages

Set up an MLLP channel, parse incoming messages, and respond with acknowledgments.

Start tutorial Build

Build and send HL7 v2 messages

Construct HL7 v2 messages from scratch using typed segment classes and send them over MLLP.

Start tutorial

FAQ

Frequently asked questions

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||PMU^B01^PMU_B01|MSG00001|P|2.9\rEVN|B01|20260401120000\rSTF|STF-001||CHEN^DAVID^L^^^MD|||M\rPRA|1234\rORG|1||MED^Medicine^HL70454\rAFF|1|AMA^American Medical Association\rLAN|1|EN^English^HL70296\rEDU|1|MD^Doctor of Medicine^HL70360'
msg = HL7Message.parse(raw)

staff_id = msg.stf.primary_key_value_stf
staff_name = msg.stf.staff_name

Beyond the mandatory MSH header, the required segments are: EVN, STF. 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.

Reference

PMU^B01 segment composition

Segments that make up the PMU^B01 message, in order. Groups are shown with their child segments.

#	Segment	Usage	Repeats	Description	Group
1	`MSH`	Required	No	Message header	-
2	`SFT`	Optional	Yes	Software segment	-
3	`UAC`	Optional	No	User authentication credential	-
4	`EVN`	Required	No	Event type	-
5	`STF`	Required	No	Staff identification	-
6	`PRA`	Optional	Yes	Practitioner detail	-
7	`ORG`	Optional	Yes	Practitioner org unit	-
8	`AFF`	Optional	Yes	Professional affiliation	-
9	`LAN`	Optional	Yes	Language detail	-
10	`EDU`	Optional	Yes	Educational detail	-
11	`CER`	Optional	Yes	Certificate detail	-
12	`NK1`	Optional	Yes	Next of kin / associated parties	-
13	`PRT`	Optional	Yes	Participation information	-
14	`ROL`	Optional	Yes	Role	-

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Open source In Python