Message type

Unsolicited population / location-based laboratory observation

Delivers unsolicited population or location-based laboratory observations. The OBR and OBX segments carry the observation results for public health surveillance.

40segments

13required

6groups

v2.9HL7 version

# Zato
from zato.hl7v2 import HL7Message

# An incoming message ..
raw = 'MSH|^~\&|SENDER|FAC|RCV|DEST|20260701||' \
      'OPU^R25^OPU_R25|MSG001|P|2.9\r' \
      'OBR|1||ORD001\r' \
      'OBX|1|NM|2345-7^Glucose^LN||95|mg/dL|70-100'

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

# .. whose fields we can now access.
order_id = msg.obr.placer_order_number
test = msg.obr.universal_service_identifier
value = msg.obx.observation_value
units = msg.obx.units

Python examples

Build and parse OPU^R25 messages in Python

How to construct, send, receive, and extract fields from real-world OPU^R25 messages.

Parse an incoming OPU^R25 message

Demonstrates receiving and extracting key fields from a unsolicited population / location-based laboratory observation transaction

# Zato
from zato.hl7v2 import HL7Message

# An incoming message ..
raw = 'MSH|^~\&|SENDER|FAC|RCV|DEST|20260701||' \
      'OPU^R25^OPU_R25|MSG001|P|2.9\r' \
      'OBR|1||ORD001\r' \
      'OBX|1|NM|2345-7^Glucose^LN||95|mg/dL|70-100'

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

# .. whose fields we can now access.
order_id = msg.obr.placer_order_number
test = msg.obr.universal_service_identifier
value = msg.obx.observation_value
units = msg.obx.units

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||OPU^R25^OPU_R25|MSG00001|P|2.9\rPV1|1|I|MED^201^A^^^MAIN||||1234^CHEN^DAVID^L^^^MD|5678^PATEL^NINA^R^^^MD|||MED|||||||VN-90001|||||||||||||||||||||20260401\rPV2|||^Routine checkup\rPRT|1||AT^Attending||1234^CHEN^DAVID^L^^^MD'
msg = HL7Message.parse(raw)

order_id = msg.obr.placer_order_number
test = msg.obr.universal_service_identifier

Beyond the mandatory MSH header, the required segments are: PV1, OBX, NK1, PID, OBX, SPM, OBX, SAC. 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

OPU^R25 segment composition

Segments that make up the OPU^R25 message, in order. Groups are shown with their child segments.

#	Segment	Usage	Repeats	Description	Group
1	`MSH`	Required	No	Message header	-
2	`ARV`	Optional	Yes	Access restriction	-
3	`SFT`	Optional	Yes	Software segment	-
4	`UAC`	Optional	No	User authentication credential	-
5	`NTE`	Optional	No	Notes and comments	-
6	`PV1`	Required	No	Patient visit	-
7	`PV2`	Optional	No	Patient visit - additional info	-
8	`PRT`	Optional	Yes	Participation information	-
9	`OBX`	Required	No	Observation result	PATIENT_VISIT_OBSERVATION
10	`NTE`	Optional	Yes	Notes and comments	PATIENT_VISIT_OBSERVATION
11	`PRT`	Optional	Yes	Participation information	PATIENT_VISIT_OBSERVATION
12	`NK1`	Required	Yes	Next of kin / associated parties	ACCESSION_DETAIL
13	`PID`	Required	No	Patient identification	ACCESSION_DETAIL
14	`PD1`	Optional	No	Patient additional demographic	ACCESSION_DETAIL
15	`PRT`	Optional	Yes	Participation information	ACCESSION_DETAIL
16	`OH1`	Optional	Yes	Employment status	ACCESSION_DETAIL
17	`OH2`	Optional	Yes	Past or present job	ACCESSION_DETAIL
18	`OH3`	Optional	No	Usual work	ACCESSION_DETAIL
19	`OH4`	Optional	Yes	Combat zone work	ACCESSION_DETAIL
20	`ARV`	Optional	Yes	Access restriction	ACCESSION_DETAIL
21	`OBX`	Required	No	Observation result	PATIENT_OBSERVATION
22	`PRT`	Optional	Yes	Participation information	PATIENT_OBSERVATION
23	`NTE`	Optional	Yes	Notes and comments	PATIENT_OBSERVATION
24	`SPM`	Required	No	Specimen	ACCESSION_DETAIL
25	`OBX`	Required	No	Observation result	SPECIMEN_OBSERVATION
26	`PRT`	Optional	Yes	Participation information	SPECIMEN_OBSERVATION
27	`NTE`	Optional	Yes	Notes and comments	SPECIMEN_OBSERVATION
28	`SAC`	Required	No	Specimen container detail	CONTAINER
29	`INV`	Optional	No	Inventory detail	CONTAINER
30	`OBR`	Required	No	Observation request	ORDER
31	`PRT`	Optional	Yes	Participation information	ORDER
32	`ORC`	Required	No	Common order	ORDER
33	`PRT`	Optional	Yes	Participation information	ORDER
34	`NTE`	Optional	Yes	Notes and comments	ORDER
35	`PRT`	Optional	Yes	Participation information	ORDER
36	`TQ1`	Required	No	Timing / quantity	ORDER
37	`TQ2`	Optional	Yes	Timing / quantity relationship	ORDER
38	`OBX`	Required	No	Observation result	ORDER
39	`PRT`	Optional	Yes	Participation information	ORDER
40	`NTE`	Optional	Yes	Notes and comments	ORDER

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