Message type

Collaborative care query

Supports collaborative care coordination between providers. Key segments include MSH, RF1. Care coordination platforms and clinical systems exchange this to share patient care information across organizational boundaries.

7segments

3required

1group

v2.9HL7 version

# Zato
from zato.hl7v2 import HL7Message

# An incoming message ..
raw = 'MSH|^~\&|SENDER|FAC|RCV|DEST|20260701||' \
      'CCQ^I19^CCQ_I19|MSG001|P|2.9\r' \
      'SFT|ACME^Software|v4.1|EHR System|BIN001'

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

# .. whose fields we can now access.
vendor = msg.sft.software_vendor_organization
version = msg.sft.software_certified_version_or_release_number

Python examples

Build and parse CCQ^I19 messages in Python

How to construct, send, receive, and extract fields from real-world CCQ^I19 messages.

Parse an incoming CCQ^I19 message

Demonstrates receiving and extracting key fields from a collaborative care query transaction

# Zato
from zato.hl7v2 import HL7Message

# An incoming message ..
raw = 'MSH|^~\&|SENDER|FAC|RCV|DEST|20260701||' \
      'CCQ^I19^CCQ_I19|MSG001|P|2.9\r' \
      'SFT|ACME^Software|v4.1|EHR System|BIN001'

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

# .. whose fields we can now access.
vendor = msg.sft.software_vendor_organization
version = msg.sft.software_certified_version_or_release_number

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||CCQ^I19^CCQ_I19|MSG00001|P|2.9\rRF1||ROUTINE^Routine^HL70283||20260401|20260430\rREL|1||HAS^Has^HL70948'
msg = HL7Message.parse(raw)

vendor = msg.sft.software_vendor_organization
version = msg.sft.software_certified_version_or_release_number

Beyond the mandatory MSH header, the required segments are: RF1, PRD. 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

CCQ^I19 segment composition

Segments that make up the CCQ^I19 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	`RF1`	Required	No	Referral information	-
5	`PRD`	Required	No	Provider data	PROVIDER_CONTACT
6	`CTD`	Optional	Yes	Contact data	PROVIDER_CONTACT
7	`REL`	Optional	Yes	Clinical relationship segment	-

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Open source In Python