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Segment

Application status change

Used to request or announce the start-up, shut-down, or migration of an HL7 application to a different CPU or file system. It appears in NMQ and NMD messages and carries the current and new application, facility, and CPU identifiers. Primarily used by application management tools to coordinate operational changes across networked healthcare systems.

9fields
1required
v2.9HL7 version
nsc.py
from zato.hl7v2.v2_9 import NSC

nsc = NSC()
nsc.application_change_type = 'U'
nsc.current_cpu = 'WELLNESS-SRV-01'
nsc.current_application = 'FITNESS-APP'

Build NSC segments in Python

How to construct and work with real-world NSC segments.

1

Wellness application startup

Application coming online

from zato.hl7v2.v2_9 import NSC

nsc = NSC()
nsc.application_change_type = 'U'
nsc.current_facility = 'WELLNESS-SRV-01'
nsc.new_fileserver = 'FITNESS-APP'
2

Nutrition system migration

Application moving to new server

from zato.hl7v2.v2_9 import NSC

nsc = NSC()
nsc.application_change_type = 'M'
nsc.current_cpu = 'NUTR-SRV-01'
nsc.current_fileserver = 'FS-OLD'
nsc.current_application = 'DIET-APP'
nsc.new_cpu = 'NUTR-SRV-02'
nsc.new_fileserver = 'FS-NEW'
nsc.new_application = 'DIET-APP'
3

Screening system shutdown

Application going offline

from zato.hl7v2.v2_9 import NSC

nsc = NSC()
nsc.application_change_type = 'D'
nsc.current_cpu = 'SCREEN-SRV-01'
nsc.current_fileserver = 'FS-SCREEN'
nsc.current_application = 'PREV-CARE-APP'

Learn by building

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

Frequently asked questions

NSC contains application status change information including state transitions and server details for monitoring wellness system changes.

Common change types include U (up/startup), D (down/shutdown), and M (migration). These track wellness application state transitions.

Use current and new fields to track the migration:

nsc.application_change_type = 'M'
nsc.current_cpu = 'OLD-SERVER'
nsc.new_cpu = 'NEW-SERVER'

NSC contains status changes while NST contains statistics. Both are used for monitoring wellness application health.

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.

NSC field reference

Complete list of fields in the NSC segment, HL7 v2.9.

#Python nameDatatypeUsageRepeatableTable
1application_change_typeCWERequiredNoHL70409
2current_cpuSTOptionalNo-
3current_fileserverSTOptionalNo-
4current_applicationHDOptionalNoHL70361
5current_facilityHDOptionalNoHL70362
6new_cpuSTOptionalNo-
7new_fileserverSTOptionalNo-
8new_applicationHDOptionalNoHL70361
9new_facilityHDOptionalNoHL70362

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Open source In Python