Facility

FAC identifies a facility involved in a product experience report - manufacturer, distributor, or user facility. It carries the facility identifier, type, telecommunication details, and signature authority information for regulatory documentation.

The facility_id_fac field uses the EI (entity identifier) datatype:

from zato.hl7v2.v2_9 import FAC, EI

fac = FAC()
fac.facility_id_fac = EI(
    entity_identifier='FAC-001',
    namespace_id='MFG_SITE',
    universal_id_type='LOCAL'
)

The facility_telecommunication field uses the XTN (extended telecommunication) datatype:

from zato.hl7v2.v2_9 import FAC, XTN

fac = FAC()
fac.facility_telecommunication = XTN(
    telecommunication_use_code='PRN',
    telecommunication_equipment_type='PH',
    country_code='1',
    area_city_code='555',
    local_number='5551234'
)

The facility_type field uses HL7 table 0331 to classify the facility role:

from zato.hl7v2.v2_9 import FAC

fac = FAC()

# M = Manufacturer
fac.facility_type = 'M'

# D = Distributor
fac.facility_type = 'D'

# U = User facility
fac.facility_type = 'U'

Use signature_authority_title and signature_authority_telecommunication to identify the responsible person:

from zato.hl7v2.v2_9 import FAC, XTN

fac = FAC()
fac.signature_authority_title = (
    'Plant Manager'
)
fac.signature_authority_telecommunication = XTN(
    telecommunication_use_code='PRN',
    telecommunication_equipment_type='PH',
    country_code='1',
    area_city_code='555',
    local_number='5551235'
)

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.