Describes observations that are derived by calculation from other observations, carrying the derivation rule or formula. It follows OM1 for calculated results (such as anion gap or LDL cholesterol) in MFN messages, providing receiving systems with the logic or reference for how the result is computed.
from zato.hl7v2.v2_9 import OM6
om6 = OM6()
om6.sequence_number_test_observation_master_file = '1'
om6.derivation_rule = 'BMI = weight_kg / (height_m ** 2)'How to construct and work with real-world OM6 segments.
Text rule referencing total cholesterol, HDL, and triglycerides results
from zato.hl7v2.v2_9 import OM6
om6 = OM6()
om6.sequence_number_test_observation_master_file = '1'
om6.derivation_rule = 'LDL = TC - HDL - (TG / 5)'Simple body-mass index formula tied to master-file sequence two
from zato.hl7v2.v2_9 import OM6
om6 = OM6()
om6.sequence_number_test_observation_master_file = '2'
om6.derivation_rule = 'BMI = weight_kg / (height_m * height_m)'Derived lipid summary built from total and HDL cholesterol for fitness programs
from zato.hl7v2.v2_9 import OM6
om6 = OM6()
om6.sequence_number_test_observation_master_file = '3'
om6.derivation_rule = 'Non-HDL = TC - HDL'Step-by-step guides for working with HL7 v2 in Zato.
OM5 lists bundled tests, while OM6 documents how a derived numeric result is computed from other OBX values for reporting and quality review.
Yes—spell out which upstream results feed the formula so interfaces can validate that required wellness markers arrived before publishing calculated values.
Assign a TX string with the plain-language or symbolic formula:
from zato.hl7v2.v2_9 import OM6
om6 = OM6()
om6.sequence_number_test_observation_master_file = '1'
om6.derivation_rule = 'BMI = weight_kg / (height_m ** 2)'OBX carries the published calculated value while OM6 explains its source math, which helps coaching and analytics tools audit screening outputs.
Use the same numbering scheme as other OMx segments in the master file so each calculated observation stays linked to its observation definition.
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.
Complete list of fields in the OM6 segment, HL7 v2.9.
| # | Python name | Datatype | Usage | Repeatable | Table |
|---|---|---|---|---|---|
| 1 | sequence_number_test_observation_master_file | NM | Optional | No | - |
| 2 | derivation_rule | TX | Optional | No | - |
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