The mapping template extracts the patient FHIR resource from a FHIR bundle and converts it to
relational format, and the attached file includes an
intelligent structure model
that
contains the schema for the conversion. To create a different
intelligent structure model
, you
can use a different XML file as input to the
intelligent structure model
and
regenerate the schema.
The following image shows the transformations in the mapping template:
The targets are parameterized in the mapping template, so you can perform one of the
following tasks:
Replace the parameters with specific
connections and target objects in the Target transformations.
Leave the parameters in the Target
transformations and specify targets in the
mapping
task or use a parameter file.
The mapping template contains the following transformations:
1. Source transformation
The Source transformation uses a FHIR connection to submit a GET request for a patient
resource by querying patient details. The sample query references a
patient’s given name.
2. Expression transformation
The Expression transformation removes special characters in the XML data that
can cause validation issues, such as converting ampersands to
&
.
3. Data Services transformation
The Data Services transformation uses the FHIR validation service from the data services
repository to validate the FHIR resource.
4. Target transformations to troubleshoot validation errors
The Target transformations that are downstream of the Data Services transformation write
errors and error flags to target files. If the FHIR validation service finds
errors in the incoming FHIR resource, you can use the error messages to
troubleshoot the upstream data flow. To write the data to the target files,
you can use any target connection that writes XML data, such as a flat file
or relational connection that can hold XML data.
5. Structure Parser transformation
The Structure Parser transformation uses the
intelligent structure model
to convert the XML data to relational
format.
6. Target transformations to write relational data
The Target transformations write the patient elements to a relational target, such as the
patient, patient identifier, and patient address elements. To write the data
to a relational target, use a relational connection.
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