Mappings

Overview

Data Mappings are configured data conversions for an integration workflow. They take an input Data Type and convert it to a different output Data Type.

Data Mapping input:output can be 1:1, 1:many, or many:1.

Some examples of standard data mappings are:

• HL7 v2.x ADT message -> FHIR Patient Resource
• Custom JSON Document -> FHIR Patient & FHIR Document Resource
• HL7 v2.x SIU message -> Custom JSON Document
• HL7 v2.x SIU message -> FHIR Patient & FHIR Appointment Resource

Intely Data Mappings can be customized to meet your specific workflow needs and set up through a point-and-click configuration.

Example Data Mapping:

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Data Filters

Filters provide a method to specify the selection of data in a payload. The filters in Intely use logical operators and the fields in a data type to qualify a specific field value.

This can be extremely helpful when working with a large bundle of data or a data structure that may have generic, repeating properties.

Filters are available to set up on each field mapping and will present for the user after dragging an input field to an associated output field.

For example, If I wanted to get the Patient Email from this payload, I would get the email from the Field[Text] value WHERE the Field[Name] = "Patient Contact Email".

"Fields": [
    {
        "Name": "Patient Contact Email",
        "Type": "string",
        "Text": "[email protected]",
        "Page": 1,
        "Confidence": 0.99
    },
    {
        "Name": "Patient Last Name",
        "Type": "string",
        "Text": "Daniel",
        "Page": 0,
        "Confidence": 0.941
    }]

Data Crosswalks

Crosswalks provide a simple way to convert individual field values on the fly during during a mapping. Source and destination systems may have different ID's, reference values, or any other data that need to map to each other during a conversion.

Crosswalks are available to set up on each field mapping and will present for the user after dragging an input field to an associated output field.

For example, if a source system produces a User Name, but the destination system expects a User ID, a Crosswalk comes in handy. When John Smith is present in a particular field, the mapping will convert the value to 123 for the destination system.

This is a simple example but shows how Crosswalks can be applied to many types of field translations in a mapping.