Video Key Moments
Building an EDI 837 Claim Interface for Analytics and Reporting
In this quick tour you see how to take an inbound EDI 837 claims feed, normalize it on the PilotFish assembly line, map it into a reusable canonical patient structure then fan it out to multiple targets for analytics, reporting and operational systems. The demo focuses on an 837 route inside the eiConsole, but the same pattern applies to other HIPAA transactions, HL7, FHIR and JSON.
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30-second summary
- Use a single aggregation route to receive HL7, EDI, FHIR and JSON feeds into one analytics pipeline
- Convert EDI 837 to XML automatically, then map into a canonical patient schema with a 3-pane graphical data mapper
- Reuse mappings for different trading partners by changing source formats, not target logic
- Test routes inline with real EDI 837 files and watch transactions flow step by step across stages
- Emit both database statements and JSON messages from the same route for downstream analytics, APIs or data lakes
837 Aggregation Route for Analytics and Reporting
The demo begins in an aggregation route built for analytics and reporting. Several upstream feeds converge on this route: some HL7 messages, some X12 EDI transactions, some FHIR payloads and JSON. For this video, the focus stays on the EDI 837 claims feed.
On the main assembly line screen you see:
- Source Systems on the left, where each row represents a way of getting data from a sender
- Target Systems on the right, where each row represents where processed data is delivered
- The familiar 7-stage assembly line in the middle that shows every step from Listener to testing
Regardless of format or protocol, every transaction moves through the same configuration-driven flow where it is ingested, normalized, routed and delivered with full visibility.
Single Assembly Line for Mixed Formats
The route illustrates one of PilotFish’s core design goals: every interface looks and behaves the same, even when formats differ.
Within this EDI 837 claim interface you can:
- Attach different Listeners for HL7 LLP, file drops, web services, S3 buckets, message queues or databases
- Declare the inbound format as EDI 837 in the Source Transform so the platform converts it into XML automatically
- Apply routing rules based on payer, facility, transaction attributes or envelope values
- Plug in validation or enrichment Processors without changing the rest of the pipeline
This gives technical teams a consistent way to onboard new partners or add new data sources without reworking the entire route.
Drag & Drop EDI 837 Data Mapping
The heart of this quick tour is the eiConsole Data Mapper, a 3-pane graphical mapping tool that turns EDI 837 XML into a patient-centric canonical model.
In the mapper you see:
- Source tree on the left representing EDI 837 in XML form, including loops like 2000B and 2000BA
- Target tree on the right showing a compact patient canonical XML structure used downstream for analytics and reporting
- Mapping pane in the center, where you drag elements from Source to Target and compose transformation logic
For example, to populate the patient’s last name field, you simply navigate to the correct loop in the source tree, select the NM103 element, then drag it into the center pane to bind it to the patient’s last name in the target structure.
The mapper includes a tools palette across the top that supports:
- Functions for string and numeric manipulation
- Conditional logic and lookups
- Reusable templates and macros for common 837 patterns
This approach lets you design a single canonical model, reuse it across routes and apply different EDI 837 variations or trading partner guides with minimal change.
Inline Testing with Real EDI 837 Data
The video then switches to testing mode to show how a real EDI 837 claim moves through the route.
From the test view you can:
- Load a saved 837 sample file directly into the route
- Run the test and watch the transaction flow left to right through each stage
- Inspect XML at each step to confirm the EDI has been parsed, mapped and routed correctly
Inline testing makes it easy to debug mappings, validate configurations and confirm that changes behave as expected before deployment to eiPlatform.
Multi-Target Outputs: Database Statements and JSON
At the Target Transform and Transport stages, the same normalized 837 data is fanned out into multiple outputs:
- One branch generates database statements that can load claims, patients or encounters into relational or NoSQL stores
- Another branch generates JSON documents suitable for APIs, streaming platforms or cloud analytics services
You configure each target independently while reusing the same canonical mapping. This ensures consistent semantics across systems and avoids duplicate logic in every downstream endpoint.
Once the route is ready, you can export it for deployment to eiPlatform, where it runs unattended and can be monitored in eiDashboard. PilotFish deployments work well in containerized environments such as Docker, which simplifies scaling and operations.
Why PilotFish for EDI 837 Claim Interfaces
- Model your 837 interfaces visually with an assembly line user interface that is easy to learn for new team members
- Keep mappings maintainable with a canonical patient structure and reusable transformation logic
- Support mixed-format environments where HL7, FHIR, JSON and X12 travel through the same route design patterns
- Add new trading partners quickly by adjusting Listeners and Source formats instead of rebuilding entire interfaces (see also Trading Partner Management)
- Deploy to eiPlatform for reliable, unattended execution with operational visibility through eiDashboard
FAQ
Yes. The demo shows one 837 aggregation route, but the same mapping and canonical model can be reused for other clearinghouses, payers or providers by configuring additional Listeners and Source transforms.
You can configure Listeners and Source transforms for HL7 messages, FHIR resources, CSV files or JSON APIs. Each format is normalized to XML, ensuring consistent mapping regardless of the original payload.
The route in the video is built with configuration and visual mapping in the eiConsole. You select Listeners and Transports from menus, then design mappings using drag & drop. Custom code is optional for edge cases, not required for the main flow.
Yes. You can define multiple Target Systems in the same route. For example, you might send data to a claims warehouse, a downstream adjudication engine, and a JSON-based analytics pipeline using a single mapped canonical model.
Check out our FAQ pages for more.
Building an EDI 837 Claim Interface – Quick Tour
This route is set up as an aggregation interface for analytics and reporting. Several different data feeds arrive here: some HL7, some EDI, some FHIR and some JSON. In this quick tour, the focus is on the EDI feed.
On the main assembly line screen, the Source Systems are on the left. You can think of each row on that side as a place where you get data from. Target Systems are on the right, which is where the data is sent to its destinations. No matter which system sends the data or which format it uses, every transaction moves through the same assembly line where it is ingested, transformed, routed and finally delivered.
Using the Data Mapper
Next, the demo opens the Data Mapper. This is the 3-pane graphical drag & drop mapping tool inside the eiConsole.
On the left, you see the source format. In this case, that is the EDI 837 represented in XML, where you can see all of the loops and segments. On the right is a smaller patient canonical XML structure that the route will produce for downstream use.
To build the mapping, you drag fields from the source tree into the center pane and connect them to the target fields. The tools palette across the top provides functions for more complex mapping logic when needed.
For example, the demo maps the patient’s last name. It navigates through the source tree to the 2000B and 2000BA loops, then selects NM103. That field is dragged into the center pane and linked to the patient’s last name element on the target side. Once that connection is made, the mapping is in place.
Testing with a Real EDI 837 File
The next step in the video is to switch into testing mode and run a real 837 test file through the route.
A saved EDI 837 sample is loaded into the test harness. When the test is started, the user can watch the transaction move through the stages from left to right. At each step the transformed data can be inspected so it is easy to confirm that the EDI has been converted into XML correctly, mapped into the patient canonical model and routed to the right targets.
Delivering to Database and JSON Targets
The demo concludes by showing the outputs. In this route, the EDI 837 data is transformed into XML, mapped into the canonical structure, and then converted into database statements for one target. The same mapped data is also turned into JSON for another target system that expects a different file format.
Both outputs are produced by the same route using the same mapping, which keeps the logic consistent and easier to maintain.
Thank you for watching.
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X12, chartered by the American National Standards Institute for more than 35 years, develops and maintains EDI standards and XML schemas.