Case Study Healthcare

Near-Real-Time HL7 Integration for a Cloud Help Desk Platform

Parsing and splitting HL7 data on a hybrid Informatica pipeline so a cloud Help Desk platform always has the customer's latest information

5-minute requirement beaten — files processed end-to-end in 3-4 minutes

Summary

A healthcare-sector customer needed to feed HL7 data from their systems into a cloud-based Help Desk solution in near-real-time, so support agents could work from the latest customer information. The core technical challenge was parsing and splitting HL7 files — generated every five minutes — while preserving data hierarchy and removing duplicates, all within that same five-minute window. aiDataWorks designed a hybrid solution using Informatica PowerCenter on-premise with a custom data-transformation (DT) service to parse, split, and validate the HL7 files, then used a PowerExchange connector to load results into the customer's cloud Help Desk platform. Leveraging Informatica B2B libraries cut development time in half and produced a fully reusable framework, letting the customer extend the solution to new HL7 formats with minimal additional effort. The result was an end-to-end cycle time of roughly 3 to 4 minutes per file, beating the original real-time requirement.

The challenge

  • Hybrid, near-real-time delivery. HL7 data had to move from the customer's on-premise systems into a cloud-based Help Desk solution in near real time, integrating a hybrid environment rather than running on a batch or overnight cycle.
  • Support agents needed current data. The cloud Help Desk platform needed the latest customer information on hand so support agents could deliver better service during live interactions.
  • Hierarchy-preserving splitting with de-duplication. Each HL7 file had to be split into event-specific pieces while preserving its original hierarchy, and duplicate records had to be identified and removed based on specific criteria.
  • A five-minute processing window. New files were generated every 5 minutes, and each one had to be parsed, split, validated, and loaded into the cloud platform inside that same window.

The solution

Solution architecture: HL7 file landing → DT parser/splitter → event-specific processing → PowerExchange → cloud Help Desk Download diagram (PDF)

How we built it

File detection & event-wait pipeline

  • A data file and a matching trigger file are delivered to a local landing folder in the on-premise environment.
  • An event-wait process continuously watches the landing folder and fires a processing session the moment both files arrive.
  • Starting the pipeline on the event, rather than a fixed schedule, keeps the process inside the five-minute window regardless of exactly when a file lands.

Custom HL7 parsing & splitting (DT services)

  • Built a custom Data Transformation (DT) service running on Informatica PowerCenter, on-premise, purpose-built to parse HL7's nested structure.
  • A splitter DT service breaks each incoming file into event-specific files while maintaining the original hierarchy.
  • Event-specific DT services then parse each event's data in turn, including nested and child data, and apply the de-duplication criteria before the data moves downstream.

Cloud delivery & reusable framework

  • Parsed, validated data is loaded into the customer's cloud Help Desk service through a PowerExchange connector.
  • Once loaded, the processed file is moved to archive, closing out the cycle.
  • Built with fully reusable code and mappings, drawing on Informatica B2B libraries, so the customer can add new HL7 libraries and formats going forward with minimal to no impact on the existing process.

Outcomes

3-4 min End-to-end file processing time target was 5 min
50% Development time cut via B2B libraries
Fully reusable DT mappings extend to new HL7 formats minimal to no rework
  • Support agents work from near-real-time customer data instead of stale batch extracts, improving the quality of every help desk interaction.
  • Cutting development time in half through Informatica B2B libraries meant more HL7 file formats could be built inside the original project deadlines.
  • Because the DT service and PowerCenter mappings are fully reusable, the customer can extend the pattern to new HL7 formats going forward with minimal additional effort.

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