Diameter Health Customer story

Automated healthcare data ingestion for Diameter Health

Diameter Health’s technology refines raw patient data into high quality, actionable information at scale for healthcare organizations. With the help of CloverDX they have made their data processes, and their customer onboarding, more efficient.

Automated data ingestion use case

  • Ingest and transform complex healthcare data (HL7 v2) into a standardized format at scale in order to onboard customers
  • Orchestrate the movement of data from Diameter Health platform to delivery location to customers

Diameter Health technology is the standard for health data optimization and refines raw patient data into high quality, actionable information, enabling healthcare organizations that depend on multi‑source clinical data streams to realize greater value from their data.

The data format that the healthcare industry uses - HL7v2 - can be complex, with significant variability in how it's used.

harvardpanHarvard Pan, Chief Technology Officer at Diameter Health, outlines the problem:

"You can imagine, you have 10 providers that are giving you these files, and even if it's the same type of file, same version, there could be variations within it, so we needed a process that could handle the variations in a configurable way."

The challenge that Diameter Health faced was how to turn this real-world, non-standard HL7v2 into something standard, at scale, across a number of customers. They needed a data ingestion process that could handle these variations, without requiring lots of extra development work.

They also wanted to enable their clinical experts, who don't necessarily have coding experience, to configure what an HL7v2 file looks like, transform it into their data model, and then send to their APIs. 

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“CloverDX technology enabled Diameter Health to reduce HL7v2 mapping time by 83%”

The project they worked on with CloverDX dealt with the transformation of the HL7v2 documents into Diameter Healths JSON model, and also with building a configurable interface to enable analysts to have input into the data ingestion process. 

The analysts are able to work with a format that's familiar to them - in this case an Excel file - to define mappings.

As part of the automated data ingest process, CloverDX digests the mapping document and automatically maps incoming HL7 messages onto target JSON structures, that are then consumed by Diameter Health platform's REST API.

With the CloverDX solution, Diameter Health are now able to present their customers with an out-of-the-box solution where they don't need to spend extra effort and IT cost. As Harvard Pan explains:

"It is a big win for them [Diameter customers], but also a big win for us because we can offer a scalable service which is a new revenue stream for us." 

And one of the main benefits is that the whole process of delivering value to a customer is much quicker, with Diameter Health being able to have more control over the process.

“CloverDX’s value, to me, is in reducing the friction needed to be able to roll solutions out to our customers."

Read the full interview with Diameter Health

Goals:

  • Onboard customers (and their data) to the Diameter Health platform more quickly
  • Manage complex variations in data formats, configurably and transparently
  • Improve Diameter Health team productivity with scalable processes and technology

How CloverDX helped Diameter Health automate HL7v2 data ingestion

  • Data mapping solution based on CloverDX provides clinical experts an Excel‑based mapping file that can easily be processed automatically

  • CloverDX digests the mapping document, and maps incoming HL7 messages onto target JSON structures that are consumed by the Diameter Health platform’s REST API

  • Reporting and status monitoring included as part of the automated system

  • Data ingest and orchestration of data movement managed automatically through CloverDX – delivering cost savings and better resource allocation

Case study: Enterprise-scale data mapping for Diameter Health

Read More: Data Ingest with CloverDX