TriNetX adds 190m patient claims to its Diamond Network

By Maggie Lynch

- Last updated on GMT

(Image: Getty/peshkova)
(Image: Getty/peshkova)

Related tags Patient centricity Patient Real world data Real world evidence Software Clinical data Research

TriNetX announced it will add claims data from 190m patients to its network, including ambulatory care, medical claims, and pharmacy claims, to enable researchers to query and analyze the information.

Through the platform, longitudinal clinical and claims data representing more than 300m patients overall will be available.

The data consists of clinical facts, specialty data from cardiovascular and oncology patients, linked medical claims, and clinical data types include demographics, diagnoses, and facts extracted from physician notes.

According to a spokesperson for the company, TriNetX sourced the claims data commercially then mapped the disparate information to a clinical data model with a consistent semantic meaning and reconciled, adjusted, resubmitted, and canceled claims to establish final claims data.

Through this process, “data can be queried consistently regardless of the underlying data source,”​ explained the spokesperson.

TriNetX hosts all of the data on its web-based platform, however, users can choose to run analytics on TriNetX Diamond Network, to support clinical trial optimization and observational research. It is available through the company’s interface on a subscription base with an additional license fee.

The TriNetX Diamond Network combines multiple claim sources. The spokesperson told us that the data represents a broad cross-section of the US population and “doesn’t suffer from inherent biases of other claims datasets.”

“The Diamond Network includes any patients having data in the EMR datasets or who have both medical claims and pharmacy claims, ensuring that patients in the network have rich data that is appropriate for feasibility and comparative effectiveness analysis.”

Claims data and ‘the hypothesis generation’

Jennifer Stacey, VP of clinical sciences at TriNetX said in a press release that claims data is a critical component of real-world evidence (RWE) within the health care industry. It enhances researchers' ability to understand market dynamics and therefore make strategic decisions.

For the “hypothesis generation,”​ the network can be powerful, according to Stacey. It allows for clinical outcomes research and enables studies to be derived from real-world data.

The spokesperson told us, “when conducting research, having multiple data sets to conduct analyses and gain further validation, only increases confidence in the results.”

Alex Eastman, VP of product management at TriNetX, explained in a press release that “on-demand research-grade”​ data available through its curated platform, can shorten the time spent “wrangling and mapping data”​ which he estimates is around 80% of most data analysis time.

TriNetX’s growth

TriNetX has expanded​ its range of services recently, as the industry has increasingly been using the company to gain access to its data.

In May of 2018, the company introduced TriNetX Research​. The offering, a suite of analytics solutions using real-world data, combined longitudinal clinical and genomic data in a self-service platform. Additionally, in October of 2018 the company added new capabilities​ to its research platform.

Previously, the company had also added a natural language processing service​ and an algorithm to aid in patient identification​.

Recently, the platform has been tapped by Allergan​, Tufts University​, Pfizer​, Sanofi​, and Icon​. 

Related news

Show more

Related products

show more

Saama accelerates data review processes

Saama accelerates data review processes

Content provided by Saama | 25-Mar-2024 | Infographic

In this new infographic, learn how Saama accelerates data review processes. Only Saama has AI/ML models trained for life sciences on over 300 million data...

More Data, More Insights, More Progress

More Data, More Insights, More Progress

Content provided by Saama | 04-Mar-2024 | Case Study

The sponsor’s clinical development team needed a flexible solution to quickly visualize patient and site data in a single location

Using Define-XML to build more efficient studies

Using Define-XML to build more efficient studies

Content provided by Formedix | 14-Nov-2023 | White Paper

It is commonly thought that Define-XML is simply a dataset descriptor: a way to document what datasets look like, including the names and labels of datasets...

Related suppliers

Follow us


View more