TriNetX adds 190m patient claims to its Diamond Network
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.
