Verinovum offers data enrichment and integration technology services, providing streamlined tools to address complex patient data challenges and deliver actionable insights for improved healthcare outcomes. Verinovum works with healthcare payers, providers, and healthcare IT partners to enhance the completeness, cleanliness, and accuracy of clinical data with its Data Curation-as-a-Service (DCaaS) platform and other solutions.

Originally founded to advance healthcare data interoperability for health information exchanges (HIEs) in 2013, the company expanded its focus over time to support data curation specialties, placing new demands on its infrastructure. In its early years, Verinovum relied on a relational data architecture using Microsoft SQL Server, but this proved insufficient for its increasingly demanding performance and modeling requirements.

The company needed to reliably handle large volumes of disparate data from electronic health record (EHR) systems. However it lacked replication capabilities to the degree needed for high availability and performance. In addition, Verinovum required a data platform that was flexible enough to allow for rapid changes to its data model for a variety of clients and evolving business needs.

To optimize capturing and managing highly variable healthcare data from disparate sites, Verinovum decided to deploy Apache Cassandra®, an open source, NoSQL database management system.

Having worked in financial services prior to healthcare, Campbell appreciates the importance of protecting sensitive data. The enterprise-grade security of DataStax Enterprise offers Verinovum encryption for data in flight (TLS) and at rest (TDE), KMIP security policies, role-based access control (RBAC), row-level access control (RLAC), as well as user and application authentication with Kerberos.

With Cassandra, Verinovum unleashes powerful capabilities for its applications to leverage real-time writes and queries, with low latency. “We’ve found the solution to be high performing and agile for our most challenging initiatives involving high-volume transactions and our needs for flexibility in the data model,” says Ryan Campbell, Chief Vision Officer at Verinovum.

In the past, when it used a relational data structure, updating Verinovum’s data model was a complicated, time-consuming task for the company’s IT team. “The way we have it set up now, when we need to change the data model, we make a change, test it, and we’re done. It doesn’t take long,” says Campbell.

When conducting up-front planning for new initiatives, Verinovum’s IT architects are also enjoying reduced complexity. “Now when we architect, we no longer have to try to think about every potential variation in the data model that we may or may not need down the road,” Campbell says. “Data modeling now takes probably half or a third of the time that we used to spend.”

Verinovum reduced its IT infrastructure expenses thanks to the lower costs of managing Cassandra nodes in comparison to expensive servers that were previously needed to support its enterprise relational databases. “Given the hardware expense and the cost of being able to scale, even with an on-premise environment, we definitely have a more favorable TCO now,” says Campbell.

Verinovum’s nimble core data platform unlocks accelerated new business development opportunities. “On the revenue side, we’ve gained extra agility in our go-to-market strategies. We can do planning around new projects with new clients—and because of the flexibility of our platform—we don’t have to do a lot of pre-building,” Campbell says.

“We don’t have to partake in the ‘build it and they will come model.’ Instead we can let them come, and then we can quickly build what they need from the foundational platform we have with Cassandra and the application we’ve built around it,” he says.

Campbell is excited to help Verinovum’s clients improve business operations and their patients’ lives with more complete, accurate clinical data. In the case of one regional payer, Verinovum’s data curation services helped increase the quality and usability of data from 14% to 89%.

Better clinical data can help support early disease detection and boost patient adherence to treatment plans for common diseases like diabetes, congestive heart failure, and asthma. “From a cost perspective, it can save payers and providers a lot of money. And if you catch a condition early, patients usually have better treatment options, better quality of life going forward, versus detecting it later,” says Campbell.