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Q-Centrix and Realyze Intelligence Partner to Advance the Automation of High-Quality Clinical Data

Q-Centrix and Realyze Intelligence Partner to Advance the Automation of High-Quality Clinical Data
Realyze Intelligence and Q-Centrix partner on AI and NLP translation tools that enhance unstructured data collection and ultimately help the industry unlock the full value of clinical data

Q-Centrix, the largest exclusive provider of clinical data management solutions to hospitals and health systems, announced a partnership with Realyze Intelligence, a company using artificial intelligence (AI) and natural language processing (NLP) to capture unstructured clinical data, ensuring patient populations with heart conditions or cancer receive the most beneficial treatments.

“Q-Centrix has been investing in data automation for several years — testing the capabilities with some of the leading partners in the space. As a result of our efforts, we recognized that the optimal solution would include an AI / NLP based software provider, allowing us to build our own proprietary algorithms on top of that base,” said Brian Foy, chief product officer at Q-Centrix. “Because of our scale — now working with more than 1,200 facilities — and the breadth of our data, we are excited to partner with Realyze and lead the industry in this exciting transformation. As the value of clinical data exponentially grows, we will continue to meaningfully enhance our refined, proprietary process to curate high-quality clinical data using innovative technology (automation and software) and our clinical experts.”PREDICTIONS SERIES 2022

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By partnering with Realyze, Q-Centrix will bring a sophisticated AI and machine learning component to its industry-leading Enterprise Clinical Data Management (eCDMTM) platform. The eCDM combines clinical expertise with market-leading technology, information and analytics to enable the extraction, curation, management and analysis of high-fidelity clinical data across health care systems and within key clinical segments like oncology, cardiology, surgical and others. Realyze was spun out of UPMC Enterprises, the innovation, commercialization and venture capital arm of leading health system UPMC.

Realyze’s NLP will act as a translation layer that consumes data from Q-Centrix’s proprietary models to identify clinical information in unstructured fields. The result will be a complete clinical model of a patient to determine meaning, precedent and clinical implications. Health systems using Q-Centrix’s solutions will now have access to a best-in-class offering that truly unlocks the potential of their clinical data by augmenting clinical data experts, streamlining the data curation process and further enhancing their industry-leading data accuracy.

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“A significant amount of rich clinical information remains untapped as unstructured data in physicians’ notes, requiring extraction by clinical experts,” said Aaron Brauser, president and chief executive officer of Realyze. “Our goal is to not only provide a solution that improves both the capability and efficiency of extraction for hospitals and health systems but also to improve patient understanding leading to better care. Overall, this partnership combines the expertise and technology of both companies to streamline how clinical data translates to patient outcomes.”

At the outset, Q-Centrix will apply Realyze’s technology within cardiology and oncology. The partnership may grow into other clinical segments and data applications that can substantially impact the advancement and personalization of care.

“Automation will play an important role in the capture of clinical data and will complement the essential human touch,” continues Foy. “Clinical data experts are an important element in the deciphering and pinpointing of notable information. This partnership makes the largest group of clinical data experts in the world more efficient, and, as the demand for clinical data increases, Realyze’s technology helps us scale the capabilities of our experts to improve the quality, reach and use of clinical data.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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