CHICAGO, IL--(Marketwired - December 07, 2017) - To help hospitals meet the growing demands of value-based care, Q-Centrix is introducing artificial intelligence (AI) into its clinical data registry solutions. The move advances a first-of-its-kind approach for registry data management that bundles AI-supported technology with clinical expert service. This proper deployment of AI can produce significant cost savings for hospitals through speedier and more-accurate quality data reporting.
"Healthcare often lags in adopting new information technologies because of the resulting demands placed on healthcare workers," said Patrick Herguth, Q-Centrix Chief Operating Officer. "We have seen success when innovations are paired with the clinical expertise and support to ensure users get the most from the solution. We believe the same can be achieved with natural language processing (NLP) across healthcare quality improvement."
The shift toward linking reimbursement to health outcomes is requiring hospitals to focus more resources on data reporting while diminishing margins are forcing executives to scrutinize any additional spending. For example, patient care and technology usage data must be submitted to avoid Medicare penalties and receive positive payment adjustments. Other quality reporting demands include:
- National healthcare coverage determinations
- Expanding clinical registry participation
- Implementation of the Medicare Access and CHIP Reauthorization Act
- Private payer adoption of pay-for-performance models
Q-Centrix has begun integrating NLP into its American College of Cardiology National Cardiovascular Data Registry (NCDR®) solutions. In 2018, it will expand this to include more registries in NCDR and in other major nationally-recognized registry groups.
"With proper NLP deployment, we saw significant quality data management cost savings -- up to 50% -- for some hospitals. And, because we offer a comprehensive solution, there is minimal risk for hospitals who partner with us," said Herguth. "To extend this value to more institutions, we are working to adapt our NLP-supported solution for use in other healthcare quality initiatives, including outside the registries."
NLP is a form of machine learning technology -- meaning it is designed to understand human language and information patterns. Leveraging it in healthcare offers numerous benefits, since up to 80% of data in electronic medical records (EMRs) can be unstructured information. To achieve its full potential, NLP needs to be "trained" to hone in on patterns that are specific to quality documentation within a healthcare institution.
"The unstructured data in an EMR tends to hold rich clinical insights. Participation in national registries, such as those under the ACC's NCDR, the STS, and the AHA's GWTG, require a clinical expert to abstract this information, which can be extremely time consuming," said Herguth. "Paired with NLP, our clinical data registry solution adapts to a hospital's processes, so clinicians can focus more on delivering and improving care and less on structuring data into 'click-through' forms."
Q-Centrix has the added ability to manage, train, and maintain NLP-supported solutions through its depth of resources and expertise. As part of its registry solution, it combines technology with the industry's largest and broadest team of nurse-educated quality information specialists -- more than 800 experts focused on data abstraction and analysis -- acting as virtual extensions of quality departments within more than 450 hospitals.
Q-Centrix aims to measurably improve the quality and safety of patient care in the U.S. through the use of its market-leading technology platform, Q-Apps, coupled with the industry's largest and broadest team of nurse-educated, quality information specialists. Processing in excess of 1 million quality data transactions annually, Q-Centrix is a comprehensive quality partner to hundreds of hospitals, providing quality data management solutions, including quality data capture, surveillance, measure calculations, analysis, reporting, and improvement solutions. For more information about Q-Centrix, visit www.q-centrix.com.