News | Analytics Software | February 03, 2016

Spreemo Announces Large-Scale Data Research Partnership with the University Radiology Group

Initiative will pair Spreemo’s analytics with URG’s clinical and academic experience to improve quality patient outcomes

Spreemo, URG, University Radiology Group, partnership, quality of care, data analytics

February 3, 2016 – Predictive analytics platform Spreemo has entered into a strategic research partnership with the University Radiology Group (URG), one of the nation’s pre-eminent radiology practices performing approximately 1.8 million patient imaging exams annually. Spreemo, through its Quality Research Institute, and URG will jointly investigate the effect of various factors in the delivery of care, including patient diagnoses and how these impact the ensuing outcomes and overall cost. Utilizing data from Spreemo’s Fortune 100 and 500 partners, URG will combine its clinical and academic experience with Spreemo’s data and analytics to further its evidence-based understanding of quality. The product of this effort aims to improve patient outcomes.     

In operation for more than 50 years, URG is the second largest radiology practice in the nation, comprised of approximately 140 doctors servicing a network of over nine acute and full-service hospitals, as well as 20 outpatient facilities. As the Academic Radiology Faculty and research arm of Rutgers Robert Wood Johnson Medical School, URG offers care in over 4,000 beds throughout its footprint within the state of New Jersey. 

“Spreemo’s advances in quality measures have guided patients and payers toward better decisions about care,” added Robert Epstein, M.D., chairman of the board of URG. “We’re excited to partner with Spreemo as we share the mission of delivery of quality and appropriate care for patients.  This collaboration allows the evaluation of radiology data on an unprecedented scale – not only to optimize provider best practice, but also to build high-quality programs that lead to more accurate diagnoses and efficient treatment pathways.” 

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