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Home » R&D nonprofit to collaborate on use of predictive analytics

R&D nonprofit to collaborate on use of predictive analytics

June 10, 2013
CenterWatch Staff

The Gordon and Betty Moore Foundation, which focuses on environmental conservation, patient care and scientific research, awarded a grant to the Parkland Center for Clinical Innovation (PCCI), a nonprofit R&D corporation. PCCI will collaborate with international informaticists, health services researchers, statisticians and legal and ethical experts who will identify how the use of real-time healthcare predictive analytics can make a positive impact on patient outcomes and costs. The experts will initially meet in Washington D.C.

"Healthcare must be redesigned to integrate multiple elements—information technology and decision support, medical technology, interprofessional team-based care, practices that are based on evidence, systems engineering and continual learning," said George Bo-Linn, chief program officer for the Gordon and Betty Moore Foundation's Patient Care Program. "Predictive analytics is a key component of this integrated design."

Gabriel Escobar, M.D., a senior research director at the Kaiser Permanente Northern California division of research, will co-lead the Washington D.C. session with Ruben Amarasingham, M.D., founder and chief executive officer of PCCI.

"Use of predictive analytics in routine clinical care holds great promise," said Escobar. "It could lead clinicians and health systems to zero in on discrete subsets of patients, dramatically reducing resource consumption while simultaneously improving patient outcomes. But many challenges remain before this promise is achieved."  

The collaboration seeks to open up a pathway for the future of healthcare, which is decades behind other industries in its use of predictive analytics. The experts will center their collaboration on ways to 1) improve model transparency and validation; 2) break down the digital divide that keeps safety-net systems from reaping the benefits of often costly decision support technologies; 3) tap into new data sources that can bring great insight into a patient's health; and 4) consider the legal and ethical frameworks needed for the field. 

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