UPMC’s new alliance could be a boon for mHealth
The University of Pittsburgh Medical Center is enlisting the aid of two nearby universities to study how data analytics might be applied to new healthcare projects. And mHealth might be the beneficiary.
UPMC will spend as much as $20 million a year over the next six years to fund research at the University of Pittsburgh and Carnegie Mellon University, while both universities will contribute hundreds of millions of dollars in grant money. The newly formed Pittsburgh Health Data Alliance will also work with companies such as Disney, Google and Apple.
The alliance is targeting “the next generation of healthcare, the next generation of IT,” UPMC President and CEO Jeffrey Romoff said during a recent press conference. He said the research could create a new form of “artificial intelligence” that gives consumers and healthcare providers real-time access to biometric data.
UPMC, which will market new products developed by the alliance through its UPMC Enterprises business, already operates the Center for Connected Medicine, widely considered one of the largest and best healthcare innovation centers in the country. The center is overseen by Andrew Watson, MD, and includes IBM, Alcatel-Lucent, General Electric and Verizon as founding partners and Allscripts, the Advisory Board Company, Johnson Controls, Surescripts, Storz, Varian Medical Systems, ClinicalConnect and Vidyo as strategic partners.
The University of Pittsburgh’s Center for Commercial Applications of Health Data, led by Professor and Department Chair Michael Becich, MD, PhD, will target personalized medicine, genomic data and data analysis, while Carnegie Mellon’s Center for Machine Learning and Health, led by Professor Eric Xing, PhD, will focus on big data analytics, security and education issues, machine learning and disease modeling.
Among the products envisioned by alliance organizers are a smartphone app that might use genetic data and medical history to suggest dietary changes, a mobile platform capable of identifying or predicting a disease outbreak before it happens, and a mobile health platform that alerts clinicians when a patient shows the first signs of rejecting a transplanted organ.
