MS PATHS: Harnessing Real-Time Patient Data to Reshape MS Care and Research

December 11, 2016 /
MS Research Study and Reports


                                                                  

  


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Expert centers pool data to build a “learning health system” in Multiple Sclerosis (MS)PINTEREST

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When the Institute of Medicine recently put out a call for U.S. healthcare institutions to share data from routine care to create “learning health systems,” it had a few principles in mind:
  • Align science, informatics, incentives and culture for continuous improvement
  • Seamlessly embed best practices into the care process
  • Empower patients to actively take part in all elements of their care
  • Systematically capture new knowledge as an integral byproduct of caregiving
“This sounds great in theory, but it’s been relatively uncommon in practice,” says Robert Bermel, MD,Medical Director of Cleveland Clinic’s Mellen Center for Multiple Sclerosis Treatment and Research. The stumbling blocks, he notes, have been mostly logistical and technological.

Introducing MS PATHS

But Dr. Bermel has recently been collaborating with colleagues from other healthcare institutions and Biogen on an initiative to overcome those barriers in multiple sclerosis (MS). The project, sponsored by Biogen, is known as MS PATHS (Multiple Sclerosis Partners Advancing Technology and Health Solutions).
“MS PATHS is a one-of-a-kind collaboration between academic healthcare institutions and industry to create an integrated, efficient data collection system to conduct research and potentially improve clinical care,” Dr. Bermel explains. “We aim to leverage data in aggregate and collaborate across centers to learn more about MS through standardized neuro-performance testing, patient-reported data and imaging.”
Initial MS PATHS efforts are focused on information-sharing via a learning health system to which Cleveland Clinic’s Mellen Center and other leading healthcare institutions in the U.S. and Europe will contribute standardized patient-reported data.

Learning from pooled clinical practice

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