GNS HEALTHCARE, INC COLLABORATES WITH NATIONALLY RANKED HOSPITAL TO PREDICT ADVERSE DRUG EVENTS AND HOSPITAL READMISSIONS

September 13, 2011

Brigham and Women's Hospital, the Center for Patient Safety Research and Practice and GNS Healthcare will build predictive patient outcome models from EHR, claims and pharmacy data

 

Cambridge, MA - September 13, 2011 - GNS Healthcare, Inc. (GNS) announced today a collaboration with David W. Bates, MD, M.Sc. and Brigham and Women's Hospital (BWH), a teaching affiliate of Harvard Medical School. Their collaboration will focus initially on predicting adverse drug events and on hospital readmissions for patients admitted for congestive heart failure.

 

"GNS is incredibly excited to announce this collaboration with Dr. Bates, Brigham and Women's Hospital and the Center for Patient Safety Research and Practice, which Dr. Bates directs. Dr. Bates is internationally renowned in using technology to improve patient safety, quality of care, and cost effectiveness. His work has demonstrated that the most effective way to prevent costly adverse events is to improve systems and the information they can make available," said GNS Healthcare Founder and CEO, Colin Hill. "We feel strongly that GNS' platform will provide new insights that will be pivotal to realizing major improvements and truly personalizing care."

 

The collaboration will use GNS's proprietary REFS™ platform and data from the Electronic Health Records (EHRs) of patients treated by the Partners HealthCare system. Together, they aim to identify the hidden, underlying pathways and relationships that are driving such events. Once surfaced, these can be harnessed to reduce the adverse impact these issues have on people's health. Preventable adverse events are estimated to cost the U.S. medical system as much as $50 billion a year.

 

"GNS Healthcare has developed supercomputer-driven, hypothesis-free technologies to extract actionable insights from large, complex healthcare datasets," said Dr. David Bates, Chief of the Division of General Internal Medicine and Primary Care at BWH, a Professor of Medicine at Harvard Medical School, and a Professor of Health Policy and Management at the Harvard School of Public Health. "The hypothesis-free approach represents an exciting way to identify non-obvious combinations of conditions, drugs and other factors that lead to adverse events, and reveal what activities can mitigate them. This has the potential to dramatically increase the quality of patient care while reducing overall costs."

 

Beyond predicting which patients are at high-risk of an ADE or readmission, the collaborators aim to identify interventions that help professionals prevent these events from occurring. The collaboration complements work GNS is doing with leading pharmacy benefit managers related to ADE predictions, their efforts with leading providers related to predicting 'never events', and several other analytic efforts in health care.

 

About REFS™
 

REFS™ (Reverse Engineering-Forward Simulation) is comprised of integrated machine learning algorithms and software that extract causal relationships from complex, multi-dimensional data and enable the simulation of billions of 'what if?' hypotheses to explore novel unseen conditions and predictions forward in time. This model-centric discovery and simulation approach represents a paradigm shift in data analysis, leapfrogging existing approaches such as high-dimensional pattern matching.

 

About GNS Healthcare, Inc.
 

GNS Healthcare, a subsidiary of Via Science, is a healthcare science and technology company that applies next-generation machine learning and simulation technologies to understand patient treatments. In partnerships with health plans, pharmacy benefit managers, care delivery systems, and pharmaceutical & biotech companies, GNS Healthcare helps 'match patients to treatments' - whether it's identifying waste, gaps in care or optimal treatment paths - to help deliver on the promise of 'smart' medicine.

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