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VA Launches Predictive Analytics, Clinical Decision Support Center

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October 3, 2019

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The National Center for Collaborative Healthcare Innovation will enhance care delivery using predictive analytics and clinical decision support tools.

The Department of Veterans Affairs (VA) recently established the National Center for Collaborative Healthcare Innovation (NCCHI) within the Palo Alto Health Care System (VAPAHCS) in California, which will leverage predictive analytics, artificial intelligence, and clinical decision support to improve veteran care.

The new center was established July 25 and formed in partnership with the Veterans Health Administration Innovation Ecosystem (VHA IE), which aims to modernize and enhance the customer experience for Veterans and their families.

NCCHI will help the VA achieve its mission of developing impactful healthcare solutions that are shared efficiently throughout the VA enterprise.

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NCCHI will be located in Silicone Valley, and will build on a foundation of existing collaborations between VAPAHCS, VHA IE, leading technology companies, and other government agencies.

The center’s immediate priorities include focusing on fine-tuning artificial intelligence, clinical decision support efficiencies, and sharing solutions that can benefit many more patients. VA is also currently building an infrastructure to facilitate more effective communication, collaboration, and engagement to support further work in the organization.

NCCHI will expand on the VA Palo Alto Health Care System’s efforts to improve care with AI and predictive analytics. In August 2019, the organization partnered with DeepMind Health, a Google-backed company, to develop a machine learning tool that can predict kidney injury in patients up to 48 hours in advance.

“We are proud to partner with the Department of Veterans Affairs on this important challenge,” Mustafa Suleyman, co-founder of DeepMind, said when the partnership was announced.

“This project has great potential intelligently to detect and prevent deterioration before patients show serious signs of illness. Speed is vital when a patient is deteriorating: the sooner the right information reaches the right clinician, the sooner the patient can be given the right care.”

The machine learning tool has the potential to improve kidney care for all patients.

“These are exciting times for research and innovation at VA,” said VA Secretary Robert Wilkie. “Studies like this can have a significant effect in not only the Veteran community, but people throughout the nation.”

Additionally, in April 2019, the VA leveraged deep learning technology to identify and address suicide risks among veterans. In collaboration with researchers at Lawrence Berkeley National Laboratory, the VA used EHR data, genomic information, and AI to identify patterns that may indicate a likelihood to attempt suicide.

“The VA has been collecting medical records and genomic data from some 700,000 veterans, and they need help from DOE to interpret all of this information to improve healthcare for these individuals,” said Silvia Crivelli, a computational biologist in Berkeley Lab’s Computational Research Division (CRD).

“We believe that, for suicide prevention, the unstructured data will give us another side of the story that is extremely important for predicting risk — things like what the person is feeling, social isolation, homelessness, lack of sleep, pain, and incarceration.”

VA expects that the operational tools and solutions developed at NCCHI will be foundational to supporting similar work throughout the enterprise.

“The NCCHI is an important part of our strategy to be leaders in health care innovation and quality” said VA Secretary Robert Wilkie. “The center is particularly exciting because it is uniquely designed as a catalyst to combine strengths from non-health care fields.”

Date: October 03, 2019

Source: HealthITAnalytics

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