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Press Release: High Definition Care Platform Chosen for CDC Epicenter Trial in SSI

Updated: Apr 22, 2019

DASH Analytics, makers of the High Definition Care Platform© (HDC), announced today that their machine learning technology was chosen for a CDC Epicenters Program research trial entitled "SUpPress SSI – Single Use Negative Pressure Wound Therapy (NPWT) to Reduce Surgical Site Infections.” The multicenter trial will assess the efficacy of using negative pressure wound therapy in preventing surgical site infections.

The HDC Surgical Site Infection module is a decision support tool underpinned by powerful machine learning algorithms. It uses real-time patient data from the electronic medical record during surgery to determine a patient’s risk of developing a surgical site infection. The system provides real-time decision support to surgeons during the operation that allows them to optimize the wound management strategy to reduce infections. In previous trials, this technology provided a 74% reduction in surgical site infections in general surgery, improving patient outcomes and substantially reducing the cost of care.

The CDC Epicenter trial will use the DASH Surgical Site Infection module to provide objective, real-time risk stratification of patients in the operating room for potential intervention with negative pressure wound therapy. This is a critical feature of the trial, as the ability of clinicians to perform such risk stratification is very limited due to the multitude of complex patient variables that can lead to surgical site infection.

John W. Cromwell MD, Chief Technology Officer, stated, “We are very excited that the CDC, through their funding, has endorsed this innovative approach to reducing infections. We are looking forward to DASH Analytics being an enabling technology for hospitals to eliminate infections through real-time data analytics.”

The Surgical Site Infection Module is but one component of the DASH High Definition Care Platform, a machine learning technology platform that is designed to use real-time data analytics to maximize the value of care delivered in hospitals to: 1) improve patient outcomes, 2) reduce clinical variations in care, and 3) reduce the costs of hospital care.

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