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GaN Corporation SBIR Phase II Award, September 2019

A SBIR Phase II contract was awarded to GaN Corporation in September, 2019 for $1,187,475.0 USD from the U.S. Department of Health & Human Services and National Institutes of Health.

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sbir.gov/node/1681553
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
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GaN Corporation
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Government Agency
0
Government Branch
National Institutes of Health
National Institutes of Health
0
Award Type
SBIR0
Contract Number (US Government)
2R44NR015928-02A10
Award Phase
Phase II0
Award Amount (USD)
1,187,4750
Date Awarded
September 26, 2019
0
End Date
June 30, 2021
0
Abstract

PROJECT SUMMARY Significance: Americaandapos;s health care system remains challenged by tens of billions of dollars of fraud and inefficiencies. Lost and stolen equipment cost about $4,000 per hospital bed, increasing to $8,000 when expenses incurred from out-of-place equipment are added. In addition, a 2017 report estimates $95 billion was lost to fraud, waste, abuse, and other improper payments in the Medicare and Medicaid programs. Real Time Location Systems (RTLS) are an emerging technology that promises to increase the visibility and efficiency of clinical workflows. There is no clear market leader. Low-cost solutions have poor accuracy, and high-accuracy solutions are too expensive. For instance, The Veteran Administrationandapos;s $543 million foray into medical RTLS has been deemed “a catastrophic failure.” The problem and opportunity are highly significant. Investigator(s): Dr. Hans G. Schantz of Q-Track has more than forty patents and managed over $10 million in sponsored research at Q-Track. Professors Jung Hyup Kim and Laurel Despins at the University of Missouri will evaluate and optimize the proposed innovations with respect to clinical end-user needs. Innovation: Q-Trackandapos;s pioneering low-frequency approach to indoor location – Near-Field Electromagnetic Ranging (NFER) provides sub-meter accurate location results in the most challenging environments including a third of U.S. nuclear plants, health care facilities, military training sites, and other industrial facilities. Cost has limited adoption to broader markets. This effort aimed to achieve a radical reduction in cost by a factor of two. In Phase 1, Q-Track dramatically demonstrated feasibility, lowering the retail price of a Locator-Receiver from $2750 to $600, while maintaining 40 cm or better accuracy. Taking an existing NFER RTLS deployment at the Intensive Care Unit at the University Hospital, University of Missouri Health Care in Columbia, Missouri as a baseline, Q-Trackandapos;s Phase 1 success drives the overall NFER RTLS cost from $2191/bed to $1474/bed. Phase 2 builds on this successful outcome with sub-meter accurate, low cost (andlt;$1000/bed), RTLS using an innovative low-frequency approach. In Phase 2, we lower the cost of the QTag location tag in a redesign. We compliment sub-meter accurate medical personnel tracking with Asset Tag Tracking capability using $1-$2 Bluetooth Low Energy active asset tags. We further implement user-centric data analytics to understand and characterize health care operations. U.S. Patent 8,326,451 further describes Q-Trackandapos;s innovative approach. Approach: Finally, we will collaborate with academic researchers to deploy a pilot at an Intensive Care Unit. Our pilot will track medical personnel and assets. Our study assesses the ability of the system to characterize, optimize, and validate health care operation in real-world settings to detect fraud and achieve efficiencies. Environment: Our partnership with Dr. Kim and the ICU at the University Hospital, University of Missouri Health Care in Columbia, Missouri ensures real-world feedback in an operational health care setting.PROJECT NARRATIVE Americaandapos;s health care system remains challenged by tens of billions of dollars of fraud and inefficiencies. Real Time Location Systems (RTLS) are an emerging technology that that promise to increase the visibility and operational efficiency of clinical workflows, however adoption has been limited by poor performance and high cost. This Phase 2 effort builds on a successful Phase 1 outcome to deliver a sub-meter accurate, low cost (andlt;$1000/bed), RTLS using an innovative low-frequency approach to the problem, combined with user- centric data analytics to characterize, optimize, and validate health care operation, so as to achieve tens of billions of dollars in fraud reduction and process improvements.

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