SBIR-STTR Award

The goal of the Phase I study is to determine the feasibility of piloting a low cost Real Time Location System (RTLS) for use in healthcare based on a novel technology known as Near Field Electromagnetic. The proposed QHealth system promises to support a number of healthcare applications such as equipment management, workflow optimization, hand-hygiene compliance, patient safety, and medical billing. We address current deficiencies of RTLS used in healthcare by improved performance and lower cost. The Phase I hinges on the ability to deliver an inexpensive locator while maintaining high accuracy of 1m or better. A further innovation is in the use of a RTLS-RFID fusion in a prototype QTag, allowing for the management of large number of healthcare assets at a low cost. The Phase I will include prototyping, characterization, and system testing. If successful, the project will create a RTLS enabling a return on investment of at least $4,000 per bed per year. Factored over the 800,000 registered hospital beds in the U.S., the savings could be as much as $3.2 billion per year.

Public Health Relevance Statement:


Public Health Relevance:
The healthcare system in the United States suffers from ineffective logistics management, patient safety concerns and escalating costs. This effort will explore if an inexpensive, high resolution Real Time Location Systems can reduce operating and capital expenses within hospitals.

NIH Spending Category:
Bioengineering; Clinical Research; Health Services; Patient Safety

Project Terms:
Address; Adoption; Alabama; Area; Attention; base; Beds; Capital; Clinical; Computer software; cost; cost effective; Cost Savings; density; design; Detection; detector; Development; Electromagnetic Fields; Equipment; Feasibility Studies; Frequencies; Generations; Goals; Hand; Handwashing; Healthcare; Healthcare Systems; hospital bed; Hospitals; Hygiene; improved; Individual; innovation; interoperability; Investments; Legal patent; Location; Logistics; Measurement; Medical; Military Personnel; Modification; Monitor; new technology; next generation; Noise; novel; patient safety; Performance; Phase; phase 1 study; phase 2 study; prevent; Production; prototype; Provider; public health relevance; Reader; Reading; Reporting; Research Infrastructure; Resolution; Safety; Savings; Signal Transduction; Small Business Innovation Research Grant; Standardization; Stream; success; System; Technology; Testing; Time; Training; United States; Vision; Work

America'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 Administration'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-Track'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-Track'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 (<$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-Track'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.

Public Health Relevance Statement:
PROJECT NARRATIVE America'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 (<$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.

Project Terms:
Adoption; Americas; base; Beds; Bluetooth; Charge; Clinical; Computer software; cost; cost effective; Data; Data Analytics; design; Development; Electromagnetic Fields; Emerging Technologies; Ensure; Environment; Equipment; Equipment and supply inventories; Failure; Feedback; Fraud; Frequencies; Funding; Goals; Grant; Health care facility; Health Care Fraud; health care settings; Health Expenditures; Health Insurance; Health Personnel; Healthcare; Healthcare Systems; hospital bed; Hospitals; Human Resources; Individual; Industrialization; innovation; insurance claims; Intensive Care Units; interoperability; Justice; Legal patent; Letters; Location; Logistics; Medical; Medical Audit; Medical center; Medicare; Medicare/Medicaid; meter; Military Personnel; Missouri; next generation; novel; Nuclear; off-patent; operation; Outcome; patient safety; payment; Performance; Phase; phase 2 study; Plants; prevent; Price; Procedures; Process; professor; programs; Reporting; Research; Research Personnel; S Phase; Safety; Savings; Site; Small Business Innovation Research Grant; Social Security; success; System; Technology; Testing; Time; Training; United States Department of Veterans Affairs; United States National Center for Health Statistics; Universities; University Hospitals; Validation; wasting