Pennington Biomedical Research Center

Our understanding of COVID-19 includes how long the virus lasts on surfaces or in the air. This information guides the development of theories on human-to-human spread. However, no human data exists to understand its person-to-person spread within hospitals and to frontline workers; an unknown that contributes to their high risk of infection. State-of-the-art real time location sensing technology is currently implemented in hospitals to track equipment or staff. We propose to provide the most robust human information available to date regarding COVID-19 infection risk in frontline workers by understanding both their precise proximity and duration of time near COVID-19+ patients or undiagnosed staff. Location data can be retroactively applied to patients’/staff movement that occurred even before becoming COVID-19 positive, for example tracking through hallways or using restrooms. This information will help develop functional guidelines for hospitals to implement as prevention strategies and prophylactic procedures.

Nearly 600 – and counting – US health workers have died of COVID-19 as of early June, 2020 according to Kaiser Health News. This tally includes doctors, nurses, paramedics, as well as crucial health support such as hospital janitors, administrators and nursing home workers. CDC data shows that as early as April 15, 2020, 9,000 US healthcare workers had contracted COVID-19. Globally, hospitals are implementing strategies, policies and procedures in an effort to keep their workers and patients safe during the pandemic. However, there is scant real-world evidence to inform many of these policies. While laboratory-based evidence demonstrates surface and in-air life of the coronavirus, the information does not provide usable, pragmatic information to those creating policies to decrease the spread of COVID-19. For example, many hospitals are rotating staff to treat COVID-19 versus non-COVID-19 patients. This strategy has minimal data to support personnel rotation frequency, and therefore may instead be increasing the risk of transferring COVID-19 to the non-COVID-19 areas. There is a lack of information for hospital administrators to implement mitigation measures that will be truly successful.

Pennington Biomedical Research Center and Our Lady of the Lake Regional Medical Center (OLLRMC) have created a solution to protect our frontline healthcare workers by generating novel, human data on the transmission of COVID-19 in a hospital setting. Functional data from real-world settings is key to frontline workers’ safety. We will obtain this data through the innovative repurposing of state-of-the-art location-sensing technology in OLLRMC. The real-time locating system uses small badges placed on patients and hospital staff that sense the precise location of personnel throughout the hospital, including proximity to other badges (personnel) along with timestamping locations and movement. Hospital personnel wearing the badge can communicate the precise proximity and length of time near a COVID-19 patient. Badges can also be placed on patients and identify other badge wearers within a defined distance (for example, three to six feet of social distancing), offering potentially the most robust proximity and duration information available to date for hospital settings.

This novel use of the real-time locating system has the potential to help inform mitigation strategies used in hospitals locally, nationally, and even worldwide. Data suggests the spread of COVID varies by healthcare position (those who work in units 24/7, like ICU nurses, versus float staff, respiratory physicians, or dietitians). All workers may have different exposure cutoffs regarding risk of infection. Once these cutoffs are established, we can develop and implement preventative strategies. The collective scientific understanding of COVID-19 transmission is growing, including how long COVID-19 lasts in the air or on surfaces, however none of this information provides functional data that demonstrates how COVID-19 exposure impacts healthcare workers. We will address this major gap by determining proximity and duration exposure cutoffs for COVID19 risk (for example, perhaps the highest risk is associated with spending a collective 20 hours within six feet of a COVID patient) and then suggest protective procedures, such as proactive COVID testing, alerting the worker of risk to minimize complacency, or changes in policies related to rotation staff. We may also be able to identify hospital hotspots of COVID-19 transmission.

The Health Security and Pandemics Challenge seeks solutions for communities around the world to prepare for, detect, and respond to emerging pandemics. Our solution analyzes real-world data to inform decision-making among hospital administrations so that they can implement policies that protect health workers. In so doing, we can ultimately slow the spread of an outbreak within a hospital and even outside the hospital walls. Our findings, which we intend to share broadly, will be replicable to hospitals around the world.

This project is innovative due to the novel application of RTLS technology to track COVID exposure of healthcare workers and perform retrospective contact tracing with real-world human data.

This is a new project utilizing and expanding current state-of-the-art technology already in limited use at Our Lady of the Lake Regional Medical Center (OLLRMC) in Baton Rouge, Louisiana. In late 2019, OLLRMC invested in Midmark’s real-time locating system with the goal of gathering actionable insight to improve workflow. Today, the hospital is utilizing this technology for equipment tracking and ‘staff-assist’ functions, specifically, the ability for a badge-wearing staff member to send an alarm notifying other hospital personnel of the precise location of a staff member in duress.

Pennington Biomedical Research Center (PBR) and OLLRMC have a multi-phased plan to transform the current use of this technology by adding badges to include all hospital staff and patients in order to obtain data that will allow us to inform policies related to protecting healthcare workers and preventing within-hospital spread of COVID-19. Phase 1 can be completed very quickly through the addition of the COVID units at OLLRMC. Within six months of sufficient funding to add the COVID units, we will begin to provide concrete policy suggestions to hospitals related to proximity and duration to keep frontline healthcare workers safe and prevent within-hospital spread of COVID-19.

This is a new application of an existing technology, specifically, Midmark’s real-time locating system. The system works in the background, gathering location data on people and equipment. Wired or wireless sensors are installed throughout a facility and communicate to badges and tags worn by staff, patients, and also placed on equipment. We aim to repurpose this technology to track the locations of healthcare workers and patients and also tracking person-to-person interactions throughout the hospital. By integrating with the hospital electronic medical record (EMR) system and enrolling hospital staff in a study to track if or when they contract COVID19, we can create human data on disease transmission risk based on a person’s proximity AND duration of proximity to COVID19+ patients or other COVID19+ staff through retroactive RTLS data. By monitoring which healthcare workers become infected with COVID19, we can use this RTLS data to inform policies and procedures to protect healthcare workers. For example, if being near a COVID19+ patient for a collective 20 hours within 3-6 feet creates a higher risk for healthcare workers, preventative measures such as re-training on PPE procedures, prophylactic testing or re-assignment of at-risk staff (determined by real-time data) may be implemented to reduce healthcare worker risk. Regardless of the rapidly developing processes currently in place, this novel use of existing technology will generate robust human data on healthcare workers and inform current or future practices. 

The RTLS technology is gaining increasing usage in hospital systems worldwide and is advertised as “accurate data and real-time intelligence by design.” The technology is primarily used to improve workflow, track important assets like equipment, and provide alerts to staff toward the location of another staff member in distress (when activated). Hospitals already integrate the RTLS technology into the electronic medical records. This system usually requires an expensive and timely installation, however, the hospital we are collaborating with (Our Lady of the Lake) already has the infrastructure installed and working in their hospital. We have met with the technology engineers and have determined the steps for implementation, which primarily require the minor installment of wireless sensors in new areas, the purchasing of badges for additional patient and staff monitoring and electronic medical record integration – all items and processes that are currently implemented at the hospital (and even worldwide in other hospital systems). The novelty of our approach is repurposing this technology to function as a means to track COVID19 risk and transmission instead of tracking equipment or staff members in acute duress. The massive amount of location data is already collected, analyzed and assessed through Our Lady of the Lake (hospital) and Midmark (technology provider). Pennington Biomedical has established itself as a world-renowned research institute and adds the expertise of clinical research methodology, data analysis, biostatistical approaches to utilize this large dataset to address COVID19 transmission questions.

Our long-term vision is to protect the safety of healthcare workers through collecting real-world, human information on the spread of COVID-19 among patients and healthcare workers.

Our theory of change is transforming our approach to collecting data for the mitigation of COVID19 spread. We aim to re-envision the process, which currently uses a lab-based data approach (e.g. COVID lifespan on surfaces or in the air in the lab setting, which are used to develop THEORIES of human transmission) to a real-world human data approach (using the real-time locating system technology to develop COVID19 proximity and duration exposure data).

The results from this study will inform hospital policies and procedures to reduce the spread of COVID-19 among patients and healthcare workers, which may provide additional protection to the community by safeguarding family and other close contacts of patients and healthcare workers.

The immediate impact of collecting data from the COVID units at OLLRMC will provide novel information on COVID-19 spread and risk to healthcare workers by utilizing state-of-the-art real-time locating system (RTLS) technology. The data collected will inform hospital procedures and practices to minimize healthcare workers’ risk by demonstrating viral spread in the real-world setting, rather than a controlled lab environment.

As we expand the project to additional areas of the hospital, we can add a contact tracing component to address non-frontline worker spread of COVID-19 and identify hotspot locations of COVID spread within the hospital. Current high-risk transmission areas are theoretical, for example, restrooms or cafeterias. This project allows real-world data that identifies where in the hospital COVID transmission occurs, especially when applied to non-healthcare worker staff, visitors or administrators.

Our solution, if funded, will immediately serve the 7,300 employees at Our Lady of the Lake Regional Medical Center by generating this novel, real-time human data on COVID19 exposure and risk assessment. If the policies and procedures created from this data are then shown to further reduce COVID19 transmission within the hospital, this project then has the potential to impact the other 6,146 hospital systems within the US and as well as hospitals worldwide. There is further potential this data may expand beyond this current epidemic as well. We will be creating human-data based policies and procedures rather than theories generated from lab-based experiments to protect disease spread. This solution also creates a template to mimic this research in other hospitals with COVID19 or other future respiratory-spread infectious diseases (epidemics/pandemics), so that the quickest and most efficient data can be collected to combat disease spread. 

Within 10 business days of funding, the technology can be purchased, acquired and installed by highly trained technicians. Within three months of funding, we anticipate to begin data analysis. Within six months of funding, we expect to use the acquired data to inform this hospital site on potential practices that may improve the safety of healthcare workers and prevent the spread of COVID-19. We have a history of successful scientific publication and communication practices and will distribute this information for the assessment and use by other hospitals and hospital systems as we work together to combat COVID-19.

As this data collection begins, we will continue to aggressively fundraise for this program, allowing us to add different units (for example, emergency room, ICU) throughout the hospital to provide an even more complete picture of how transmission spreads and identify hotspots for transmission in other areas of the hospital. We anticipate that this project will provide data that is implemented into functional hospital policies and procedures to prevent COVID19 spread within the hospital system; thus, a 5-year plan would be to create a blueprint of this research so that if (when) the next epidemic occurs, this research can be implemented at multiple hospital systems to generate quick and effective data to prevent disease spread within the hospitals, protecting frontline workers, patients, other staff and ultimately the population at large from disease.

The primary barrier is a financial one – without additional funding, we cannot proceed with this project. OLLRMC leadership and personnel are eager to assist with this project. We have a history of publishing our results in academic and professional journals. Because Louisiana faced a high number of cases early on in the pandemic, we can ensure that there will not be so many cases that the hospital personnel are overwhelmed. The research can be conducted successfully while maintaining the highest level of patient care.

Pennington Biomedical Research Foundation has pledged to assist with finding and seeking funding from multiple sources so that this solution can become a reality. Center Executive Director Dr. John Kirwan has also pledged support of this program. 

PBRC (research institute): 2

OLLRMC (hospital): 3

Nursing Technology Consult: 1

Our team represents a unique collaboration between a well-established research center, a prominent local hospital with COVID19 dedicated units and state-of-the-art real-time locating system technology, data management and electronic health record integration.

Baton Rouge is the ideal location for this program because Louisiana faced a high number of cases early on in the pandemic. We can share insights gained through this program to other locations that still have yet to hit their peaks or their second wave of infection as cities re-open from stay-at-home orders.

This solution represents a three-way partnership. Pennington Biomedical Research Center is a world leader in the research of obesity, diabetes, dementia and other diseases. Since its founding, Pennington Biomedical has led the scientific community in achieving breakthrough research. For over 30 years, our scientists have conducted groundbreaking science and translated this knowledge into community outreach programs that educate, prevent, diagnose and treat. The research enterprise includes approximately 63 faculty and 24 post-doctoral fellows who comprise a network of 43 laboratories supported by lab technicians, nurses, and support personnel, and 13 highly specialized core service facilities. Pennington Biomedical Research Foundation provides fundraising and financial management support services to the solution.

OLLRMC treats 35,000 inpatients and 650,000 outpatients annually for a full range of illness and injury, including those that are extremely complex, for both pediatric and adult patients. Their services include an 800-bed hospital and the area’s only Level II Trauma Center; a freestanding Children’s Hospital; a 450-provider care network covering more than 40 specialties; two free-standing emergency rooms; a network of nearly 15 urgent care clinics; outpatient imaging and surgery centers.

Pennington Biomedical will bring expertise in data analytics to this challenge, creating solutions that hospitals around the world can implement.

As a research-focused group our “business model” is focused on the dissemination of research-acquired data into actionable items for community members. For example, Pennington Biomedical Research Center was pivotal in the development of the DASH diet, which was the #1 ranked diet world-wide for 8 years by U.S. News and World Reports. This is the perfect example of how novel research approaches are utilized to collect data and then the results are developed into digestible information for the community. For this project, our goal is to generate data on COVID19 within hospital transmission and develop this into digestible information for hospitals to implement.

In terms of obtaining funding for the development of this project and eventual development and dissemination of functional guidelines, we have created a multi-phased approach to generate usable data while also creating a platform to apply for additional grant funding and further expand our data collection and analysis capabilities. An example is that the data used from this project will inform hospital policies and procedures to protect from COVID19. Those policies and procedures then need to be tested and compared to the original data to evidence an improvement and the potential for expansion to other hospital locations or even other hospitals around the country or world-wide.

Since the creation of both Pennington Biomedical Research Center and its 501c3 support organization, Pennington Biomedical Research Foundation, in 1988, the Foundation has raised more than $38.9 million to support the critical research needs of the Center. In addition, Pennington Biomedical Research Center has a long history of successfully securing federal grants for research-specific projects. Since 1991, NIH has invested $356 million in the Center's research. Foundation staff will continue to seek out new potential partners to fund additional components of this program. This solution, once fully funded, will not require additional funding in future years.

Pennington Biomedical Research Center’s sole focus is biomedical research. Being able to partner with a world leader and gaining access to business and entrepreneurship training would bring new perspectives and critical insights, as well as new strategies, to our proposed solution. Additionally, we are optimistic that this challenge will assist us in efforts to secure the funding necessary to make this solution a reality.

Additionally, as a research scientist interested in developing my independence, the mentorship and strategic advice from the Solve and MIT networks will be instrumental in gaining exposure to different areas of science and idea-generating platforms. I expect the Solve community to aid in the advancement of this idea and I am excited to be involved in the extended 9-month program to meet other innovative and motivated Solvers. 

Pennington Biomedical Research Center is a world leader in obesity, diabetes, and nutrition research and in taking our scientific discovery and translating it to programs that benefit the community. We welcome partnerships that will bring us new expertise and insights related to marketing, media and exposure. We want to be able to share our findings with as many people as possible. We also welcome the opportunity to hear expertise from infectious disease and hospital systems experts. This will not only help us assess the long-term data, but understand the functional translatability to other hospitals both in the United States and worldwide. 

Optimally, collaboration with infectious disease organizations, such as the Centers for Disease Control and Prevention (CDC), would dramatically improve our ability to translate the RTLS data into functional applications for diverse hospital settings and populations.

Outside of direct collaboration with infectious disease organizations and experts, we welcome innovative minds for brainstorming, feedback on study design, and data assessment. Our general approach is that new perspectives offer important insight, whether acted upon or otherwise. An example would be a group of healthcare professionals, non-healthcare professionals, community members, and hospital technology/communications experts joining on virtual or in-person meetings to hear thoughts, perspectives and additional applications of this work. It may also be beneficial to discuss study updates with a small team of various backgrounds, including frontline workers like nurses, medical doctors, and dietitians along with managerial hospital staff and a technology representative to ensure the project evolves with new or advanced technologies, systems and data analysis approaches.

Our solution, while local in nature, has implications for healthcare workers in hospitals across the globe. The Elevate Prize would benefit our ability to scale the impact of the solution and amplify philanthropy to ensure our solution becomes a reality. Specifically, our solution ties into The Elevate Prize Foundation’s recognition that healthcare workers are putting their own health and safety at risk to treat those infected and save lives.

If Pennington Biomedical Research Foundation is chosen for The Elevate Prize, the bulk of the funding will be used to purchase and install the technology to cover as many units within OLLRMC as possible. Remaining funds will be used for data analysis; policy and strategy recommendations; and distribution of this information via scientific and professional journals as well as more traditional publicity methods. With $100,000 we can incorporate all the COVID units. An additional $100,000 will allow us to add the emergency room. As funding increases, we will continue to add more units to obtain the most complete picture possible of how COVID spreads within hospitals.

Another potential collaboration is with artificial intelligence/machine learning to incorporate the RTLS data with EMR to 1) create a faster turnaround time from data collection to analysis and 2) potentially predict COVID19 transmission based on RTLS data among healthcare workers – for example, if a healthcare worker spends additional time in a COVID19 identified transmission hotspot, this healthcare worker can be alerted in real-time and potentially reduce risk by immediately modifying workspace habits.

Our solution utilizes data science to eliminate the gap between theoretical, laboratory understanding of COVID-19 spread and functional, human data. We will collect and analyze this data to protect frontline healthcare workers by suggesting policies and strategies to keep healthcare workers safe that are based on functional data rather than theory.

With appropriate growth and collaborations, AI technology can be used to analyze the real-time locating system technology to monitor the precise proximity and duration of hospital workers and patients. This information will provide real-world human data on COVID19 exposure and risk of contracting the virus. With the AI technology and real-time alerts, we can potentially identify healthcare worker risk and immediate alert staff or patients of risk, providing prophylactic care or changing day-to-day work habits to reduce spread of disease. With highly infectious diseases, disease spread may be dictated by the "weakeast link" in the chain of prevention - AI plus our proposed use of this real-time locating system technology will be able to quickly identify and efficiently alert high-risk individuals, allowing for proactive steps to prevent spread before it happens. 

Globally, hospitals implement generic pandemic procedures. However, in the absence of real-world evidence, it is unknown whether these policies are optimally mitigating COVID-19 transmission. For example, hospitals frequently rotate personnel to treat COVID-19 versus non-COVID-19 patients. It is unknown if this will minimize spread, and may, in fact, increase the spread. This can be directly addressed by the proximity and duration data proposed in this solution.

If Pennington Biomedical Research Foundation is chosen for The Elevate Prize, the bulk of the funding will be used to purchase and install the technology to cover as many units within OLLRMC as possible. Remaining funds will be used for data analysis; policy and strategy recommendations; and distribution of this information via scientific and professional journals as well as more traditional publicity methods. With $100,000 we can incorporate all the COVID units. An additional $100,000 will allow us to add the emergency room. As funding increases, we will continue to add more units to obtain the most complete picture possible of how COVID spreads within hospitals.

Our solution targets three of the UN’s Sustainable Development Goals. Our solution fits under the umbrella of Good Health and Well Being, working to ensure healthy lives and promoting the well-being of all. Our solution also targets the UN’s goal of Industry, Innovation and Infrastructure. By keeping our healthcare workers safe, we are strengthening the health industry worldwide. In addition, keeping healthcare workers safe will save health systems millions of dollars in economic costs. Finally, our solution also fits under Partnership for the Goals,  utilizing the best experts in highly different and specialized fields to create a novel solution to this and future pandemics.

This technology, especially in combination with AI robot learning and big data assessment, will quickly become an invaluable tool for any hospital. Hospitals are being build and upgraded more frequently than ever and this system can be inserted within the original build (technology infrastructure) of the entire hospital. By doing this, more hospitals will be able to immediate perform the most robust contact tracing of any infectious disease outbreak (which will inevitably occur again).