A number of UICOMP faculty were among the investigators chosen as recipients of the spring 2021 grants from the Jump Applied Research for Community Health through Engineering and Simulation (ARCHES) program. Seven research projects are sharing more than $400,000 in funding aimed at addressing the challenges health care faces in the development of policies and procedures for mass vaccination, health care delivery, and quality and patient safety improvements.
The Jump ARCHES program is a partner-ship among UICOMP, OSF HealthCare and The Grainger College of Engineering at the University of Illinois Urbana-Champaign (U of I).
The funding supports research involving clinicians, engineers and social scientists to rapidly develop technologies and devices that could revolutionize medical training and health care delivery. A requirement of the grant applications was for solutions that could be deployed quickly, within four to six weeks. Investigators were also encouraged to consider how to best mitigate the impact of age, location, and social barriers in delivering quality health care to vulnerable populations.
John Vozenilek, MD, chief medical officer for innovation and digital health at OSF HealthCare, notes the importance of timely research and collaboration. “With the UK variant now the predominant virus in the U.S., it is critical that we leverage the talent at Jump Trading Simulation + Education Center in Peoria and the brilliant minds within engineering, technology and social science at the U of I. This will help us quickly find much-needed solutions to address the challenges health care faces in developing policies and procedures for mass vaccination, health care delivery, quality and patient safety improvements.”
Jump ARCHES Coordinator Seth Stutzman adds, “The outcomes of these projects will help with issues arising from the current pandemic and help physicians apply lessons learned in the post-COVID health care landscape.”
The funded projects with their investigators are listed below.
Every shot counts: development of a novel predictive model and toolkit to predict and decrease vaccine-preventable rural covid-19 deaths
Jimen Sung, PhD
Scott Barrows, MA, FAMI*
Adam Cross, MD*
Ann Willemsen-Dunlap, CRNA, PhD*
Mary Stapel, MD*
Currently, 50% of the U.S. population has received at least one COVID-19 vaccine, which is below the projected 70-90% required to achieve herd immunity to the virus. This project aims to develop a predictive model to forecast vaccine- preventable deaths in each county in the U.S. and the most likely reasons for vaccine hesitancy among populations. A toolkit will help guide rural populations in their decision-making about accepting the COVID-19 vaccine.
Human factors in the use of telepresence robots after the COVID-19 pandemic
Inki Kim, PhD
Jon Michel, MD*
Shandra Jamison, MA, RRT
The COVID-19 pandemic outbreak resulted in an increase in telemedicine visits to prevent the spread of the virus. The goal of this concept is to establish, justify and optimize a set of existing or new use cases for telepresence robot use in telemedicine to reduce the risk of in-hospital transmission of COVID-19 as well as for continued quality of care delivery in the post-COVID-19 era.
COVID-19 infection levels in central Illinois communities without access to frequent testing: a sewage monitoring and epidemiological modeling study
Thanh Helen Nguyen, PhD
John Farrell, MD*
New COVID-19 variants spread faster and have evaded some of the vaccineinduced protective immune response in the UK and other countries. To determine whether these factors will influence the level of infection and diversity of variants in areas that lack frequent testing, this project will collect and monitor the levels and genotypes of the virus in sewage collected at selected neighborhoods. The goal is to help public health officials prepare for increased burdens on health care facilities and workers.
Voice vitals: a new approach for anxiety and depression screening
in the era of COVID-19
Mary Pietrowicz, PhD
Ryan Finkenbine, MD*
Sarah Donohue, PhD*
Existing systems fall short in identifying and treating individuals with anxiety disorders and major depressive disorders due to a variety of issues including people not seeking medical attention, attitudinal barriers like stigma and structural barriers such as a lack of providers. This proposal aims to develop a prototype of machine models that can listen to speech and language and automatically screen for anxiety and depression disorders.
How to design and operate end-to-end vaccine deployment using social media, addressing supply chain allocations constraints and utilizing telemedicine
Anton Ivanov, PhD
Subhonmesh Bose, PhD
Albert England III, MD*
Ashen Eren Mehmet, PhD
Ujjal Mukherjee, PhD
Sebastian Souyris, Postdoctoral Fellow
Yuqian Xu, PhD
This idea aims to provide a comprehensive vaccine deployment strategy using data analytic frameworks. These frameworks will (1) shape population attitudes towards vaccination by reducing their uncertainty via social media channels, (2) provide a dynamic inventory management tool for perishable or sensitive goods, and (3) develop telemedicine-based solutions for convenient and sufficient post-vaccination patient support.
Building a motivational, interviewing conversational agent (mintbot) for promoting covid-19 vaccination among people with multiple sclerosis
Jessie Chin, PhD
Suma Bhat, PhD
Chung-Yi Chiu, PhD
Jared Rogers, MD*
Brian Laird, PharmD
Individuals with multiple sclerosis are likely to be hesitant to getting the COVID-19 vaccine due to their compromised health condition. This concept aims to develop an accessible, generalizable and efficient digital health solution for promoting COVID-19 vaccination among vulnerable populations, such as people with disabilities.
*denotes a UICOMP investigator