Seven health projects at the University of Utah have received seed grants that can accelerate the development and use of more science-based digital health applications in everyday healthcare.
The subsidy is Digital Health Initiative (DHI), It will focus on projects designed to create digital tools that are safer and more effective than those currently available, according to. Guilherme Del Fiol, MD, Ph.D., Co-Director of DHI and Professor of Biomedical Informatics at U of U Health.
Guilherme Del Fiol is Co-Director of DHI and Professor of Biomedical Informatics at U of U Health.
“The use of digital health applications by both patients and physicians has skyrocketed in recent years,” Del Fiol says. “But how many of these apps actually work as intended? Huh? Most of it is advertised with little or no rigorous scientific evidence.”
In fact, in 2019, an analysis of research conducted by America’s top 25 funders of digital health tools, such as wearable biosensors and mobile health apps, found that most of these products had low health outcomes, cost , or found to have no real impact on access. I be concerned. Another study of mental health apps concluded that of the 1,400 apps evaluated, only 14% were based on real-world experiences, and none mentioned certification or certification processes. attached.
“We see these seed grants as the perfect opportunity to change that trajectory,” said Del Fiol. “They represent the starting point for bringing innovative, reliable, and scientifically tested digital health applications from the bench to the bedside.”
Seed-funded projects receive up to $50,000 in one year. The researcher develops, tests and evaluates digital applications that fall into one of his four main areas of interest within DHI.
- Mobile apps and games for health
- Virtual reality and sensors
- Clinical decision support tool
- Integration with Electronic Health Record (EHR)
If successful, the project will proceed to clinical trials designed to evaluate its utility in the larger context, said Victoria Tiase, Ph.D., RN, DHI’s Director of Strategic Development.
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If successful, the project will proceed to clinical trials designed to evaluate its utility in the larger context, said Victoria Tiase, Ph.D., RN, Director of Strategic Development at DHI.
“Clinicians who treat patients at the bedside need more efficient care today,” said Tiase. “So we need to get more practical and effective digital tools in our pipeline. We hope these seed grants are a starting point for that effort.”
The seven seed grant recipients represent 11 U of U Health disciplines, ranging from anesthesiology to nursing to public health.
Project name/Overview/Winners
Coming Home Toolkit Health Record and Community Service Integration
Andrea Wallace PhD (Nursing)
Dr. Roger Altizer (Entertainment Art Engineering, Population Health Science)
Kensaku Kawamoto, MD, Ph.D. (Biomedical informatics)
Wallace and colleagues evaluate the effectiveness of a digital resource planner that enables patients to self-manage their health status after discharge. Called the “Getting Home Toolkit,” the planner includes sections on transportation, medication, errands, meals, household chores, personal care, billing, and insurance. It is also designed to help patients better communicate their needs to family, friends and healthcare providers.
Expanding the impact of home symptom care through EHR integration and implementation science
Elizabeth Sloss, Ph.D., MBA, RN (Nursing, Huntsman Cancer Institute)
Cathy Mooney Ph.D., RN (Nursing)
Justin D. Smith PhD (Population Health Science)
Guillerme del FiorMD, Ph.D. (Biomedical Informatics)
Kensaku Kawamoto, MD, Ph.D. (Biomedical informatics)
Symptom Care at Home is a program that helps cancer patients alleviate the symptoms that occur during cancer treatment. Seeking automated coaching or follow-up from a practitioner. This DHI seed grant will allow researchers to identify how home symptom care incorporates patient-reported symptoms into electronic medical records.
Patient-generated health data for geriatric patients
Dr. Jolie Butler (Biomedical informatics)
Butler collects patient-generated health data from chronic pain patients over the age of 65 using mobile devices such as Fitbit. Participating patients will examine their personal data and discuss it with the research team so that they can understand how these data can help them manage their own health. This research can be applied to care for future pain and other health conditions.
Expansion of intraoperative anesthesia information display and pharmacological prediction function
Ken B. Johnson, MD, MS (Anesthesiology)
Beca Chacin (Patient Simulation Anesthesia Center)
Soeren Hoehne (Patient Simulation Anesthesia Center)
Cameron Jacobsen, MS (Anesthesiology)
Noah Syroid MS (Anesthesiology)
Johnson and colleagues are combining an anesthesia prediction system with electronic medical records at U of U Health. The system provides anesthesia providers with visual guidance to monitor and predict levels of sedation, analgesia (analgesia), and muscle relaxation in patients undergoing general anesthesia.
Explainable AI for Equitable Risk Stratification of Atrial Fibrillation and Stroke
Dr. Mark Yandel (Human Genetics, Bioinformatics)
Martin Tristani Firozi MD (Pediatrics)
Benjamin Steinberg MD (Cardiology)
Yandell and colleagues are using artificial intelligence to create more accurate predictions of individual stroke risk. Computational models account for socioeconomic disparities that have rarely been considered in previous attempts to predict stroke. These considerations include housing, transportation, discrimination, access to nutritious food and exercise. These sophisticated predictions will enable physicians to provide patients with more personalized stroke prevention advice.
Remote sensing of autonomic function and mobility coupling using wearables to monitor recovery after mild traumatic brain injury.
Dr. Peter Fino (Health and Kinesiology)
Melissa Cortez, DO (Neurology)
Leland Dibble, Ph.D., PT (Physical Therapy and Athletic Training)
Fino and his colleagues aim to develop a system to assess individuals with persistent mild traumatic brain injury (mTBI) symptoms, such as concussion. Researchers use wearable home devices to monitor activity, heart rate, and other key metrics of mTBI.
Combining data streams from these devices worn at home, the researchers believe, could enable early identification of individuals with persistent mTBI symptoms and expedite rehabilitation when they show signs of abnormal recovery. increase.
Preliminary Feasibility of Spanish Translation and NeuroFlex: A Digital Cognitive Intervention for Late-life Depression
Sara Morimoto, Psy.D. (Population and Health Sciences)
Morimoto translates and tests a video game designed to ease depression in elderly Spanish-speaking volunteers. Called Neurogrow, the game lets players take care of a virtual garden, performing tasks such as watering, fertilizing, and getting rid of pesky bugs.
In previous studies, scientists found that Neurogrow helped relieve depression and improve cognitive function in older English-speaking non-Hispanic men and women. Researchers hope to see similar results in Spanish-speaking volunteers. If successful, we plan to use her Neurogrow more broadly in the Latino/Hispanic community.
