Prevention of medical errors is a key part of advancing patient safety and providing the best possible health care.
By reducing preventable harms, such as surgical complications and infections, hospitals and clinics could dramatically increase patient safety and save billions of dollars in health care costs.
Now, a nationwide coalition including the University of Utah Center for Evaluation of Health AI Research (UCHAI) aims to help build a model for improved patient safety in health care.
As one of four members of the Coalition for Advancing Safer Healthcare (CASH), researchers at UCHAI will investigate how direct-to-consumer technology can improve patient safety.
"UCHAI's role in the CASH project will be to give five national recommendations on how patients can use AI to improve the safety of their own care," says David Classen, MD, professor of epidemiology at University of Utah Health, the team leader of UCHAI, and leader of U of U Health's CASH working group. "These recommendations will be used to dramatically improve safety across the continuum of care." By empowering patients with technology, the working group's recommendations will help people make their own health care better.
UCHAI as a whole focuses on figuring out how to best use AI tools to improve health care safety, quality, and efficiency, so the center's expertise is ideally suited to the mission of the broader coalition. Ongoing research at UCHAI is working to ensure that electronic health record systems are safe and effective, detect and predict adverse health events, and develop and validate electronic safety measures.
Other partners in the coalition include the Johns Hopkins Medicine Armstrong Institute for Patient Safety and Quality, which will focus on large-scale health systems technology; the MedStar Health National Center for Human Factors in Healthcare, focusing on human factors; and the UC San Diego Health Joan & Irwin Jacobs Center for Health Innovation, looking into how to use data to improve patient safety.
