Jenna Marquard, PhD
Dr. Jenna Marquard is a Professor in the Population Health and Systems Cooperative Unit in the School of Nursing at the University of Minnesota. Her research lies at the intersection of human factors engineering and health informatics. The vision for my research is to help clinicians and patients make better decisions. My research aims to do this by providing these individuals with the right information, at the right time, in the right format. Our focus is often, but not always, on the use of health information technology (IT) as a key information resource for these individuals. We work under the premise that health IT is not meant to replace these individuals, but rather, that health IT has the potential to support or hinder these individuals as they make complex decisions. More recently, we have focused on the use of health information visualizations to support decision making.
If health IT is to support these individuals, we must understand how they search for and use information as they make decisions. If we can better understand these information search patterns, we can design health IT that helps these individuals find the information they need quickly, and in a format that helps them make better decisions. The major goal of my research has therefore been to understand how nurses, physicians, patients, and consumers search for and use information as they make complex decisions during tasks such as treatment planning, acute care episodes, and chronic disease management. For nurses and physicians, our focus has typically been on their use of electronic health records. For patients, our focus has typically been on their use of mobile technologies.
My research has been funded by the National Science Foundation (NSF), Agency for Healthcare Research and Quality (AHRQ), and the National Institutes of Health (NIH). Within NIH, our work has been supported by multiple institutes, including the National Institute of Nursing Research (NINR) and the National Institute of Allergy and Infectious Diseases (NIAID). This diversity in funding sources is attributable to longstanding collaborations across engineering, nursing, medicine, psychology, and computer science.