Dr. Jenssen's research involves the use of clinical decision support systems and population health management techniques to protect children from secondhand smoke exposure and tobacco use. More broadly, he focuses on leveraging health information technology to engineer and implement novel approaches and products to improve care for children and their parents.
Dr. Phillips' research interests involve learning health systems and the intersection of technology and clinical informatics with clinical research for pediatric oncology patients. His current focus is on developing novel automated methods to identify cancer patients with malnutrition and optimizing their nutritional support. He has a secondary interest in quality improvement research for supportive care in pediatric oncology.
Dr. Zorc's work focuses on the intersection of interventional clinical research, quality improvement (QI), and clinical informatics. He has formal certification in epidemiology, QI methodology, and clinical informatics, and has participated in multi-center research networks, guideline and improvement collaboratives, and electronic health record development locally and nationally.
Dr. Forrest's research focuses on developing novel ways of conducting multi-center pediatric applied clinical research, child health services and outcomes research, pediatric person-reported outcome measure development and application, life course health science, learning health systems science, and policies and programs that promote the lifelong health of children. He has a particular interest in the concept and measurement of health.
Dr. Bailey’s research centers on the development of learning health systems. This endeavor includes the creation of methods to share data across hospitals, recognize the clinical implications of information gathered from different sources, and provide support to clinicians to use this information more effectively.
Dr. Fiks’ research is aimed at improving outcomes for ambulatory pediatric patients through primary care, practice-based scholarship with a focus on improving health and healthcare decision-making through health information technology.
Dr. Huang works on methodology development to understand the dynamics of disease activities and inform health management using multivariate longitudinal health data. She also works on data integration in Clinical Research Networks.
Dr. Tremoulet's current research interests include designing intelligent information systems that use human data (e.g. medical images, vital signs, reaction times, verbal, numerical or abstract reasoning assessments, neurological measures, etc.) to support healthcare and/or to improve job performance by enabling more effective human-machine interaction.
Dr. Masino and his team research the application and development of machine learning methods to inform basic scientific discovery and the creation of predictive analytic models for personal health and clinical decision support.