Research in the Pali Shah Lab focuses on lung transplants. Specifically, we’re interested in chronic rejection and quality and safety as they relate to lung transplants.

Research in the Asad Latif Lab focuses on patient safety and quality improvement. Our key interests include preventing hospital-acquired infections and improving health systems, the evaluation and prevention of healthcare errors and the utility of telemedicine in intensive care units. One recent study focused on reducing medication errors (the single most common type of error in healthcare) related to drug formulation in the intensive care unit.

Work in the Sean Berenholtz Lab focuses on patient safety, ICU care, quality health care and evidence-based medicine. Two notable and successful projects include the National On The Cusp: Stop BSI project, which was implemented in 47 states with the goal of eliminating bloodstream infections, and the Agency for Healthcare Research and Quality (AHRQ)-funded Keystone ICU project, which improved communication and teamwork and reduced hospital-acquired infections in more than 100 ICUs in Michigan. One recent study focused on ventilator-associated pneumonia (VAP), one of the most common type of health care-associated infections in the ICU. Existing VAP prevention intervention bundles vary widely on the interventions, but our research team described a structured approach for developing a new VAP prevention bundle.

The Mathioudakis lab is focused on developing and evaluating clinical decision support systems, technology, and mHealth for diabetes prevention and management. Our lab leverages large electronic medical record databases and uses machine learning algorithms and artificial intelligence to identify patterns in clinical care associated with optimal clinical outcomes. We are interested in understanding the role that advanced diabetes technologies can play in improving health outcomes for patients with diabetes. Our lab has published extensively on outcomes related to diabetes prevention and diabetes management and outcomes. Based on data from our long-term (over 10 year) clinic-based prospective cohort study from the Johns Hopkins Multidisciplinary Diabetic Foot and Wound Clinic, we have published extensively on clinical predictors and outcomes of patients with diabetic foot ulcers, focusing specifically on the role that glycemic control plays in patients with this complication. Healthcare disparities exist throughout medicine, but are particularly prominent in diabetes; our lab has evaluated healthcare inequities in diabetes outcomes and is developing and evaluating strategies to overcome them. In addition to identify optimal management approach to diabetes and its complications, our lab is interested in development and evaluation of innovative technology approaches to diabetes prevention.

Research in the Hanan Aboumatar Lab focuses on advancing patient-centered outcomes through improved patient and family involvement. We also focus on multilevel methods to increase the patient-centered focus of care delivery. Recent research examined the impact of a quality-improvement intervention on patient involvement in primary care and treatment with respect and dignity in intensive care.

The Timothy Niessen Lab studies patient outcomes in the ICU. We are particularly interested in the effects of sleep quality, delirium transitions and sedation on the improvement of intensive care patients. Our investigators also focus on the practices of internal medicine interns, studying the variability of hand washing hygiene, etiquette-based communication and time spent in direct and indirect patient care. We have also studied the onset of myelopathy as a result of B12 deficiency from long-term colchicine treatment and recreational nitrous oxide use.

The Suchi Saria Lab, part of the Institute for Computational Medicine, explores topics within the fields of machine learning and computational statistics, with a focus on computational solutions for problems in health informatics. Our team investigates the applications of machine learning and computational statistics to domains where one has to draw inferences from observing a complex, real-world system evolve over time. We use Bayesian and probabilistic graphical modeling approaches to address the challenges that emerge with modeling and prediction in real-world temporal systems.

Research in the Grant (Xuguang) Tao Lab explores environmental and occupational epidemiology topics, including workers' compensation and injuries, and nosocomial infections. We conduct research through clinical trials and systematic literature reviews, and also use cancer registry data and GIS applications in environmental epidemiological research. Our recent studies have explored topics such as the effectiveness of lumbar epidural steroid injections following lumbar surgery, the effect of physician-dispensed medication on workers' compensation claim outcomes and how the use of opioid and psychotropic medications for workers' compensation claims impacts lost work time.

Research in the Caleb Alexander Lab examines prescription drug use. This includes studies of population-based patterns and determinants of pharmaceutical use, clinical decision-making about prescription drugs, and the effect of changes in regulatory and payment policies on pharmaceutical utilization. We have special expertise in conducting survey-based studies and analyzing secondary data sources, including administrative claims, the Medical Expenditure Panel Survey and the National Ambulatory Medical Care Survey.

Researchers in the Kathleen Sutcliffe Lab study organizational adaptability, reliability and resilience. Our work examines how factors such as management teams, group dynamics, information search processes, communication and learning processes affect organizational performance. Our team also studies how an organization’s design and culture affect members’ abilities to sense, manage and respond to dynamic demands. Additionally, our work seeks to better understand the factors that promote individual and organizational resilience.