The Sydney Dy Lab has conducted extensive research on quality of care, patient safety and decision-making, with a focus on patients with cancer and other serious and terminal diseases. Our team seeks to improve health systems and services to optimize the use of technology and medication, particularly in end-of-life health care policy. Our research approach includes primary and quantitative data collection, quality measurement improvement, systematic literature reviews and analysis of secondary database.

Research in the Michael A. Rosen Lab primarily focuses on patient safety and simulation-based health care training and technology. Recent work provided examples of how human factors experts can collaborate with health care professionals and simulationists (experts in the design and implementation of simulation) to use contemporary simulation to improve health care delivery. Another recent study examined the anesthesia practice at two tertiary care hospitals in Sierra Leone, West Africa, where anesthesia is associated with high mortality rates. We identified gaps in the application of internationally recommended anesthesia practices at both hospitals, likely caused by lack of available resources.

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.

Research in the John Matthew Austin Lab explores health care performance measures, with a goal of improving patient care by enabling healthcare providers to view data about their performance, track patient outcomes and comply with best care practices. Our lab is currently working to develop performance measures for the ICU part, and we are part of The Leapfrog Group, an annual survey of U.S. hospitals that compares hospital performance on national measures of safety, quality and efficiency. Our research also explores the use of scientifically sound decision-support tools for guiding improvements in healthcare delivery systems.

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.

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.

Research conducted in the Todd Dorman Lab examines the use of informatics in intensive care settings as it relates to remote patient monitoring, safety and management strategies. Specific areas of interest include the surgical stress response; aminoglycoside antibiotics; fungal infections; renal failure; pharmacokinetic models of drug administration; and ICU triage and its impact on disaster preparedness.

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 Sanjay Desai Lab focuses primarily on clinical outcomes in survivors of critical illnesses, such as acute lung injury. We also investigate techniques to improve graduate medical education and are conducting a clinical trial on the comparative effectiveness of models that optimize patient safety and resident education. Our research examines factors such as residency work-hour reform, hand hygiene practices and the use of etiquette-based communication.

Research in the John Ulatowski Lab explores the regulatory mechanisms of oxygen delivery to the brain and cerebral blood flow. Our work includes developing and applying new techniques and therapies for stroke as well as non-invasive techniques for monitoring brain function, fluid management and sedation in brain injury patients. We also examine the use of novel oxygen carriers in blood. We’ve recently begun exploring new methods for perioperative and periprocedural care that would help to optimize patient safety in the future.