Optimization of Patient Treatment


A quarter of absolute healthcare expenses in the United States (about $750 billion) is assumed to be due to systemic inefficiencies, and thus unnecessary. Pinpointing and investigating healthcare inefficiencies has become feasible only recently through digitalization of healthcare and access to petabytes of electronic records detailing millions of patients. Such investigations have to be performed with close consideration that some downstream problems are caused by prior upstream events, and hence the root of these problems might be somewhere else in the clinical pathway of patients, a path that starts before admission and ends after discharge and usually consists of thousands of interactions between patients and the healthcare system. 

In our group, we develop technologies that support more effective and efficient information-driven clinical pathways, and concomitant methods of assessment, analysis and continuous improvement. These techniques can be used for clinical outcome prediction, risk analysis of treatment decisions, and identification of increased-risk patient categories. Analyzing retrospective digital patient records provides unique opportunities to develop technologies for realistic and challenging patient data and hence will have a stronger impact on improving individualized care delivered at hospitals. 

Our team, including colleagues, students, and staff, is now co-located across five sites – Malone Center for Engineering in Healthcare at the Johns Hopkins University, the Johns Hopkins Hospital (Baltimore, USA), Technical University of Munich, Ludwig Maximilian University of Munich, and Helmholtz Center in Munich (Munich, Germany). 

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