Aiding infection analysis and diagnosis through temporally-contextualized matrix representations

Determining infections and sepsis of severely burned adults in a timely fashion allows clinicians to provide necessary treatments to critically ill patients, potentially reducing the chance of mortality. In current practice, clinicians examine large amounts of heterogeneous medical records using a spreadsheet-like representation and perform analysis of descriptive statistics to aid in their decision making for sepsis diagnosis. A more efficient approach is required to streamline such a process; accordingly, we developed an interactive visual interface for supporting quick inspection and comparison of patients' retrospective clinical trajectories. In particular, we employ a timeline representation to present entire treatment contexts for individual patients, and an aggregated matrix representation for summarizing multiple data variables of individual patients over time. This provides clinicians with a compact and intuitive way to discover the important trends, patterns, and events that occur in the context of multiple patients. We present several possible use cases identified by clinicians using our system and show that our preliminary results have the potential to greatly improve diagnostic timing and accuracy of sepsis identification in critically ill patients.