Visual analytics for evaluating clinical pathways

Abstract

Digital platforms in healthcare institutions enable tracking and recording of patient care pathways. Besides the Electronic Health Records (EHRs), the event logs from Hospital Information Systems (HIS) are a very efficient source of information, from both operational and clinical point of view. Process mining allows comparison of a patient care pathway with the event log(s) from HIS, to understand how well the reality as depicted in the event log fits the expectation as modeled using a care pathway. In this paper, we present SepVis, a visual analytics tool which aims to fill the gap in current process-centric applications by looking at patients' pathways from a clinical point of view. We demonstrate the utility of SepVis in selected use cases derived by the guidelines in the management of sepsis patients.

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