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.
Original language | English |
---|---|
Title of host publication | 2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 39-46 |
Number of pages | 8 |
ISBN (Electronic) | 9781538631874 |
DOIs | |
Publication status | Published - 1 Oct 2017 |
Event | 8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 - Phoenix, United States Duration: 1 Oct 2017 → … |
Conference
Conference | 8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 |
---|---|
Country/Territory | United States |
City | Phoenix |
Period | 1/10/17 → … |
Keywords
- Conformance-checking
- Event-logs
- Process Mining
- Sepsis
- Visual Analytics