Analyzing the trajectories of patients with sepsis using process mining

F. Mannhardt, D. Blinde

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

59 Citations (Scopus)
387 Downloads (Pure)


Process mining techniques analyze processes based on event data. We analyzed the trajectories of patients in a Dutch hospital from their registration in the emergency room until their discharge. We considered a sample of 1050 patients with symptoms of a sepsis condition, which is a life-threatening condition. We extracted an event log that includes events on activities in the emergency room, admission to hospital wards, and discharge. The event log was enriched with data from laboratory tests and triage checklists.
We try to automatically discover a process model of the patient trajectories, we check conformance to medical guidelines for sepsis patients, and visualize the flow of patients on a de-jure process model. The lessons-learned from this analysis are: (1) process mining can be used to clarify the patient flow in a hospital; (2) process mining can be used to check the daily clinical practice against medical guidelines; (3) process discovery methods may return unsuitable models that are difficult to understand for stakeholders; and (4) process mining is an iterative process, e.g., data quality issues are often discovered and need to be addressed.
Original languageEnglish
Title of host publicationRADAR+EMISA 2017, Essen, Germany, June 12-13, 2017
Number of pages9
Publication statusPublished - 2017
EventRADAR + EMISA 2017 - Essen, Germany
Duration: 12 Jun 201713 Jun 2017

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


ConferenceRADAR + EMISA 2017


  • Medical guidelines
  • Patient trajectories
  • Process mining


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