Towards Evidence-Based Analysis of Palliative Treatments for Stomach and Esophageal Cancer Patients: a Process Mining Approach

Pam Pijnenborg, Rob Verhoeven, M. Firat, Hanneke W.M. van Laarhoven, Laura Genga

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


Stomach and esophageal cancer are in the top ten most common cancers worldwide, both with high mortality rate.Approximately one-third of these patients have metastases at initial diagnosis and should receive personalized palliative care to improve their remaining life time. However, there is a lack of consensus about personalized palliative care options. This often leads to difficulties in determining the right treatment pathway for individual patients. This study investigates the applicatio nof process mining techniques on palliative care pathways for stomach and esophageal cancer to obtain an evidence-based understanding of which palliative treatments are commonly carried out in clinical practice and how they are associated with patients’ survival time. Given the high variability of the treatment pathways, ’local models’ are derived, rather than end-to-end process models, which are then validated with the aid of physicians. In addition, this study also investigates the use of predictive process monitoring techniques to predict patients’ life expectancy. The results show the benefit of taking the process-flow into account in predicting the outcome of the palliative treatments.
Original languageEnglish
Title of host publication2021 3rd International Conference on Process Mining (ICPM)
EditorsClaudio Di Ciccio, Chiara Di Francescomarino, Pnina Soffer
Number of pages8
ISBN (Electronic)978-1-6654-3514-7
Publication statusPublished - 25 Oct 2021
EventInternational Conference on Process Mining - Eindhoven University of Technology, Eindhoven, Netherlands
Duration: 31 Oct 20214 Nov 2021


ConferenceInternational Conference on Process Mining
Abbreviated titleICPM 2021
Internet address


  • Healthcare Processes
  • Local Process Mining
  • Medical services
  • Predictive Process Monitoring
  • Process monitoring
  • Stomach
  • cancer


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