Measuring Patient Flow Variations: A Cross-Organisational Process Mining Approach

Suriadi Suriadi, Ronny S. Mans, Moe Thandar Wynn, Andrew Robert Partington, Jonathan Karnon

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

50 Citations (Scopus)


Variations that exist in the treatment of patients (with similar symptoms) across different hospitals do substantially impact the quality and costs of healthcare. Consequently, it is important to understand the similarities and differences between the practices across different hospitals. This paper presents a case study on the application of process mining techniques to measure and quantify the differences in the treatment of patients presenting with chest pain symptoms across four South Australian hospitals. Our case study focuses on cross-organisational benchmarking of processes and their performance. Techniques such as clustering, process discovery, performance analysis, and scientific workflows were applied to facilitate such comparative analyses.Lessons learned in overcoming unique challenges in cross-organisational process mining, such as ensuring population comparability, data granularity comparability, and experimental repeatability are also presented.

Original languageEnglish
Title of host publicationAsia Pacific Business Process Management. AP-BPM 2014
Subtitle of host publicationLecture Notes in Business Information Processing
EditorsChun Ouyang, Jae-Yoon Jung
Number of pages16
ISBN (Electronic)978-3-319-08222-6
ISBN (Print)978-3-319-08221-9
Publication statusPublished - 2014
Externally publishedYes
EventBusiness Process Management, AP-BPM 2014 -
Duration: 3 Jul 2014 → …

Publication series

NameLecture Notes in Business Information Processing
Volume181 LNBIP
ISSN (Print)1865-1348


ConferenceBusiness Process Management, AP-BPM 2014
Period3/07/14 → …


  • Process mining
  • data quality
  • patient flow
  • data mining
  • Patient flow
  • Data quality
  • Data mining


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