@inproceedings{d03c4e6858114f9d8fe72ef8670baba4,
title = "Measuring Patient Flow Variations: A Cross-Organisational Process Mining Approach",
abstract = "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.",
keywords = "Process mining, data quality, patient flow, data mining, Patient flow, Data quality, Data mining",
author = "Suriadi Suriadi and Mans, {Ronny S.} and Wynn, {Moe Thandar} and Partington, {Andrew Robert} and Jonathan Karnon",
year = "2014",
doi = "10.1007/978-3-319-08222-6_4",
language = "English",
isbn = "978-3-319-08221-9",
volume = "181",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer ",
pages = "43--58",
editor = "Chun Ouyang and Jae-Yoon Jung",
booktitle = "Asia Pacific Business Process Management. AP-BPM 2014",
note = "Business Process Management, AP-BPM 2014 ; Conference date: 03-07-2014",
}