Process mining for clinical processes: A comparative analysis of four Australian hospitals

Partington, Andrew, Wynn, Moe T., Suriadi, Suriadi, Ouyang, Chun, & Karnon, Jonathan (2015) Process mining for clinical processes: A comparative analysis of four Australian hospitals. ACM Transactions on Management Information Systems, 5(4), 19:1-19:18.

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Business process analysis and process mining, particularly within the health care domain, remain under-utilised. Applied research that employs such techniques to routinely collected, health care data enables stakeholders to empirically investigate care as it is delivered by different health providers. However, cross-organisational mining and the comparative analysis of processes present a set of unique challenges in terms of ensuring population and activity comparability, visualising the mined models and interpreting the results. Without addressing these issues, health providers will find it difficult to use process mining insights, and the potential benefits of evidence-based process improvement within health will remain unrealised. In this paper, we present a brief introduction on the nature of health care processes; a review of the process mining in health literature; and a case study conducted to explore and learn how health care data, and cross-organisational comparisons with process mining techniques may be approached. The case study applies process mining techniques to administrative and clinical data for patients who present with chest pain symptoms at one of four public hospitals in South Australia. We demonstrate an approach that provides detailed insights into clinical (quality of patient health) and fiscal (hospital budget) pressures in health care practice. We conclude by discussing the key lessons learned from our experience in conducting business process analysis and process mining based on the data from four different hospitals.

Impact and interest:

3 citations in Scopus
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ID Code: 66728
Item Type: Journal Article
Refereed: Yes
Keywords: process mining, healthcare, patient flows
DOI: 10.1145/2629446
ISSN: 2158-6578
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Institutes > Institute for Future Environments
Copyright Owner: Copyright 2015 ACM
Deposited On: 28 Jan 2014 22:33
Last Modified: 18 Jan 2016 18:34

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