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Process Mining for Clinical Processes
Author(s) -
Andrew Partington,
Moe Thandar Wynn,
Suriadi Suriadi,
Chun Ouyang,
Jonathan Kar
Publication year - 2015
Publication title -
acm transactions on management information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.603
H-Index - 29
eISSN - 2158-6578
pISSN - 2158-656X
DOI - 10.1145/2629446
Subject(s) - process mining , comparability , process (computing) , health care , quality (philosophy) , business , business process , business process management , data science , medicine , process management , knowledge management , computer science , work in process , marketing , political science , philosophy , mathematics , epistemology , combinatorics , law , operating system
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 nd it difcult to use process mining insights, and the potential benets 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 scal (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

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