Process mining based on patient waiting time: an application in health processes
International Journal of Web Information Systems
ISSN: 1744-0084
Article publication date: 21 June 2022
Issue publication date: 12 December 2022
Abstract
Purpose
Similar to many business processes, waiting times are also essential for health care processes, especially in obstetrics and gynecology outpatient department (GOD), because pregnant women may be affected by long waiting times. Since creating process models manually presents subjective and nonrealistic flows, this study aims to meet the need of an objective and realistic method.
Design/methodology/approach
In this study, the authors investigate time-related bottlenecks in both departments for different doctors by process mining. Process mining is a pragmatic analysis to obtain meaningful insights through event logs. It applies data mining techniques to business process management with more comprehensive perspectives. Process mining in this study enables to automatically create patient flows to compare considering each department and doctor.
Findings
The study concludes that average waiting times in the GOD are higher than obstetrics outpatient department. However, waiting times in departments can change inversely for different doctors.
Research limitations/implications
The event log was created by expert opinions because activities in the processes had just starting timestamp. The ending time of activity was computed by considering the average duration of the corresponding activity under a normal distribution.
Originality/value
This study focuses on administrative (nonclinical) health processes in obstetrics and GOD. It uses a parallel activity log inference algorithm (PALIA) to produce process trees by handling duplicate activities. Infrequent information in health processes can have critical information about the patient. PALIA considers infrequent activities in the event log to extract meaningful information, in contrast to many discovery algorithms.
Keywords
Acknowledgements
Conflict of interest: The authors declare that they have no conflict of interest.
Citation
Dogan, O. (2022), "Process mining based on patient waiting time: an application in health processes", International Journal of Web Information Systems, Vol. 18 No. 5/6, pp. 240-254. https://doi.org/10.1108/IJWIS-02-2022-0027
Publisher
:Emerald Publishing Limited
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