Process Data Analytics for Hospital Case-mix Planning

, , , , , & Callow, Donna (2022) Process Data Analytics for Hospital Case-mix Planning. Journal of Biomedical Informatics, 129, Article number: 104056.

Free-to-read version at publisher website

Description

The composition and volume of patients treated in a hospital, i.e., the patient
case-mix, directly impacts resource utilisation. Despite advances in technology, existing case-mix planning approaches are mostly manual. In this paper, we report on a solution that was developed in collaboration with the Queensland Children’s Hospital for supporting its case-mix planning using process mining. We investigated (1) How can process mining capabilities be used to inform hospital case-mix planning?, and (2) How can process data be used to assess hospital capacity assessment and inform hospital case-mix planning? The major contributions of this paper include (i) an automated workflow to support both process mining analysis, and capacity assessment, (ii) a process mining analysis designed to detect process performance and variations, and (iii) a novel capacity assessment model based on limiting-resource saturation.

Impact and interest:

9 citations in Scopus
3 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

67 since deposited on 17 Mar 2022
40 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 228885
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Andrews, Robertorcid.org/0000-0001-7743-5772
Goel, Kanikaorcid.org/0000-0002-6250-2589
Corry, Paulorcid.org/0000-0003-3313-5967
Burdett, Robertorcid.org/0000-0003-2484-3646
Wynn, Moe Thandarorcid.org/0000-0002-7205-8821
Additional Information: Acknowledgements: This research was funded by the Australian Research Council (ARC) Linkage Grant LP180100542 and supported by the Princess Alexandra Hospital and the Queensland Children's Hospital in Brisbane, Australia.
Measurements or Duration: 11 pages
Keywords: Hospital case-mix planning, Process mining, Capacity assessment
DOI: 10.1016/j.jbi.2022.104056
ISSN: 0010-4809
Pure ID: 106999374
Divisions: Current > Research Centres > Centre for Data Science
Current > Research Centres > Centre for Agriculture and the Bioeconomy
Current > QUT Faculties and Divisions > Faculty of Science
Current > Schools > School of Information Systems
Current > Schools > School of Mathematical Sciences
Funding:
Copyright Owner: 2022 Elsevier Inc.
Copyright Statement: This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au
Deposited On: 17 Mar 2022 01:36
Last Modified: 06 Jul 2024 03:21