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Title: | Process data analytics for hospital case-mix planning | Authors: | Burdett, R. Callow, D. Wynn, M. T. Andrews, R. Goel, K. Corry, P. |
Issue Date: | 2022 | Source: | 129 , 2022 | Journal: | Journal of Biomedical Informatics | Abstract: | 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.L20174249062022-03-29 | DOI: | 10.1016/j.jbi.2022.104056 | Resources: | https://www.embase.com/search/results?subaction=viewrecord&id=L2017424906&from=exporthttp://dx.doi.org/10.1016/j.jbi.2022.104056 | | Keywords: | workflow;mining;human;child;articlecase mix;Queensland | Type: | Article |
Appears in Sites: | Children's Health Queensland Publications |
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